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Iirs lecure notes for Remote sensing –An Overview of Decision Maker Document Transcript

  • 1. CONTENTS. No. Topics Faculty Page No.1. Overview of Remote Sensing Ms. Shefali Agarwal 12. Terrain Analysis Ms. Shefali Agarwal 153. Geographic Information System Mr. P.L. N. Raju 274. Fundamental Concepts of GPS Mr. P. L. N. Raju 385. Geo informatics for Natural Dr. P.S. Roy 69 Resources Management Dean, IIRS6. Applications in Agriculture and Soils Dr. S.K. Saha 1047. Applications in Forest Management Dr. S. P.S. Kushwaha 1178. Applications in Geosciences Dr. P.K. Champtiray 1289. Applications in Human Settlement Dr. B.S. Sokhi 139 Studies and Management10. Applications in Marine Sciences Dr. D. Mitra 14311. Applications in Water Resources Dr. S.P. Aggarwal 154
  • 2. 1 OVERVIEW OF REMOTE SENSING Shefali Agrawal Photogrammetry and Remote Sensing Division1. Introduction In recent times earth observation from aerospace media has gained significantimportance due to ever increasing demand for most authentic, timely and uniforminformation of earth surface features and processes involved. Due to rapid developmentand changing life style, the impact on environment and its effect on surface processesand features have under gone sea change. The impact of development on theenvironment is significant as the rapidly growing population; urbanization and otherdevelopment efforts have exerted tremendous pressure on natural resources and havecaused their depletion and degradation. Biodiversity is declining at an unprecedentedrate - as much as a thousand times what it would be without the impact of humanactivity. Half of the tropical rainforests have already been lost. Land degradation affectsas much as two thirds of the worlds agricultural land. As a result, agriculturalproductivity is declining sharply. The conservation measures are far from satisfactoryand as development processes and interventions still continue, natural resources will besubjected to greater damage in the future. Hence there is an urgent need to look foralternative strategies and approaches for better and more efficient management ofnatural resources in order to ensure their sustainable use. This is further compoundedby the ever increasing occurrences of natural hazards. Therefore, there is a greaterdemand for most authentic timely information on a suit of geophysical parameters andenvironmental indicators. Towards this space provides a vantage point where a largenumber of sensors have been deployed onboard satellites providing geo spatialinformation needed to understand the Earth system as a whole.1.1. Definition of Remote Sensing Remote sensing is the science of acquiring information about the Earths surfacewithout actually being in contact with it. This is done by sensing and recording reflected Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 3. 2or emitted energy and processing, analyzing, and applying that information (Lillesandand Kiefer, 2004).Remote sensing, also called earth observation, refers to obtaininginformation about objects or areas at the Earth’s surface by using electromagneticradiation (light) without coming in physical contact with the object or area. The basicprocess involved in remote sensing is the interaction of the electromagnetic radiationwith the Earths surface and detection at some altitude above the ground. RemoteSensing Systems have four basic components to measure and record data about anarea from a distance, Fig1. These components include: • Emission of electromagnetic radiation (EMR) • Transmission of energy from the source to the surface of the earth, as well as absorption and scattering • Interaction of EMR with the earths surface: reflection and emission • Transmission of energy from the surface to the remote sensor • Sensor data acquisition • Data transmission, processing and analysis Fig.1 Remote sensing process With respect to the type of energy resources, the RS technology is defined aspassive or active, Fig 2. Passive Remote Sensing makes use of sensors that detect the Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 4. 3 reflected or emitted electro-magnetic radiation from natural sources. Active remoteSensing makes use of sensors that detect reflected responses from objects that areirradiated by artificially generated energy sources, such as radar. Fig.2. Passive and active remote sensingWith respect to Wavelength Regions, the RS technology is classified as: • Visible and reflective infrared RS operating at a range of 0.4μm to 2.5μm. • Thermal infrared remote sensing operating at a range of 3μm to14μm. • Microwave remote sensing operating at a range of 1mm to1m. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 5. 4 ‘Optical range’ Cosmic Gamma X- Radio Electric power U-V Infrared Micro-waves TV rays rays Rays Visible spectrum Ultraviolet Blue Green Red Infrared (IR) 0.3μ m 0.4 0.5μ m 0.6 0.7μ m 10.0 15.0 300nm 500nm 700nm Wavelength Fig.3. Electromagnetic spectrum 1.2 Interaction of EMR with the Earths Surface Radiation from the sun, when incident upon the earths surface, is either reflectedby the surface, transmitted into the surface or absorbed and emitted by the surface. TheEMR, on interaction, experiences a number of changes in magnitude, direction,wavelength, polarization and phase. These changes are detected by the remote sensorand enable the interpreter to obtain useful information about the object of interest. Theremotely sensed data contain both spatial information (size, shape and orientation) andspectral information (tone, color and spectral signature). In the visible and reflective Infrared remote sensing region, the radiation sensedby the sensor is that due to the sun, reflected by the earths surface. A graph of thespectral reflectance of an object as a function of wavelength is called a spectralreflectance curve. Figure shows the typical spectral reflectance curves for three basictypes of earth feature vegetation, soil, and water in the visible and reflective Infraredregion Fig.4.The band corresponding to the atmospheric window between 8 μm and 14μm is known as the thermal infrared band. The energy available in this band for remote Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 6. 5sensing is due to thermal emission from the earths surface. Both reflection and self-emission are important in the intermediate band from 3 μm to 5.5 μm. In the microwave region of the spectrum, the sensor is radar, which is an activesensor, as it provides its own source of EMR. The EMR produced by the radar istransmitted to the earths surface and is reflected (back scattered) from the surface tobe recorded by the radar system again. The microwave region can also be monitoredwith passive sensors, called microwave radiometers, which record the radiation emittedby the terrain in the microwave region. Fig. 4. Typical spectral reflectance curves for vegetation, soil and water. In the microwave region of the spectrum, the sensor is radar, which is an activesensor, as it provides its own source of EMR. The EMR produced by the radar istransmitted to the earths surface and is reflected (back scattered) from the surface tobe recorded by the radar system again. The microwave region can also be monitoredwith passive sensors, called microwave radiometers, which record the radiation emittedby the terrain in the microwave region. 1.3 Platforms and Sensors In order to enable sensors to collect and record energy reflected or emitted froma target or surface, they must reside on a stable platform away from the target orsurface being observed. As space provides one of the most vantage points for earth Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 7. 6observation, two prominent orbits are considered for Earth observation: the geo-stationary orbit and the polar orbit. The geo-stationary orbit is such a position that itkeeps pace with the rotation of the Earth. These platforms are covering the same placeand give continuous near hemispheric coverage over the same area day and night.These are mainly used for communication and meteorological applications. This geo-stationary orbit is located at an altitude of 36,000 km above the equator Fig 5. Fig. 5 Geostationary and near polar orbits The second important remote sensing orbit is the polar orbit. Satellites in a polarorbit cycle the Earth from North Pole to South Pole. The polar orbits have an inclinationof approximately 99 degrees with the equator to maintain a sun synchronous overpassi.e. the satellite passes over all places on earth having the same latitude at the samelocal time. This ensures similar illumination conditions when acquiring images over aparticular area over a series of days. The altitude of the polar orbits varies from 600 to900 km, approximately.1.4. Resolutions In general resolution is defined as the ability of an entire remote-sensing system,including lens antennae, display, exposure, processing, and other factors, to render asharply defined image. It depends on large number of factors that can be groupedunder: Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 8. 7a. Spectral resolution: The spectral band in which the data is collected.b. Radiometric resolution: It is the capability of the sensor to differentiate two objectsbased on the reflectance / emittance differences.c. Spatial resolution: It is the capability of the sensor to discriminate the smallestobject on the ground. Higher the spatial resolution smaller the object that can beidentified Spatial resolutions vary from few kilometers to half a meter.d. Temporal resolution: It is the capability to view the same target, under similarconditions at regular intervals. Today a large number of earth observation satellites provide imagery that can beused in various applications.2. Indian Remote Sensing Satellites India is one of the major providers of the earth observation data in the world in avariety of spatial, spectral and temporal resolutions. India has launched severalsatellites including earlier generation IRS 1A, IRS 1B, IRS 1C, IRS 1D, IRS P2,IRS P3,IRS P4 and latest P6 and Cartosat series for different applications, the details of theseare listed in Table 1.Table 1: Indian Earth Observation Satellites. Spectral Swath Satellite No. of Resolution Revisit Launch Sensors Types Range Width Name Bands (m) (days) (µ) (km) MarchCartosat-1 PAN 1 2.5 m 25 2005 0.52 - 0.59 17th 0.62 - 0.68IRS-P6 October LISS -III MSl 4 23 140 24 0.77 - 0.86 2003 1.55 - 1.70 Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 9. 8 0.52 - 0.59 0.62 - 0.68 AWiFS MSl 4 56 740 0.77 - 0.86 1.55 - 1.70 0.52 - 0.59 0.62 - 0.68 LISS -IV MS 3 5.8 23.9 5 0.77 - 0.86 LISS -IV PAN 1 0.62 - 0.68 5.8 70 5 OCM MS 8 0.4 - 0.885 360 m 1420IRS-P4 May 26, 6.6,10.65, 120, 80, 2(Oceansat) 1999 MSMR RADAR 4 1360 18, 21 GHz 40 and 40 0.62-0.68 (red) WiFS MS 2 189 774 5 0.77-0.86 (NIR) 0.52-0.59 (green) SeptemberIRS-1D 0.62-0.68 - 1997 3 23 142 (red) LISS-III MS 0.77-0.86 24-25 (NIR) 1.55-1.70 1 70 148 (SWIR) PAN PAN 1 0.50-0.75 6 70 0.62-0.68IRS-1C 1995 (red) WiFS MS 2 189 810 5 0.77-0.86 (NIR) Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 10. 9 0.52-0.59 (green) 0.62-0.68 3 23.6 142 (red) LISS-III MS 0.77-0.86 24-25 (NIR) 1.55-1.70 1 70.8 148 (SWIR) PAN PAN 1 0.50-0.75 5.8 70 450-520 0.52-0.59 LISS-I MS 4 0.62-0.68 72.5 148IRS-1B 1991 0.77-0.86 22 (NIR) (same as LISS-II MS 4 36.25 74 LISS I) Same as LISS-I MS 4 72.5 148 aboveIRS-1A 1988 22 Same as LISS-II MS 4 36.25 74 above3. Global Satellites Global remote sensing satellites include Landsat, SPOT, ASTER, MODIS, MOS,JERS, ESR, Radarsat, IKONOS, QuickBird etc (Table 2): Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 11. 10 Table 2: Earth Observation satellites from other countries Spectral Swath Satellite No. of Resolution Revisit Launch Sensors Types Range Width Name Channels (m) (days) (µ) (km) 0.43-0.47 (blue) 0.61- 600 xSPOT -5 May 2002 VMI MS 4 0.68(red) 1000 1 120 0.78-0.89( NIR) 1.58- 1.75(SWIR) 0.5-0.59 (green) HRS 0.61-0.68 10 (red) 10 MS 4 60 26 0.79-0.89 10 HRG (NIR) 20 1.58-1.75 (SWIR) 5 m, combined to PAN 1 0.61-0.68 60 generate a 2.5-metre product. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 12. 11 10 m (resampled 1 0.61-0.68 at every 60 PAN 5m along track) blue (0.45- 4 2.5 m 17 km 0.52) green (0.52-0.6) MSQuickBird- Oct. 18, red (0.63-2 2001 0.69) NIR.76- 0.89) PAN 1 0.45-0.9 0.61 m Dec. 5, 12.5EROS 1 PAN 1 0.5-0.9 1.8 m 1-4 2000 kmTerra VNIR - Dec. 18,(EOS AM- 3 stereo (0.5- 15 m 16 19991) 0.9) ASTER MS 60 km SWIR (1.6- 6 30 m 2.5) 5 TIR (8-12) 90 m SWIR, TIR, CERES MS 3 20 km Total 360 MISR MS 4 250-275 m km MODIS 2 0.4-14.4 250 m 2330 5 500 m km Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 13. 12 29 1000 m 640 MOPITT MS 3 2.3 (CH4) 22 km km 0.45-0.52 (blue) 0.52-0.60 (green)IKONOS- September MS 4 IKONOS 0.63-0.69 112 24, 1999 (red) 0.76-0.90 (NIR) PAN 1 1M Landsat7 16TM As Landsat 4-5 30x30 185 705 km 15/04/1999 days Band 6: 10,40 - 60×60 12,50 Panchromatic: 15×15 0,50 - 0,90NOAA-K May - 1998 AVHRR MS 5 1100 0.5-0.59 VMI MS 4 1000 (green) 0.61-0.68 (red) March 24, 26SPOT-4 0.79-0.89 1998 MS 4 20 60 HRV (NIR) 1.58-1.75 (SWIR) PAN 1 0.61-0.68 10 60 Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 14. 134. Image Analysis and Interpretation In order to take advantage of and make good use of remote sensing data, wemust be able to extract meaningful information from the imagery. Interpretation andanalysis of remote sensing imagery involves the identification and/or measurement ofvarious targets in an image in order to extract useful information about them. Muchinterpretation and identification of targets in remote sensing imagery is performedmanually or visually by a human interpreter. It is also possible to apply digitaltechniques for image analysis and information extraction.9. Comparison of RS to Traditional Observations RS data, with its ability for a synoptic view, repetitive coverage, observations atdifferent resolutions, provides a better alternative for natural resources management,environmental monitoring and disaster management as compared to traditionalmethods. It provides images of target areas in a fast and cost-efficient manner. Whileair photos and fieldwork remain critical sources of information, the cost and time to carryout these methods often make them unviable and the human ability of observation issubjective and individual dependant, thereby making it even more unviable. RSinstrumentation makes it possible to observe the environment with EM radiation outsidethe visible part of the EM spectrum; the invisible becomes visible. RS is flexible in thatthere is a variety of RS observation techniques and a diversity of digital imageprocessing algorithms for extracting information about the earths surface. The data canbe easily integrated into a Geographical Information System thus making it even moreeffective in terms of solution offering.6. Future Prospects In near future large number of new satellites will be launched by India and othercountries with capabilities of providing high spatial, spectral and radiometric resolutiondata for variety of applications like water security, disaster management, naturalresource management, food security, infrastructure development etc. The use ofgeosynchronous orbit for providing high spatial resolution data will be a major break- Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 15. 14through to receive bio-geophysical parameters in real time basis. Remote sensingcoupled with geographical information systems where the data can be integrated withother information, will provide geo-spatial information that is critical for decision makingrelated to natural resource utilization, environmental monitoring and disastermanagement.ReferencesLillesand T.M. and Kiefer R. 2004: Remote Sensing and Image Interpretation (Third Edition). John Wiley, New York.Web Linkshttp://www.ccrs.nrcan.gc.ca/ccrs/learn/tutorials/fundam/chapter1/chapter1_2www.planetary.brown.edu/arc/sensor.htmlhttp://www.ersc.edu/resources/EOSC.htmlwww.isro.orgwww.spaceimage.comwww.eospso.gfc.nasa.govwww.landsat.orgwww.spotimage.fr/homewww.space.gc.cawww.esa.int/export/esasa/ESADTOMBAMC_earth_O.html Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 16. 15 TERRAIN ANALYSIS Shefali Agrawal Photogrammetry and Remote Sensing Division1. Introduction Terrain components play an important role in natural resource survey,environmental monitoring and natural hazards survey and analysis. Terrain features arethe most common features that can be observed from EO systems. Most importantly the3-D attribute/nature of the terrain can also be mapped and monitored using presentgeneration of EO systems using stereo viewing capability of Cartosat-1, SPOT ALOSPrism etc. and InSAR (Interferometric SAR) capability of Envisat and Radarsat. Terrainfeatures such as elevation, slope, aspect, and curvature influence most of the surfaceprocess including soil erosion, slope failures and vegetation composition. One of themost important attributes of terrain, topography influences atmospheric, hydrologic andecologic processes, such as, microclimate, local wind circulations and precipitation-runoff processes. Soil formation is also a function of relief, slope and geomorphology.Topographical features such as drainage basins, stream networks and channels, peaksand pits, drainage divides (ridges) and valleys play an important role in hydrologicalmodeling related to flooding, locating areas contributing pollutants to a stream,estimating the effects of altering the landscape etc. Relief information is also requiredfor removal of terrain distortions in aerial and satellite images and for creation oforthorectified image maps. Terrain visualization has also an important place in militaryand civil engineering operations. Based on the above application requirements and EOopportunities, a lot of emphasis is given on extraction of terrain features from usingoptical, radar, and Lidar data sets.2. Digital Elevation Model (DEM) The most important aspect of the terrain is relief that can be represented as a Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 17. 16continuous surface in the form of a Digital Elevation Model (DEM). In GIS, DEM is usedto refer specifically to a regular grid of spot heights. It is the simplest and most commonform of digital representation of topography. The term Digital Terrain Model (DTM) mayactually be a more generic term for any digital representation of a topographic surface.DEM, can be generated from the following basic relief information.a) Contour lines: Usually elevations on a topographic map are represented as a groupof contour lines with a discrete and constant contour interval.b) Grid data: For convenience of computer processing, a set of grid data with elevationare acquired from contour maps, aerial photographs or stereo satellite image data.Terrain data other than the grid data are interpolated from the surrounding grid data.c) Random point data: Terrain features are sometimes represented by a group ofrandomly located terrain data with three-dimensional coordinates. For computerprocessing, random point data are converted to triangulated irregular network (TIN). TINhas the advantage of easy control of point density according to the terrain feature,though it has the disadvantage of being time consuming in the random search for theterrain point.d) Surface function: Terrain surface can be expressed mathematically as a surfacefunction, for example, a Spline function3. Elevation Data Sources Elevation data can be obtained from the following sources • Survey data: including ground-based leveling and satellite-based GPS data; • Remotely sensed data: including radar altimeter data, laser altimeter data, optical and SAR stereoscopic image pairs, complex interferometric SAR data, and shade information in single images; and Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 18. 17 • Cartographic data: including contours, spot height points and surface structural lines digitized from paper topographical map sheets. Each data source has its own inherent strengths and limitations in terms of theavailability, accuracy, sampling density and pattern, and the ground coverage.4. Elevation Data Acquisition Techniques At present a number of techniques are available for acquiring digital elevationdata. The ground survey and aerial photogrammetry represent the traditional elevationextraction and measurement techniques. Contour-based topographical maps have longbeen the primary storage media for terrain information throughout the world. GPS,satellite image based stereoscopic technique, SAR interferometry, radar altimetry, andlaser altimetry are relatively new techniques for digital elevation acquisition. The adventof new data capture technologies has increased the acquisition speed of elevation data,improved the position and height measurements, extended their ground coverage, andreduced the cost. Ground survey and satellite-based GPS technology tend to generatevery accurate positional and height measurements. Since both ground survey and GPStechniques require physical visit of ground sampling points, the resulting measurementsare usually sparse. Often, they are utilized as GCPs (Ground Control Points) forextracting more dense elevation data from stereo photogrammetric and InSARtechniques or used as checking points for the DEM accuracy assessment.5. Digitizing Topographic Maps Due to the relatively low cost and the widest availability, the digitization oftopographical maps represents the practical method for gathering digital elevation datafor a large area, particularly for national and continental scale projects. Cartographicdata are the second hand topographical information source, in the sense that they areoriginally derived from direct height measurements of some kind. The information Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 19. 18content of a topographical map depends on not only the quality of original source databut also map scale and contour interval. In addition to contours and spot heights,topographical maps may also contain, implicitly or explicitly, many important terrainfeatures such as surface break lines, ridges and drainage lines.6. Photogrammetry-Based Stereo Technique The photogrammetry-based stereo technique derives the digital elevation databased on parallax differences between a stereo image pair. The principle is simple; first,two images are acquired of the same area with slightly different viewing perspectives(stereo-overlap). These images are then aligned and geometrically matched so that amathematical (triangulation) model can be obtained. The analyst then has theopportunity to view the modeled stereo pair in 3D to manually extract the terraininformation or use automated stereo correlation tools to extract a new DTM. Theautomated process is typically used when the surface landscape needs to be extracted.“Above-the-landscape” features (e.g., buildings) are typically derived manually (usingstereo extraction tools) and then “placed” on the DTM. The accuracy of the elevationdata derived from stereo technique is often influenced by mismatch of conjugate imagepixels, and errors of the sensor position and attitude. The current and future high-resolution earth observation satellites (table 1) having a spatial resolution of 1m & lessand stereo capabilities will go a long way in the field of mapping in terms of cost, timeand accuracy.Table 1: High resolution sensors Sensor Launch Date Resolution IRS-1C 28-DEC-95 Panchromatic: 5.8 m IRS-1D 29-SEP-97 Panchromatic: 5.8 m IKONOS 24-SEP-1999 Panchromatic: 1 m Multispectral: 4 m Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 20. 19QuickBird 18 October 2001 Panchromatic: .61 m Multispectral: 2.44 mEROS A1 05-DEC-2000 1.8mCBERS 3 2003 Panchromatic: 5 mEROS B1 2003 Panchromatic: .81 mEROS B2 2003 Panchromatic: .81 m Multispectral: 3.3 mSPOT- 5 1985 Panchromatic: 2.5m from 2 x 5m scenes Panchromatic: 5m (nadir)Terra-ASTER December 1999 Multispectral (B1-B3) 15mCartosat-1 May 2005 (Panchromatic): 2.5 mALOS - PRISM January 2006 Panchromatic: 2.5 mWorldView 1 September 2007 Panchromatic: 0.55 mGeoEye-1 August 2008 Panchromatic – 0.41m Multispectral : 1.65m Fig. 1. Photogrammetric technique (www.univcalagary) Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 21. 207. Synthetic Aperture Radar (SAR) Interferometry Incidence Revisit Year of Ban Polarizatio Swath ResolutSAR sensor angle (days) launch d n (km) ion (m) (deg.) The interferometric SAR (InSAR) technique has emerged as a precise approachto the extraction of high-resolution elevation data and measurement of very smallsurface motion (displacement); InSAR technique is based on the phase informationderived from the complex radar images. SAR interferometry combines complex radarsignals (images) recorded by the antenna at slightly different locations to measure thephase differences between the complex radar images. Relating two complex SARimages of the same scene acquired at two orbital locations forms an interferogram. Asthe radar signal transmitted by the SAR sensor is coherent, the complex SAR imagepossesses both phase and magnitude (quantities) information. The constructive anddestructive interference of coherent SAR images respectively recorded at slightlydifferent locations produce an interferogram with a two-dimensional fringe pattern,which can be unwrapped into the absolute measurement of elevation. Fig. 2. Principle of SAR interferrometry (www.aerosensing.com) Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 22. 21ERS-1 1991 C VV 23 100 30 35JERS-1 1992 L HH 35 75 18 44ERS-2 1995 C VV 23 100 30 35Radarsat-1 1995 C HH 10 to 50 40-500 8-100 24SRTM 2000 X, C VV Variable 30-350 20-30 HH/HV, 100- 30-Envisat-1 2002 C 14 to 45 35 VV/VH 400 1000 VV, HH,PALSAR 2004 L HH/HV, 18 to 55 70 10-100 44 VV/VHTerraSAR-X 2006 X Quad-pol 10 to 100 15-60 2-16 11Radarsat-2 2008 C Quad-pol 10 to 50 10-500 8-100 24 20 to 49 (qualified) 10 to 20RISAT 2008 C Quad-pol 10-240 3 - 50 13 and 49-54 (unqualifie d)Table 2: SAR satellites and sensors8. Radar Altimetry Spaceborne radar altimeters have been deployed on board of Geosat, Seasatand ERS-1 platforms for acquiring surface height measurements. A radar altimeter is anadir-pointing active microwave sensor designed to measure the surface height overocean and ice surfaces. The radar altimeter transmits a short duration Ku-band pulsevertically downwards, and then tracks the returned radar pulse. The information of theshape and timing of the returned signal is utilized to estimate the surface height. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 23. 22 Radar altimeters can provide accurate elevation measurements regardless ofweather condition over ocean and relatively flat and low-slope ground surface, but areprone to errors over highly sloped and rugged lands due to the relatively large footprint.9. Laser Altimetry A laser altimeter can provide height measurements of submeter level accuracywith the aid of GPS and Inertial Navigation System (INS) in determining the position andattitude of aircraft or spacecraft, but the data collection is usually time consuming due toits narrow ground swath. Laser altimeter data may deteriorate in the condition of badweather, such as clouds and precipitation, it generally provides much more accuratemeasurements than the radar altimeter due to the small footprint of the laser beam. Fig. 3. Principle of laser scanning (www.terraimaging.com)10. Derivation of Surface Parameter10.1 Elevation If the point of interest is exactly at a point in the raster, the elevation can be takendirectly from the database If the point of interest is between nodes of DEM grid, weneed to interpolate from neighboring grid points, e.g. bilinear, cubic, or fit a plane to thenearby raster points. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 24. 2310.2 Slope Measure the surface steepness; Slope is rise over reach (rise/reach), where riseis the change in elevation, and reach is the horizontal distance. It is expressed as: a ratio, a simple fraction, a percent, an angle in degrees.10.3 Aspect (azimuth orientation) Aspect is azimuthal direction of maximum surface slope with reference to truenorth. Aspect calculation is very sensitive to elevation errors, especially when thesurface slope is small. Without a slope, there is no topographic aspect. The aspect ateach location determines the direction of water flow over the terrain surface.10.4 Surface Curvature (convergence/ divergence) The surface curvature is the second derivative of the surface (i.e., the slope ofthe slope); the curvature of a surface can be calculated on a cell-by-cell basis. For eachcell, a fourth-order polynomial of the form is fit to a surface composed of a 3x3 window.10.5 Profile Curvature The curvature of surface in the direction of slope is referred to as the profilecurvature. Profile curvature indicates where the surface is concave or convex, resultingacceleration or deacceleration of flow. Where acceleration of flow occurs, the streamgains energy and its ability to transport particles increases. Therefore, areas of convexprofile curvature indicate areas of erosion. Conversely, in areas of concave profilecurvature, the flow rate decreases, the stream loses energy, and deposition occurs. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 25. 2410.6 Planform Curvature The curvature of a surface perpendicular to the direction of slope is referred to asthe planform curvature. Planform curvature indicates where the surface is concave orconvex, resulting in convergence or divergence of flow respectively; Convergent flowindicates a concentration of runoff and would indicate a valley. Alternatively, divergentflow would indicate a ridge.10.7 Cut and Fill Calculation Estimation of the volume of material related to cutting and filling. By subtractingthe upper (top) surface height values from the lower surface height, a variable thickness(depth) value can be obtained. The thickness values over the entire area can beintegrated to obtain the volume. Engineers need to establish road or railroad routes andgradients that minimize the movement of earth. It is generally most economical tobalance the amount of material removed from the high areas (cut) with the amount ofmaterial required to fill low areas (fill). Also used in Reservoir capacity estimation, icevolume, etc.11. Viewshed Analysis A viewshed is the region that is visible from a given vantage point in the terrain. Itassembles all the areas where the line of sight is rising as the rays move outwards. Theyes/no values can be summed to give a cumulative sense of how many times a place isseen. Inter-visibility (what can be seen from where) can be computed based on a set ofrays radiating outwards from a vantage point. In a complex 3D situation, there are manyeffects to calculate, but on a surface the surface can only obstruct a view by risingabove the line of sight. Applications of viewshed analysis include GPS signalavailability, scenic beauty evaluation, sitting television, radio, and cellular telephonetransmitter and receiver towers, locating towers for observing forest fires or enemymovement. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 26. 2512. Watershed Analysis The shape of a terrain determines the movement of water across the terrainsurface; Water will flow from higher locations downwards. A raster DEM containssufficient information to determine pattern and characteristics of a drainage basin, suchas, the upstream area contributing to a specific location and the downstream path waterwould follow, the boundary of catchment area, flow line, ridges, the hierarchical streamsystem, etc. The topology of terrain surface (skeleton of surface): peaks, pits, ridges,courses (valleys), hills and dales, etc. The area upon which water falls, and the networkthrough which it travels to an outlet is referred to as a drainage system. The flow ofwater through a drainage system is only a subset of the hydrologic cycle, which alsoincludes precipitation, evaporation, and groundwater; Watersheds tend to functionecologically as single, uniform regions. Ecologists, hydrologists, engineers, pollutionand flood control experts need to be able to define these areas precisely.13. Dem Visualization There are number of techniques to enhance and display DEM data. Shaded reliefis also one of the techniques, which is considered to be one of the most effectivetechniques for representing topography.13.1 ShadingThe gradation from dark to light in a single color according to specific principals for thepurpose of creating a three dimensional effect is called shading. In contrast to the metricaccuracy of contour lines, hill shading is primarily used for its visual effects. Slopeshading operates on the principal that the steeper the slope - the darker the shade.Oblique shading or hill shading is based upon the effect of an oblique light source on aterrain surface. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 27. 2613.2 Slope ShadingSlope shading, operates basically on the principal of the steeper - the darker.13.3 Hill Shading Hill shading is also known as a shaded relief or simply shading, it attempts tosimulate how the terrain looks with the interaction between sunlight and surfacefeatures. It Helps viewers recognize the shape of landform features on a map.14. Conclusions Terrain analysis typically encompasses numerical methods of describinglandscape attributes such as terrain roughness, vegetation, urban features, 3D modelsetc. To fully model the continuous terrain surface, a large number of points are requiredand DEM and TIN are two commonly used models of representing the continuoustopographic surface in digital form with a finite number of sample points. Most of thecommercial GIS systems provide both raster DEM and TIN model that can be used inspatial analysis and surface modeling. However, it is important to note that the mostcritical aspect of any terrain analysis is the accuracy of the terrain model it uses or howclose the data model either DEM/TIN represents the actual surface with all attributes.Web Linkswww.isprs.orgwww.terraimaging.comwww.aerosensing.com Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 28. 27 GEOGRAPHIC INFORMATION SYSTEM P.L.N. Raju Geoinformatics Division1. Significance of GIS in the Present Day Scenario Geographic Information System plays an important role in creation ofgeospatial information from vast sources such as analogue and digital domains, andaid the decision makers at various junctures of resource identification, assessmentand management. It can answer many simple questions like what, where, how aswell as complex situations of using models for estimation, prediction and dynamicallyrecreate real world situation to visualise and fly though the area for effective planningand management. GIS is becoming quite popular in the recent past among thegeneral public with the introduction of Google earth (http://earth.google.com),Microsoft Virtual earth (http://www.microsoft.com/virtualEarth/) and NASA’sWorldwind (http://worldwind.arc.nasa.gov) for viewing rich Geographic content in theform of satellite pictures/maps in 2D/3D, explore, locate, navigate etc. With the helpof these resources people can find their location, assess the present situation andfind them the route to reach the destination, overlay the new surveyed routes andother information. World wide web has also become the source for viewingGeographic information in the form of maps and location information like Maps ofIndia (http://mapsofIndia.com). All types of tools used to carry out these tasks arepart of GIS with the background of satellite image. The 3d view and animation thatwe carry out on the images are carried out using GIS tools. Third Generation mobiledevices are integrated with (GPS) receiving capability are loaded with Geographicinformation (i.e. GIS data) and used to find where you are located and givingdirections to reach the desired destination (i.e. house/office/tourist destination etc). This summary note outlines status of GIS that includes importance of GIS andits role for different application studies, journey of GIS from a mere a tool to science,how important it is to create a geospatial database and its critical nature,transformation of GIS from commercial nature to the present potential of havingmany open source and free software for the user community, progress of GIS and its Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 29. 28market potential as on today, where to look and find different GIS resources in WorldWide Web and finally summarising the technological trends and future of GIS.2. GIS Application Potential The strength of GIS depends upon how good is the geospatial database. Itcan be used for natural resource application (i.e. forestry, agriculture and waterresources etc.) in combination with remote sensing and earth observation. Inaddition it is used for infrastructure development (i.e. highways, railways etc.); utilityservices like water supply distribution network, telephone network management, gassupply distribution etc.; business application such as real estate, establishment ofnew retailer shops; heath services; investigation services like crime incidences andtheir distribution etc and geospatial information kiosks like Bhoomi project(http://www.kar.nic.in/bhoomi.html) of Karnataka State. In addition GIS can be usedfor research and scientific investigations, particularly for water budgeting,atmospheric modelling, climatic studies and global warming.3. GIS: Tool to Science GIS has evolved from a mere tool into a spatial science covering broadspectrum of fields starting from surveying, mapping, modelling, and management todecision theory. A discussion forum was launched on “GIS is a tool or science?” wasinitiated in 1993 brought out many views about GIS (Wright et al., 1997): somestrongly feel that it is considered merely a tool as it helps only in manipulation ofspatial data, combines elements of computer science, geography and enablingtechnology in problem solving environment (Skelly, 1993); Petican,1990);Groom,1993); Feldman,1993). At the same time, many others argue that it is notonly a tool but also it is definitely a science as it addresses vast issues such asunderstanding of modelling spatial phenomena (Carlson, 1993), study of spatial datauncertainty and error, data lineage and how GIS is adopted by agencies (Wright1993 et al.,), spatial data representation and developing algorithms to solve aproblem and apply it to test a theory (Sandhu, 1993). According to some, GIS isconsidered as part of a broader information science (Wright et al., 1993), anenvironment as well as a method used to discover, explore, and test spatial theory Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 30. 29(Laffey, 1993) and concepts that the tools seek facilitate, automate, and develop arestrongly rooted in science (Bartlett, 1993). Amidst diverse views, growth of GIS isphenomenal and expanded to many areas like Environmental and Earth Sciences,Urban Planning & Infrastructure Development, Socio- Economic outreach, businessenterprise and technological domains, covering them under geoinformatics umbrellaand making itself an inevitable scientific field.4. Critical Part of GIS Hardware, Software, Data and trained Manpower makes it to total GIS.Though each component is important, the most critical part of GIS is data, i.e.creation of data needs three forth of cost involved to develop the total GISapplication project, highly trained professional are required to be part of geospatialdatabase creation and three fourth’s time is spend to accomplish the task of creatingthe geospatial database. All the users require the basic framework data like commondatum and projection, administrative, roads, topographical and land use / land coverlayer information. The issue is creation of the same by one and use it by many. Allcountries are in the process of creating it and it takes lot of time. India is also in theprocess of developing at national level (i.e. National Resource Repository (NRR)under ISRO /NNRMS and National Spatial Data Infrastructure (NSDI) under DSTand many others are in the process of development which in turn helps for overalldevelopment and progress of India.5. GIS Software: Commercial vs. Open/Free GIS software is one of the bottlenecks in GIS industry as the major junkmoney (~50 per cent or so) is invested towards its procurement and maintenanceannually. Because of it many users have apprehensions to change fromconventional methods to GIS. In the recent past there is a paradigm shift in usage ofGIS software. There are many new and open/free software are launched into themarket. The free software where it is freely available and mostly through www butthe user do not have access to program coding, so not possible to modify or updateit. In case of open source, it is free as well as available with full access to program Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 31. 30coding so user can modify/update it according to his requirements. Table 1 belowprovides list of some of commercial, open and free GIS software.Table 1: List of GIS software available commercially/as a open source/freely to the user.S.No. Software Functionality /RemarksCommercial Software1. ArcGIS Core modules,market leader but high cost, many more to be bought for other applications2. Geomedia Core modules of GIS, supports education and research institutions3. MapInfo Moderate cost4. AutoCAD Map Better input and database creation facility5. JTMaps Quite economical and works in vector model (India)Open Source6. GRASS GIS Satellite data analysis & GIS (http://grass.itc.it/)7. Quantum GIS Desktop GIS, supports all OS (http://qgis.org/)8. ILWIS Satellite data analysis & GIS (www.itc.nl)9. JUMP Read shp and gml format, display facility and support for wms and wfs, limitations of working with large data files (http://jump-project.org/)10. PostGIS With spatial extensions for the open source. PostgreSQL database, allowing geospatial queries (http://postgis.refractions.net/)11. Mapserver Web server GIS S/W (http://mapserver.gis.umn.edu/)Free Software12. ArcView Limited analysis functionality, old version13. TNTMIPS Satellite data analysis and GIS but limited to window size6. Indian Geospatial Market Indian Geospatial market has matured well and growing at much higher ratethan normal growth. Geospatial market can divide into three categories such as: Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 32. 31spatial data producing agencies, user organizations (government, private, andresearch and academic setup) and industry (private entrepreneurs). As per themarket survey and compilation work done by GIS development (Indian GeospatialHandbook 2008, published by GIS Development Pvt. Ltd.) the growth for the lastthree years (i.e. 2005 to 2008) is phenomenal and it is more 45 per cent increasefrom the previous years. The annual turnover increased from Rs. 760 crores in 2005that includes GIS (540), photogrammetry (120) and Image Processing (100) to Rs.1128 crores in 2006, i.e. an increase of 48 per cent. It is further increased to morethan double i.e. Rs. 1780 crores. The details of overall Geospatial Industry includingsoftware, hardware and Services, are shown in Table 2.Table 2: Status of GIS revenue during 2005-08 period (Crores of rupees) (source: GIS 540 800 1250 Photogrammetry 120 188 350 Image Processing 100 140 180 Total 760 1128 1780 Increase (%) - 48 58 Indian Geospatial Handbook, 2008). There are many institutions / organizations which generate Remote Sensingand Geo-Information products and provide services such as (SOI, NRSA, NATMO,GSI, FSI, CGWB, CWC, IMD, Census & ANTRIX etc.) and the products and servicesare used by many user organizations like Highways, Railways, Airways, Waterways,Telecom, Power, Water resources & Irrigation, Health, Education, Environment &Forest, Agriculture, Urban Development and Land Resources and RuralDevelopment etc. Geospatial entrepreneurs mainly owned by private provide valueadded services to the above said user organizations. There are around 120companies are involved in Geospatial industry, majority of contribution i.e. 85 percent of the revenue is generated by 15 per cent of companies. The top fourcompanies are Infotech Geospatial India (30 per cent), RMSI (4 per cent ), WapmerrIndia (0.6 per cent) and Pixel Group (0.6 per cent). The manpower required forgeospatial industry is met with many who had acquired their higher education /professional qualifications from more than forty programs in geospatial education,range from P.G. Diploma, and graduate in engineering to Masters in Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 33. 32Engineering/Technology/Science, are presently being run across the country atuniversity/ institutions level.7. GIS Web Resources World Wide Web has become an important source for accessing resources ofremote sensing, GIS and GPS in which one can even download the satellite data,GIS metadata, GIS themes, access to reading material, latest developments in theform of articles from newsletters, journals. One can access to online resources onpayment basis and many cases freely as well. Table 3 provide summary of few GISresources, emphasizing more in Indian context.Table 3: GIS web resources S.No. Hosted by and Website link Nature of resources Web access to Geospatial Information in India 1. National Natural Resources Natural Resource Repository (NRR) Information System generated under NNRMS, ISRO/DOS http://www.nnrms.gov.in National Remote Sensing Centre Browsing Indian Remote Sensing 2 http://www.nrsc.gov.in (IRS) data and buying for anywhere in India National Informatics Centre RS & GIS basic reading material 3. http://gis.nic.in/ National level spatial information search facility Indian National Centre for Ocean Provide ocean information and 4. Information Service (INCOIS) advisory services to the society, http://www.incois.gov.in/ industry, government, and scientific community Meteorological and Oceanographic Meteorological and Oceanographic 5. Satellite Data Archival Centre geophysical data products http://www.mosdac.gov.in/ Web Access to Geospatial Information World over Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 34. 33 1. USGS Education material Common place to refer for education http://education.usgs.gov/ material on RS, GIS and GPS CGIAR consortium for spatial Site for downloading SRTM DEM 2. information data at 90 m resolution http://srtm.csi.cgiar.org/ GIS Reading Material 1. GIS Development monthly GIS reading material and published magazine articles in the magazine for more than http://gisdevelopment.net ten years My Coordinates monthly magazine GPS, GIS and RS reading material 2. http://www.mycoordinates.org/ with more emphasis on positioning technology 3. Indian Society of Geomatics Newsletter (quarterly) on RS, GIS http://www.isgindia.org/ and GPS NNRMS Bulletin Biannual technical publication from 4. ISRO/NNRMS bringing out RS & GIS application project outputs Geospatial Today Monthly magazine on Geospatial 5. http://www.geospatialtoday.com/ technologies Geo Place Website of multiple GIS and business 6. http://www.geoplace.com/ related publications8. Technological Trends and Future of GIS Information and Communication Technology (ICT) has revolutionized andhelped GIS to great extend. According to Peter Croswell (2005) five important trendshave exerted profound influence on geo-technology industry and user community: • Pervasive high-performance computing • Digital connectivity • Geographic data capture and compilation • Geographic data management and visualization • Standards and open system Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 35. 34 Moore (Moore’s law) has predicted more than 25 years back that theprocessing power of computers doubles every 18 months for the same cost and thisis true even today. Increase in processing speed, availability of computers ataffordable cost, increase of analysis functionalities, and availability of web resourcesmade it possible in expanding the scope of GIS. In the last five years, hardwareadvances have offered GIS users a growing array of realistic and effective solutionsfor field and mobile computing needs as well. The Internet has been a driver foroverall IT development, and it forced the trend in digital connectivity. It has lead tothe development of Internet GIS (also called web GIS), that has played a major rolein expanding the GIS usage, helping the users to access the geoinformation at lowcost in client-server environment and it will continue to further with standards andbetter services. GIS technology has always been a tool for data visualization-portraying complex spatial data and patterns through the use of 2-D and 3-D mapsand displays. Technology for the visualization of geographic information has takensignificant leaps in the last 25 years. During this time, GIS users have seentremendous advances in graphic display and large-format plotting. Realistic 3-D citymodels as well as 3-D environment data; atmosphere and ocean in individualhorizontal layers can be investigated. Open standards and specifications hasbecome an issue due to the diverse formats and structures from different softwarehave complicated the integration efforts. Over the last ten years major developmentshave taken place for the open standards and specifications. OCC (Open GeospatialConsortium), ISO-TC 211, GSDI and many others at worldwide and country levelplayed a key role in development of these standards and it is continuing to expandalong with the ICT technological trends. As indicated above, the technological trendscan be categorized into five and summarized in the following Table 4 ( Dadhwal andRaju, 2006). Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 36. 35Table 4: Technological trendsS.No. Category Technological Trends1. Data • Multispectral to Hyper-spectral • Low Spatial resolution to High Spatial resolution • Mono imaging to Stereo Imaging • Workstation to PC based2. Hardware • Workstation to PC based • PCs to Mobile / pocket PCs3. Software • Desktop level to web based GIS/Image • analysis to Mobile GIS4. Internet • Low bandwidth – Broad brand based • Web services (Google Earth / Wekemepia etc.)5. Standards • Proprietary based standards to Open • Standards As a whole the technological developments in geoinformatics lead to branch outto many areas. They are: • spatial multimedia • open GIS/ Free GIS • GIS Customization • spatial Modelling • geo-Visualization • data Warehouse and large database handling • knowledge discovery and Data mining • geo-Computation • mobile GIS /Fleet Management / Location Based Services • web GIS /Distributed GIS • spatial Data Infrastructure and Geo-Information Management • sensor Web enablement • metadata and clearing houses Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 37. 36 • interoperability/Open standards and specificationsReferencesBartlett, D. 1993. Geography Department, Cork University, Ireland. Re: GIS as a Science [Discussion]. GeographicInformation Systems Discussion List [Online]Carlson, C. L. 1993. Northern Illinois University. Re: Value of Peer Review [Discussion]. Geographic Information Systems Discussion List [Online]Feldman, M. 1993. Community Planning, University of Rhode Island. Re: GIS as a Science & Value of Peer Review [Discussion]. Geographic Information Systems Discussion List [Online].Groom, A. 1993. Christchurch City Council, New Zealand. Re: Tool or Science? [Discussion]. Geographic Information SystemsDiscussion List [Online].Laffey, S. C. 1993. Department of Geography, Northern Illinois University. Re: GIS as a Science [Discussion]. GeographicInformation Systems Discussion List [Online].Petican, D. J. 1993. University of Waterloo, Canada. Re: GIS as a Science [Discussion]. Geographic Information SystemsDiscussion List [Online].Sandhu, J. 1993. Environmental Systems Research Institute, Redlands. Re: GIS as a Science [Discussion]. Geographic Information Systems Discussion List [Online].Skelly, C. W. 1993. James Cook University, Australia. GIS & Remote Sensing Research [Discussion]. Geographic Information Systems Discussion List [Online] Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 38. 37Dadhwal,V.K and Raju,P.L.N. 2006. Geoinformatics technological trends –expanding to diversified application areas, National Conference on Geo Informatics,V.P.M’s Polytechnic, Thane, Maharastra, December 8-10, 2006.Wright, D. J. 1993a. Department of Geography, UC-Santa Barbara. Re: Value of Peer Review [Discussion]. Geographic InformationSystems Discussion List [Online]Wright, Dawn J., Goodchild, Michael F and Proctor, James D. 1997. “Demystifying the Persistent Ambiguity of GIS as “Tool” Versus “Science””Annals of the Association of American Geographers, 87(2): 346-362, 1997. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 39. 38 Fundamental Concepts of GPS P.L.N. Raju Geoinformatics DivisionIntroduction: Traditional methods of surveying and navigation resort to tedious field andastronomical observation for deriving positional and directional information. Diverse fieldconditions, seasonal variation and many unavoidable circumstances always bias thetraditional field approach. However, due to rapid advancement in electronic systems,every aspect of human life is affected to a great deal. Field of surveying and navigation istremendously benefited through electronic devices. Many of the critical situations insurveying/navigation are now easily and precisely solved in short time. Astronomical observation of celestial bodies was one of the standard methods ofobtaining coordinates of a position. This method is prone to visibility and weather conditionand demands expertise handling. Attempts have been made by USA since early 1960`s touse space based artificial satellites. System TRANSIT was widely used for establishingnetwork of control points over large regions. Establishment of modern geocentric datumand its relation to local datum was successfully achieved through TRANSIT. Rapidimprovements in higher frequently transmission and precise clock signals along withadvanced stable satellite technology have been instrumental for the development of globalpositioning system. The NAVSTAR GPS (Navigation System with Time and Ranging Global PositioningSystem) is a satellite based radio navigation system providing precise three- dimensionalposition, course and time information to suitably equipped user. GPS has been underdevelopment in the USA since 1973. The US Department of Defence as a worldwidenavigation and positioning resource for military as well as civilian use for 24 hours and allweather conditions primarily develops it. In its final configuration, NAVSTAR GPS consists of 21 satellites (plus 3 activespares) at an altitude of 20200 km above the earth’s surface (Fig.1). These satellites are Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 40. 39so arranged in orbits to have at least four satellites visible above the horizon anywhere onthe earth, at any time of the day. GPS Satellites transmit at frequencies L1=1575.42 MHzand L2=1227.6 MHz modulated with two types of code viz. P-code and C/A code and withnavigation message. Mainly two types of observable are of interest to the user. In pseudoranging the distance between the satellite and the GPS receiver plus a small correctiveterm for receiver clock error is observed for positioning whereas in carrier phasetechniques, the difference between the phase of the carrier signal transmitted by thesatellite and the phase of the receiver oscillator at the epoch is observed to derive theprecise information. The GPS satellites act as reference points from which receivers on the groundresect their position. The fundamental navigation principle is based on the measurementof pseudoranges between the user and four satellites (Fig.2). Ground stations preciselymonitor the orbit of every satellite and by measuring the travel time of the signalstransmitted from the satellite four distances between receiver and satellites will yieldaccurate position, direction and speed. Though three-range measurements are sufficientbut fourth observation is essential for solving clock synchronization error between receiverand satellite. Thus, the term "pseudoranges" is derived. The secret of GPS measurementis due to the ability of measuring carrier phases to about 1/100 of a cycle equaling to 2 to3 mm in linear distance. Moreover the high frequencies L1 and L2 carrier signal caneasily penetrate the ionosphere to reduce its effect. Dual frequency observations areimportant for large station separation and for eliminating most of the error parameters. There has been significant progress in the design and miniaturization of stableclock. GPS satellite orbits are stable because of the high altitudes and no atmospheredrag. However, the impact of the sun and moon on GPS orbit though significant can becomputed completely and effect of solar radiation pressure on the orbit and troposphericdelay of the signal have been now modeled to a great extent from past experience toobtain precise information for various applications. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 41. 40 Comparison of main characteristics of TRANSIT AND GPS reveal technologicaladvancement in the field of space based positioning system (Table 1) Details TRANSIT GPS Orbit Altitude 1000 Km 20,200 Km Orbital Period 105 Min 12 Hours Frequencies 150 MHz 1575 MHz 400 MHz 1228 MHz Navigation data 2D : 4D : X,Y,Z, t velocity Availability 15-20 minute per pass Continuously Accuracy ñ 30-40 meters ñ15m (Pcode/No. SA (Depending on velocity 0.1 Knots error) Repeatability ------- ñ1.3 meters relative Satellite Constellation 4-6 21-24 Geometry Variable Repeating Satellite Clock Quartz Rubidium, Cesium GPS has been designed to provide navigational accuracy of ±10m to ±15 m.However, sub meter accuracy in differential mode has been achieved and it has beenproved that broad varieties of problems in geodesy and geodynamics can be tackledthrough GPS. Versatile use of GPS for a civilian need in following fields have been successfullypracticed viz. navigation on land, sea, air, space, high precision kinematics survey on theground, cadastral surveying, geodetic control network densification, high precision aircraftpositioning, photogrammetry without ground control, monitoring deformations,hydrographic surveys, active control survey and many other similar jobs related tonavigation and positioning,. The outcome of a typical GPS survey includes geocentricposition accurate to 10 m and relative positions between receiver locations to centimeterlevel or better. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 42. 41Various Segments: For better understanding of GPS, we normally consider three major segments viz.space segment, Control segment and User segment. Space segment deals with GPSsatellites systems, Control segment describes ground based time and orbit controlprediction and in User segment various types of existing GPS receiver and its applicationis dealt (Fig.3).Table 2 gives a brief account of the function and of various segments along with input andoutput information.Segment Input Function Output Space Navigation message Generate and P-Code Transmit code and C/A Code carrier phases and L1,L2 carrier navigation message Navigation message Control P-Code Observations Produce GPS time Navigation message Time predict ephemeris manage space vehicles User Code observation Carrier Navigation solution Position velocity phase observation Navigation Surveying solution time MessageGLONASS (Global Navigation & Surveying System) a similar system to GPS is beingdeveloped by former Soviet Union and it is considered to be a valuable complementarysystem to GPS for future application.Space Segment: Space segment will consist 21 GPS satellite with an addition of 3 active spares.These satellites are placed in almost six circular orbits with an inclination of 55 degree.Orbital height of these satellites is about 20,200 km corresponding to about 26,600 km Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 43. 42from the semi major axis. Orbital period is exactly 12 hours of sidereal time and thisprovides repeated satellite configuration every day advanced by four minutes with respectto universal time. Final arrangement of 21 satellites constellation known as "Primary satelliteconstellation" is given in Fig.4. There are six orbital planes A to F with a separation of 60degrees at right ascension (crossing at equator). The position of a satellite within aparticular orbit plane can be identified by argument of latitude or mean anomaly M for agive epoch. GPS satellite are broadly divided into three block (Table 3) Block-I satellitepertains to development stage, Block II represent production satellite and block IIR arereplenishment/spare satellite.Table 3 Status of GPS satellite (July 1992) Launch Satellite PRN Code Launch date Orbit Plan Status Sequence Vertical BLOCK I I-1 01 04 02/78 --- Unusable 7/85 I-2 02 07 05/78 --- Unusable 7/81 I-3 03 06 10/78 Marginal Use I-4 04 08 12/78 Unusable 10/89 I-5 05 05 02/80 Unusable 11/83 I-6 06 09 04/80 Unusable 3/91 I-7 07 -- -- Launch Failure I-8 08 11 07/83 C3 Operational I-9 09 13 06/84 C1 Operational Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 44. 43 I-10 10 12 09/84 A1 Operational I-11 11 03 10/85 C4 Operational BLOCK II II-1 14 14 02/89 E1 Operational II-2 13 02 06/89 B3 " II-3 16 16 08/89 E3 " II-4 19 19 10/89 A4 " II-5 17 17 12/89 D3 " II-6 18 18 01/90 F3 " II-7 20 20 03/90 B2 " II-8 21 21 08/90 E2 " II-9 15 15 10/90 D2 " BLOCK-II R II-10 23 23 11/90 E4 Operational II-11 24 24 07/91 D1 " II-12 25 25 02/92 A2 " II-13 28 28 04/92 C2 " II-14 26 26 -7/92 " II-15 " Under Block-I, NAVSTAR 1 to 11 satellites were launched before 1978 to 1985 intwo orbital planes of 63 degree inclination. Design life of these prototype test satelliteswas only five years but as indicated in Table 2 the operational period has been exceededin most of the cases. The first Block-II production satellite was launched in February 1989using channel Douglas Delta 2 booster rocket. A total of 28 Block-II satellites are plannedto support 21+3 satellite configuration. Block-II satellites have a designed lifetime of 5-7years. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 45. 44 To sustain the GPS facility, the development of follow-up satellites under BLock-IIR has already started. Twenty replenishment satellite will replace the current block-IIsatellite as and when necessary. These GPS satellites under Block-IIR will have additionalability to measure distances between satellites and will also compute ephemeris onboard for real time information. Fig.5 gives a schematic view of Block-II satellite Electrical power in generatedthrough two solar penal covering surface area of 7.2 square meter each. However,additional battery backup is provided to provide energy when the satellite moves intoearth`s shadow region. Each satellite weighs 845kg and has a propulsion system forpositional stabilization and orbit maneuvers. GPS satellites have very high performanceof frequency standard with an accuracy of between 1X10-12 to 1X10-13 and are thuscapable of creating precise time base. Block-I satellites were partly equipped with onlyquartz oscillators but Block-II satellites have two cesium frequency standards and tworubidium frequency standards. Using fundamental frequency of 10.23 MHz, two carrierfrequencies are generated to transmit signal codes.Observation principle and signal structure: NAVSTAR GPS is a one-way ranging system i.e. signals are only transmitted bythe satellite . Signal travel time between the satellite and the receiver is observed and therange distance is calculated through the knowledge of signal propagation velocity. Oneway ranging means that a clock reading at the transmitted antenna is compared with aclock reading at the receiver antenna. But since the two clocks are not strictlysynchronized hence the observed signal travel time is biased with systematicsynchronization error. Biased ranges are known as pseudoranges. Simultaneousobservations of four pseudoranges are necessary to determine X, Y, Z coordinates of userantenna and clock bias. Real time positioning through GPS signals is possible by modulating carrierfrequency with Pseudorandom Noise (PRN) codes. These are sequence of binary values Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 46. 45(zeros and ones or +1 and -1) having random character but identifiable distinctly. Thuspseudoranges are derived from travel time of an identified PRN signal code. Two differentcodes viz. P-code and C/A code are in use. P means precision or protected and C/Amean clear/acquisition or coarse acquisition. P- code has a frequency of 10.23 MHz. This refer to a sequence of 10.23 millionbinary digits or chips per second. This frequency is also referred to as the chipping rate ofP-code. Wavelength corresponding to one chip is 29.30m. The P-code sequence isextremely long and repeats only after 266 days. Portions of seven days each areassigned to the various satellites. As a consequence, all satellite can transmit on thesame frequency and can be identified by their unique one week segment. This techniqueis also called as Code Division Multiple Access (CDMA). P-code is the primary code fornavigation and is available on carrier frequencies L1 and L2. The C/A code has a length of only one millisecond, its chipping rate is .023 MHzwith corresponding wave length of 300 meters. C/A code is only transmitted on L1 carrier.GPS receiver normally have a copy of the code sequence. For determining the signalpropagation time. This code sequence is phase-shifted in time step by step andcorrelated with the received code signal until maximum correlation is achieved. Thenecessary phase-shift in the two sequence of codes is a measure of the signal travel timebetween the satellite and the receiver antennas. This technique can be explained as codephase observation. For precise geodetic applications, the pseudoranges should bederived from phase measurements on the carrier signals because of much higherresolution. Problems of ambiguity determination is vital for such observations. The thirdtype of signal transmitted from a GPS satellite is the broadcast message sent at a ratherslow rate of 50 bits per second (50 bps) and repeats every 30 seconds. Chip sequence ofP-code and C/A code are separately combined with the stream of message bit by binaryaddition ie the same value for code and message chip gives 0 and different values resultin 1. The main features of all three signal types used in GPS observation viz carrier, codeand data signals are given in Table 4. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 47. 46Table 4 GPS Satellite Signals Atomic Clock (G, Rb) fundamental 10.23. MHz frequency L1 Carrier Signal 154 X 10.23 MHz L1 Frequency 1575.42 MHz L1 Wave length 19.05 Cm L2 Carrier Signal 120 X 10.23 MHz L2 Frequency 1227.60 MHz L2 Wave Length 24.45 Cm P-Code Frequency (Chipping Rate) 10.23 MHz (Mbps) P-Code Wavelength 29.31 M P-Code Period 267 days : 7 Days/Satellite C/A-Code Frequency (Chipping Rate) 1.023 MHz (Mbps) C/A-Code Wavelength 293.1 M C/A-Code Cycle Length 1 Milisecond Data Signal Frequency 50 bps Data Signal Cycle Length 30 Seconds The signal structure permits both the phase and the phase shift (Doppler effect) tobe measured along with the direct signal propagation. The necessary band width isachieved by phase modulation of the PRN code as illustrated in Fig 6.Structure of the GPS Navigation Data: Structure of GPS navigation data (message) as shown in fig. 7. The user has todecode the data signal to get access to the navigation data. For on line navigationpurposes, the internal processor within the receiver does the decoding. Most of themanufacturers of GPS receiver provide decoding software for post processing purposes. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 48. 47 With a bit rate of 50 bps and a cycle time of 30 seconds, the total informationcontent of a navigation data set is 1500 bits. The complete data frame is subdivided intofive subframes of six second duration comprising 300 bits information. Each subframecontains the data words of 30 bits each. Six of these are control bits. The first two wordsof each subframe are the Telemetry Work (TLM) and the C/A-P-Code Hand Over Work(HOW). The TLM work contains a synchronization pattern which facilitates the access tothe navigation data. The navigation data record is divided into three data blocks:Data Block I appears in the first subframe and contains the clock coefficient/bias.Data Block II appears in the second and third subframe and contains all necessary parameters for the computation of the satellite coordinates.Data Block III appears in the fourth and fifth subframes and contains the almanacdata with clock and ephemeris parameter for all available satellite of the GPS system. This data block includes also ionospheric corrections parameters and particular alphanumeric information for authorized users.Unlike the first two blocks, the subframe four and five are not repeated every 30 seconds.International Limitation of the system accuracy: Since GPS is a military navigation system of US, a limited access to the totalsystem accuracy is made available to the civilian users. The service available to thecivilians is called Standard Positioning System (SPS) while the service available to theauthorized user is called the Precise Positioning Service (PPS) under current policy theaccuracy available to SPS users is 100m, 2D-RMS and for PPS users it is 10 to 20 meters Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 49. 48in 3D. Additional limitation viz. Anti-Spoofing (AS), and Selective Availability (SA) isfurther imposed for civilian users. Under AS, only authorized users will have the means toget access to the P-code. By imposing SA condition, positional accuracy from Block-IIsatellite is randomly offset for SPS users. The GPS system time is defined by the cesium oscillator at a selected monitorstation. However, no clock parameter are derived for this station. GPS time is indicatedby a week number and the number of seconds since the beginning of the current week.GPS time thus varies between 0 at the beginning of a week to 6,04,800 at the end of theweek. The initial GPS epoch is January 5, 1980 at 0 hours Universal Time. Hence, GPSweek starts at Midnight (UT) between Saturday and Sunday. The GPS time is acontinuous time scale and is defined by the main clock at the Master Control Station(MCS). The leap seconds is UTC time scale and the drift in the MCS clock indicate thatGPS time and UTC are not identical. The difference is continuously monitored by thecontrol segment and is broadcast to the users in the navigation message. Difference ofabout 7 seconds was observed in July, 1992. GPS satellite are identified by two different numbering schemes. Based on launchsequence, SVN (Space Vehicle Number) or NAVSTAR number is allocated. PRN(Pseudo Random Noise) or SVID (Space Vehicle Identification) number is related to orbitarrangement and the particular PRN segment allocated to the individual satellite. UsuallyPRN number is displayed by the GPS receiver.Control Segment: Control segment is the vital link in GPS technology. Main function of the controlsegment are- Monitoring and Controlling the satellite system continuously- Determine GPS system time- Predict the satellite ephemeries and the behavior of each satellite clocks.Update periodically the navigation message for each particular satellite. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 50. 49 For continuos monitoring and controlling GPS satellites a master control stations(MCS), several monitor stations (MS) and ground antennas (GA) are located around theworld (Fig.9). The operational control segment (OCS) consists of MCS near Coloradosprings (USA), three MS and GA in kwajaleian Ascension and Diego Garcia and two moreMS at Colorado Spring and Hawai. The monitor station receive all visible satellite signals and determine theirpseudorages and then transmit the range data along with the local meteorological data viadata link to the master control stations. MCS then precomputes satellite ephemeris andthe behaviour of the satellite clocks and formulates the navigation data. The navigationmessage data is transmitted to the ground antennas and via S-band it links to thesatellites in view Fig. 8 shows this process schematically. Due to systematic globaldistribution of upload antennas, it is possible to have atleast three contacts per daybetween the control segment and each satellite.User Segment: Appropriate GPS receivers are required to receive signal from GPS satellites forthe purpose of navigation or positioning. Since, GPS is still in its development phase,many rapid advancement have completely eliminated bulky first generation userequipment’s and now miniature powerful model are frequently appearing in the market.Basic Concept of GPS receiver and its components: The main components of a GPS receiver are shown in Fig.10. These are - antenna with pre-amplifier - RF section with signal identification and signal processing - Micro-processor for receiver control, data sampling and data processing - precision oscillator Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 51. 50 - power supply - user interface, command and display panel - memory, data storageAntenna: Sensitive antenna of the GPS receiver detects the electromagnetic wave signaltransmitted by GPS satellites and converts the wave energy to electric current amplifiesthe signal strength and sends them to receiver electronics. Several types of GPS antennas in use are mostly of following types (Fig. 11). - mono pole or dipole - Quadrifilar helix (Volute) - Spiral helix - Microstrip (patch) - Choke ring Microstrip antennas are most frequently used because of its added advantage forairborne application, materialization of GPS receiver and easy construction. However, forgeodetic needs, antennas are designed to receive both carrier frequencies L1 and L2.Also they are protected against multipath by extra ground planes or by using choke rings.A choke ring consists of strips of conductor which are concentric with the vertical axis ofthe antenna and connected to the ground plate which in turns reduces multipath effect.RF section with signal identification and processing: The incoming GPS signals are down converted to a lower frequency in the RSsection and processed within one or more channels. Receiver channel is the primaryelectronic unit of a GPS receiver. A receiver may have one or more channels. In theparallel channel concept each channel is continuously franking one particular satellite. Aminimum of four parallel channel is required to determine position and time. Modernreceivers contains upto 12 channel for each frequency. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 52. 51In the sequencing channel concept the channel switches from satellite to satellite atregular interval. A single channel receiver this takes atleast four times of 30 seconds toestablish first position fix. Though some receiver type have a dedicated channel forreading the data signal. Now-a-days in most of the cases fast sequencing channels witha switching rate of about one second per satellite are used. In multiplexing channel, sequencing at a very high speed between different satelliteis achieved using one or both frequencies. The switching rate is synchronous with thenavigation message of 50 bps or 20 milliseconds per bit. A complete sequence with foursatellite is completed by 20 millisecond or after 40 millisecond for dual frequencyreceivers. The navigation message is continuous; hence first fix is achieved after about30 seconds. Though continuous tracking parallel channels are cheap and give goodoverall performance but GPS receiver based on multiplexing technology will soon beavailable at a cheaper price due to electronic boom.Microprocessor: To control the operation of a GPS receiver, a microprocessor is essential foracquiring the signals, processing of the signal and the decoding of the broadcastmessage, Additional capabilities of computation of on-line position and velocity,conversion into a given local datum or the determination of waypoint information are alsorequired. In future more and more user relevant software will be resident on miniaturizedmemory chips.Precision Oscillator: A reference frequency in the receiver is generated by the precision oscillator.Normally, less expensive, low performance quartz oscillator is used in receivers since theprecise clock information is obtained from the GPS satellites and the user clock error canbe eliminated through double differencing technique when all participating receiversobserve at exactly the same epoch. For navigation with two or three satellites only anexternal high precision oscillator is used. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 53. 52Power Supply: First generation GPS receivers consumed very high power, but modern receiverare designed to consume as little energy as possible. Most receivers have an internalrechargeable Nickel-Cadmium battery in addition to an external power input. Caution oflow battery signal prompts the user to ensure adequate arrangement of power supply.Memory Capacity: For port processing purposes all data have to be stored on internal or externalmemory devices. Post processing is essential for multi station techniques applicable togeodatic and surveying problems. GPS observation for pseudoranges, phase data, timeand navigation message data have to be recorded. Based on sampling rate, it amount toabout 1.5 Mbytes of data per hour for six satellites and 1 second data for dual frequencyreceivers. Modern receivers have internal memories of 5 Mbytes or more. Some receiverstore the data on magnetic tape or on a floppy disk or hard-disk using externalmicrocomputer connected through RS-232 port. Most modern receiver has a keypad and a display for communication between theuser and the receivers. The keypad is used to enter commands, external data likestations number or antenna height or to select a menu operation. The display indicatescomputed coordinates, visible satellites, data quality indices and other suitableinformation. Current operation software packages are menu driven and very user friendly.Classification of GPS receiver: GPS receiver can be divided into various groups according to different criteria. Inthe early stages two basic technologies were the classification criteria viz. Codecorrelation receiver technology and sequencing receiver technology, which wereequivalent to code dependent receivers and code free receivers. However, this kind ofdivision is no longer justifiable since both techniques are implemented in presentreceivers. Another classification of GPS receivers is based on acquisition of data types eg.; Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 54. 53- C/A code receiver - C/A Code + L1 Carrier phase- C/A Code + L1 Carrier phase + L2 Carrier phase- C/A code + p_code + L1, L2 Carrier phase- L1 Carrier phase (not very common)- L1, L2 Carrier phase (rarely used)Based on technical realization of channel, the GPS receivers can be classified as;- Multi-channel receiver- Sequential receiverMultiplexing receiverGPS receiver are even classified on the purpose as- Military receiver- Civilian receiver- Navigation receiver- Timing receiver- Geodetic receiver For geodetic application it is essential to use the carrier phase data as observable.Use of L1 and L2 frequency is also essential along with P-code.Examples of GPS receiver: GPS receiver market is developing and expanding at a very high speed. Receiversare becoming powerful, cheap and smaller in size. It is not possible to give details ofevery make but description of some typical receiver given may be regarded as a basis forthe evaluation of future search and study of GPS receivers. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 55. 54Classical Receivers: Detailed description of code dependent T1 4100 GPS Navigator and code freeMacrometer V1000 is given here;T1 4100 GPS Navigator was manufactured by Texas Instrument in 1984. It was the firstGPS receiver to provide C/A and P code and L1 and L2 carrier phase observations. It is adual frequency multiplexing receiver and suitable for geodesist, surveyor and navigators.The observable through it are;- P-Code pseudo ranges on L1 an L2- C/A-Code pseudoranges on L1- Carrier phase on L1 and L2 The data is recorded by an external tape recorder on digital cassettes or aredownloaded directly to an external microprocessor. A hand held control display unit(CDU) is used for communication between observer and the receiver. For navigationalpurposes the built in microprocessor provides position and velocity in real time every threeseconds. T1 4100 is a bulky instruments weighing about 33 kg and can be packed in twotransportation cases. It consumes of 90 watts energy in operating mode of 22V - 32V.Generator use is recommended. The observation noise in P-Code is between 0.6 to 1m,in C/A code it ranges between 6 to 10m and for carrier phase it is between 2 to 3 m. T1 4100 has been widely used in numerous scientific and applied GPS projectsand is still in use. The main disadvantages of the T1 4100 compared to more modernGPS equipment’s are- Bulky size of the equipment- High power consumption- Difficult operation procedure- Limitation of tracking four satellites simultaneously- High noise level in phase measurementsSensitivity of its antenna for multipath and phase centre variation if two receivers areconnected to one antenna then tracking of seven satellites simultaneously is possible. Forlong distances and in scientific projects, T1 4100 is still regarded useful. However, due to Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 56. 55imposition of restriction on P-code for civilian, T1 4100 during Anti Spoofing (AS)activation can only be used as a single frequency C/A code receiver. The MACROMETER V 1000, a code free GPS receiver was introduced in 1982 andwas the first receiver for geodetic applications. Precise result obtained through it hasdemonstrated the potential of highly accurate GPS phase observations. It is a singlefrequency receiver and tracks 6 satellites on 6 parallel channels. The complete systemconsists of three units viz.- Receiver and recorder with power supply- Antenna with large ground plane- P 1000 processorThe processor is essential for providing the almanac data because the Macrometer V1000 cannot decode the satellites messages and to process the data. At pre determinedepoches the phase differences between the received carrier signal and a reference signalfrom receiver oscillator is measured. A typical baseline accuracy reported for upto 100 kmdistance is about 1 to 2 ppm (Parts per million). Macrometer II, a dual frequency version was introduced in 1985. Though it iscomparable to Macrometer V 1000 but its power consumption and weight are much less.Both system require external ephemeredes. Hence specialized operator of fewcompanies are capable of using it and it is required to synchronize the clock of all theinstruments proposed to be used for a particular observation session. To overcome abovedisadvantages, the dual frequency Macrometer II was further miniaturized and combinedwith a single frequency C/A code receiver with a brand name MINIMAC in 1986, thusbecoming a code dependent receiver.Examples of present geodetic GPS receivers; Few of the currently available GPS receivers that are used in geodesy surveyingand precise navigation are described. Nearly all models started as single frequency C/A- Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 57. 56Code receivers with four channels. Later L2 carrier phase was added and trackingcapability was increased. Now-a-days all leading manufacturers have gone for code-less,non sequencing L2 technique. WILD/LEITZ (Heerbrugg, Switzerland) and MAGNAVOX(Torrance, California) have jointly developed WM 101 geodetic receiver in 1986. It is afour channel L1 C/A code receiver. Three of the channel sequentially track upto sixsatellites and the fourth channel, a house keeping channel, collects the satellite messageand periodically calibrates the inter channel biases. C/A-code and reconstructed L1 carrierphase data re observed once per second. The dual frequency WM 102 was marketed in 1988 with following key features :-L1 reception with seven C/A code channel tracking upto six satellites simultaneously.L2 reception of upto six satellites with one sequencing P- code channel- Modified sequencing technique for receiving L2 when P-code signals areencrypted. The observations can be recorded on built in data cassettes or can be transferredon line to an external data logger in RS 232 or RS 422 interface. Communication betweenoperator and receiver is established by alpha numerical control panel and display WM101/102 has a large variety of receiver resident menu driven options and it isaccompanied by comprehensive post processing software. In 1991, WILD GPS system 200 was introduced. Its hardware comprises theMagnavox SR 299 dual frequency GPS sensor, the hand held CR 233 GPS controller anda Nicd battery. Plug in memory cards provide the recording medium. It can track 9satellites simultaneously on L1 and L2. Reconstruction of carrier phase on L1 is throughC/A code and on L2 through P-code. The receiver automatically switches to codeless L2when P-code is encrypted. It consumes 8.5 watt through 12 volt power supply. TRIMBLE NAVIGATION (Sunny vale, California) has been producing TRIMBLE4000 series since 1985. The first generation receiver was a L1 C/A code receiver with fiveparallel channels providing tracking of 5 satellites simultaneously. Further upgradationincluded increasing the number of channels upto tweleve, L2 sequencing capability and P- Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 58. 57code capability. TRIMBLE Geodatic Surveyor 4000 SSE is the most advanced model.When P-Code is available, it can perform following types of observations, viz.,- Full cycle L1 and L2 phase measurements- L1 and L2, P-Code measurements when AS is on and P-code is encrypted- Full cycle L1 and L2 phase measurement- Low noise L1, C/A code- Cross-correlated Y-Code dataObservation noise of the carrier phase measurement when P-code is available is about ñ0-2mm and of the P-code pseudoranges as low as ñ 2cm. Therefore, it is very suitable forfast ambiguity solution techniques with code/carrier combinations. ASHTECH (Sunnyvale, California) developed GPS receiver with 12 parallelchannels and pioneered current multi-channel technology. ASHTECH XII GPS receiverwas introduced in 1988. It is capable of measuring pseudoranges, carrier phase andintegrated dopler of up to 12 satellites on L1. The pseudoranges measurements aresmoothed with integrated Doppler. Postion velociy, time and navigation information aredisplayed on a keyboard with a 40-characters display. L2 option adds 12 physical L2squaring type channels. ASHTECH XII GPS receiver is a most advanced system, easy to handle and doenot require initialization procedures. Measurement of all satellites in view are carried outautomatically. Data can be stored in the internal solid plate memory of 5 Mbytescapacity. The minimum sampling interval is 0.5 seconds. Like many other receivers it hasfollowing additional options viz.- 1 ppm timing signal output- Photogrammetric camera input- Way point navigation Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 59. 58- Real time differential navigation and provide port processing and vision planningsoftware In 1991, ASHTECH P-12 GPS receiver was marketed. It has 12 dedicated channelof L1, P-code and carrier and 12 dedicated channel of L2, P-code and carrier. It also has12 L1, C/A code and carrier channels and 12 codes less squaring L2 channels. Thus thereceiver contains 48 channels and provides all possibilities of observations to all visiblesatellites. The signal to noise level for phase measurement on L2 is only slightly less thenon L1 and significantly better than with code-less techniques. In cases of activated P-code encryption, the code less L2 option can be used. TURBO ROGUE SNR-8000 is a portable receiver weighs around 4 kg, consumes15 watt energy and is suitable for field use. It has 8 parallel channels on L1 and L2. Itprovides code and phase data on both frequencies and has codeless option. Full P-codetracking provides highest precision phase and pseudo rages measurements; codelsstracking is automatic "full back" mode. The code less mode uses the fact that each carrierhas identical modulation of P-code/Y-code and hence the L1 signal can be cross-correlated with the L2 signal. Results are the differential phase measurement (L1-L2) andthe group delay measurement (P1-P2)Accuracy specifications are:P-Code pseudo range 1cm (5 minutes integration)Codeless pseudo range 10cm (5 minutes integration)Carrier phase 0.2 - 0.3 mmCodeless phase 0.2 - 0.7 mm One of the important feature is that less than 1 cycle slip is expected for 100satellite hours. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 60. 59Navigation Receivers Navigation receivers are rapidly picking up the market. In most cases a single C/Acode sequencing or multiplexing channel is used. However, modules with four or fiveparallel channels are becoming increasingly popular. Position and velocity is derived fromC/A code pseudoranges measurement and are displayed or downloaded to a personalcomputer. Usually neither raw data nor carrier phase information is available. Differentialnavigation is possible with some advanced models. MAGELLAN NAV 1000 is a handheld GPS receiver and weighs only 850 grams. Itwas introduced in 1989 and later in 1990, NAV 1000 PRO model was launched. It is asingle channel receiver and tracks 3 to 4 satellites with a 2.5 seconds update rate and hasa RS 232 data port. The follow up model in 1991 was NAV 5000 PRO. It is a 5 channel receivertracking all visible satellites with a 1 second update rate. Differential navigation is possible.Carrier phase data can be used with an optional carrier phase module. The quadrifilarantenna is integrated to the receiver. Post processing of data is also possible usingsurveying receiver like ASHTECH XII located at a reference station. Relative accuracy isabout 3 to 5 metres. This is in many cases sufficient for thematic purposes. Many hand held navigation receiver are available with added features. The latestmarket situation can be obtained through journals like GPS world etc. For most navigation purpose a single frequency C/A code receiver is sufficient. Foraccuracy requirements better than 50 to 100 meters, a differential option is essential. Forrequirement below 5 meters, the inclusion of carrier phase data is necessary. In highprecision navigation the use of a pair of receiver with full geodetic capability is advisable. The main characteristics of multipurpose geodetic receiver are summarized inTable 5. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 61. 60Table 5: Overview of geodetic dual-frequency GPS satellite receiver (1992)Receiver Channel Code Wavelength Anti-spoofing L1 L2 L1 L2 L1 L2TI 4100 4 4 P P Single frequencyMACROMETER 6 6 - - /2 No influenceASHTECH XII 12 12 C/A - /2 No influenceASHTECH P 12 12 12 C/A, P P SquaringTRIMBLE SST 8-12 8-12 C/A - /2 No influenceTRIMBLE 4000 9-12 9-12 C/A, P P Codeless SSEWM 102 7 par 1 seq C/A P SquaringWILD GPS 200 9 9 C/A P CodelessTURBO ROGUE 8 8 C/A, P P CodelessSome of the important features for selecting a geodetic receiver are;Tracking of all satellitesBoth frequenciesFull wavelength on L2Low phase noise-low code noiseHigh sampling rate for L1 and L2High memory capacityLow power consumptionFull operational capability under anti spoofing condition Further, it is recommended to use dual frequency receiver to minimiseionospherical influences and take advantages in ambiguity solution.References :-- Technical Information on GPS systems, Institute of Navigation (ION), USA- Proceedings of ION, GPS, USA- Journal of Geoinformatics Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 62. 61- The Global Positioning System, Chapter 7 of Satellite Geodesy by Gunter Seeber,University of Hanover, Germany- Text work of GPS by Alfred Lietz- GPS World Periodicals Figure 1: The Global Positioning System (GPS), 21 satellite configuration Figure 2 Basic principle of positioning with GPS Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 63. 62Figure 3 The Space, Control and User segment of GPSFigure 4 Arrangement of satellites in full constellation Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 64. 63Figure 5: Schematic view of a Block II GPS satellite Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 65. 64 Figure 6 Generation of GPS Signals Figure 7 Structure of Navigation dataRemote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 66. 65Figure 8 Data Flow in the determination of the broadcast ephemeris Figure 9 Control Segment with observation stations Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 67. 66Figure 10 Major components of a GPS receiver Figure 11 Types of GPS Antennas VARIOUS MAKESOF GPS LEICA GPS SYSTEM - 500 SERIES WITH RADIO BECON Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 68. 67 TRIMBLE CONTROLLER MEGELLAN GPS 315 SERIES VARIOUS MAKESOF GPSTRIMBLE GPS AS A ROVER Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 69. 68 GARMIN 12 CHANNAL GPSMAGELLAN GPS - 315 SERIES Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 70. 69 Geoinformatics for Natural Resource Management P.S. Roy Associate Director, NRSC Dean, IIRS Natural resource management is dependent on the availability and qualityof the geo- information on every sphere of human activities and its interactionwith the environment. The recent developments in information technology andearth observation have facilitated unprecedented growth and need of spatialinformation in decision making in environment management on plethora of issuesrelated to earth surface processes and features, man-environment interaction,controversial environmental issues including natural disasters. The informationand its dissemination tools have created awareness among people. One canperceive quest for information in every sphere of activities of the society.Informed society is being considered precursor to the development. The civilsociety and its interface with administration need to be based on ‘transparent’information in improving quality of life. Three decades of earth observation fromsatellite have provided tremendous impetus to the transparency on the spatialinformation on natural resources, their exploitation and degradation. Our environment is changing rapidly due to increasing population,resource consumption, development & globalization and technological changes,which are threatening to our climate, biodiversity, human health, stability andsecurity. To overcome these problems we are evolving towards more humancontrolled environment. To meet the challenges we need to have a digitalabstraction of the earth to represent, understand, manage and communicate ourworld as a system. Geoinformatics is an emerging science and technology whichprovides a framework for measurement, monitoring, modeling, planning, decision Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 71. 70making and management of our environment and natural resources. The recentdevelopment in computer and related technologies opens new window for naturalresource management using geo-information tools including GeographicalInformation System. The present article provides an overview of applicationsand technological aspects of Geoinformatics for environment management. Geographic Information System (GIS) is a powerful tool in which spatialinformation can be stored, organized, and retrieved in a user friendlyenvironment. Conjunction of satellite remote sensing data and ancillary data inGIS environment combined with the Global positioning system (GPS) data is apotential tool to environment management. Combining the GIS and Informationtechnology (IT), a new word has coined namely Geoinformatics. The three majorobjectives of Geoinformatics includes: Organization/development andmanagement of geospatial data; spatial modeling and data analysis;development and integration of computer tools for visualization and analysis ofreal time geospatial problems in decision making process. The awareness and utilization of these technologies and the power ofspatial information systems specifically oriented towards decision making orresource management is growing rapidly in our country. In this direction numberof Remote Sensing and GIS base real time problem solving environment andinformation system has been developed and demonstrated by RS & GIScommunity in desktop and as well in client server environment. Environmentaland resource management problems are both spatially distributed anddetermined by complex processes and relationships, involving numerousinteracting elements with multiple attributes, and a dynamic behavior that goeswell beyond the analytical capabilities of most commercial GIS software(Kurt,2006). The technological solutions required to analyze the system includesspatially distributed simulation and optimization models, interactive informationsystem, decision support tools and expert systems based on geo-spatial Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 72. 71technologies. The primary paradigm of a GIS is the map, an inherently staticconcept of limited attributes. While modern GIS extend the scope of what can bedone within this paradigm towards digital cartography considerably, andelaborate applications can be built within existing GIS systems and powerful andflexible tool kits there is also a broad class of problem situations that do involvespatial elements, but where the GIS components are only auxiliary to anotherproblem solving approach (Fedra 1994).Many Geoinformatics systems are open to link external components that readand generate geo-referenced data, using the GIS, its data structures, userinterface and display capabilities as the overall framework. Native analyticalfunctions, however, are usually limited to Boolean overlay analysis, buffers (ormore general, neighborhood analysis), network and routing tasks, and spatiallydistributed processes that can be expressed in terms of cellular automata, oftenapplied in the context of urban development or forest fire studies (Clarke andGaydos, 1998).1. Geoinformatics and Environment Management The geo-spatial technology is growing rapidly and has taken quantum jumpfrom non-digital (hard copy) system to digital environment and simple desktop toclient/server system. When viewing satellite imagery, categorizing land use data,or comparing the changes of land cover before/after the disasters, we are gettingvery important messages from Nature. These messages are important forplanners, decision makers, researchers and also for general public. Geo-spatialdata access and dissemination methods play a vital role for getting quick andaccurate information about geography for natural resource management.Ever-growing understanding and acceptance that the Earth functions as acomplex system composed of myriad interrelated mechanisms have madescientists realize that existing information systems and techniques used areinadequate. Currently, the uncoordinated distribution of available data sets, alack of documentation about them, and the lack of easy-to-use access tools andcomputer codes are major obstacles for scientists and educators alike. These Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 73. 72obstacles have hindered scientists and educators in the access and full use ofavailable data and information, and hence have limited scientific productivity andthe quality of education. Recent technological advances, however, providepractical means to overcome such problems. Advances in computer design,software, disk storage systems as well as the growth of the World Wide Web(www) now permit for the first time the management of gigabytes to terabytes ofdata for distribution to scientists, educators, students, and the general public.Geoinformatics (geographic information science, Geomatics) aims at thedevelopment and application of methods for solving specific problems - withspecial emphasis on the geographical position of objects.The environmental control on the forest vegetation is well documented (Mueller-Dombois, Dieter and Ellenberg 1974). Physiography, topography, climate andhuman interventions largely control the distribution of vegetation and biodiversity.The developments in computer based Geographic Information System (GIS)enables the integration of spatial and non-spatial information for defining thehabitats and improving vegetation type descriptions in space and time. It is alsopossible to evolve geospatial models using multi criterion to present disturbanceregimes and landscape diversity. Landscape ecology has evolved as anoperational tool with the availability of geospatial modeling techniques. Thepower of having all information and knowledge along with access, modeling, andvisualization tools at the finger tips of a user has great potential in advancingscience, accelerating the discovery process, and enhancing the quality ofscience and education. A range of strategies exist for coupling complex analyticaltools and dynamic models with geo-spatial technology, and these cover a rangefrom low to high integration: isolated with data exchange, loose coupling, tightcoupling, and full integration (Fedra 1993, Raper and Livingstone 1993). Theintegration approach is considered as inaccessible if the analytical tools are runindependently of a GIS, which is used in parallel, and integrated if it is run usingthe GIS through shared data in distributed environment. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 74. 732. Geoinformatics: Application Domains and Examples3.1 Crops The works carried out so far, in India, has demonstrated the utility of singledate satellite data in the estimation of pre-harvest acreages of major crops,particularly in the single crop-dominated regions, with 90/90 accuracy /confidence criterion. Under the Crop Acreage and Production Estimation (CAPE)project, the preharvest acreage estimates of major crops viz, paddy, wheat,sorghum, ground nut, rapeseed, mustard, cotton and mesta / jute occupyingabout 80% of the cropped area, are being regularly carried out. The highs patialresolution (23.5m) IRS-1C/1D LISS-III data enabled identification of commerciallyimportant crops, viz. chillies, tobacco etc., which are grown under multiple cropsituations. Many horticultural crops viz. mango, coconut, arecanut, oranges andbanana could be identified and their acreages estimated using high spatialresolution LISS-II and LISS-III data. Efforts need to be made to provide theproduction estimates for various horticultural crops. In addition, detection,acreage and production estimation of horticultural crops occurring in differentstorey in as three-storey vegetation system need to be attempted using multi-spectral data from currently as well as planned earth observation satellites.Another important element in crop studies, wherein remote sensing hascontributed significantly, is the yield modeling. Statistical, meteorological and / orspectral models are used for crop yield estimation. Within spectral models, twoapproaches viz., single date data spectral index and multi-date data spectralindex-growth profile are in vogue. The single date data spectral index approachrelies solely upon the data acquisition within a narrow critical period of maximumvegetation growth phase while multi-date approach warrants spectral data atdifferent stages of crop growth within the season. However, availability of cloud-free optical sensor data is a major problem especially during the Kharif Season.With the constellation of multiple satellites viz., IRS-1C/12D and the envisaged Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 75. 74future satellites, the interval in the revisiting period of satellites is expected tofurther narrow down, enhancing thereby the probability of obtaining cloud-freedata. In addition, attempts are also underway to incorporate the spectralinformation in the process-based on models and crop simulation models toimprove the predictive capabilities of the remote sensing-based crop productionestimations.3.2 Agricultural Drought Assessment Monitoring the crop conditions at regular intervals during the crop growthcycle is essential to take appropriate curative measures and to assess theprobable loss in production. The remote sensing data can provide information onthe occurrence and the aerial extent of crop stress. However, the identification ofthe cause-whether by pests and diseases or by moisture stress or any otherfactor still remains a major limitation. When stress is caused by more than onefactor, the situation becomes even more complex. Using remote sensing and GIStechniques in conjunction with supplementary information from weatherobservations or knowledge on localized deficiency / toxicity of nutrients orpollutant elements, by deductive process one can still arrive at the cause of thestress. Realizing the potential of satellite-derived vegetation index (VI) which issensitive to vegetation stress and serves as surrogate measure to assessagricultural drought, a nation-wide project titled “National Agricultural DroughtAssessment and Monitoring System (NADAMS)’ was launched in 1987 tomonitor the drought during Kharif (South-West monsoon) season which isagriculturally more important and is also rain dependent, by generatingNormalized Difference Vegetation Index (NDVI) from temporal NOAA-AVHRRdata. For implementation of preventive and / corrective measures for combatingdrought at Mandal / Block (an administrative unit)_level, ecomprehensive droughtassessment involving integration of information on cropping pattern, social types, Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 76. 75coherent rainfall, zone, with improved spatial accuracy is required. AdvancedWiFS with less than 100m resolutions which is likely to be available from IRS-P6mission, may enable generating such information.3.3 Soils Landsat-MASS/TM, IRS-1A/1B LISS-I and II data have been used togenerate soil resources maps at scales ranging from 1:250,000 with theabstraction level of sub-groups/association thereof and association of families,respectively. In addition, the IRS-1C PAN stereo data have been used forgenerating information on soil resources at (1:5,000) maps with abstraction levelof the phases of soil series and / individual series, could be generated from theproposedCartosat-1 (IRS P-5) PAN Stereo data with 2.5m spatial resolution.Further more, derivative information, namely land capability, land irritability,erodibility, reclamability, and suitability, for different crops which in turn enablepreparing the optimal land use plan and in taking up land reclamation measures,wherever required, have also been generated. Models for soil moistureestimation using single frequency, polarization and look angle SAR data, havealso been developed. An operational model for estimation of surface as well asroot zone soil moisture using multi-frequency, multi-look angle and multi-polarization, microwave data available from future missions needs to bedeveloped. A prototype expert system for soil classification using remote sensingdata has also been developed.3.4 Degraded Lands Based on the state-of-art of space borne multi-spectral data, theinformation on the extent, spatial distribution and magnitude of eroded lands,salt-affected soils, waterlogged areas, shifting cultivation, to name a few, at1:250,000 scale and at 1:12,500 scale has been generated. This information hasbeen used for planning land reclamation and soil conservation programmes. Inaddition, the monitoring of above-mentioned lands could also be carried out atregular interval. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 77. 76For on –farm development, the assessment of waterlogging and soil salinityand/alkalinity is required at scales larger than 1:5,000 which could be generatedthrough conjunctive use of a PAN and LISS-IV data available from the proposedCartosat-1 and IRS P-6 missions. Efforts are needed to detect soil salinity and/alkalinity, and water logging in the black soil region using hyper-spectralmeasurements. Waterlogging due to rising ground water table is currently notamenable to detection by remote sensing. Measurements made from thermalsensors and ground-penetrating radar (GPR) may provide the desiredinformation.Hitherto, only qualitative assessment of soil erosion by water has been madewith the existing satellite data which is relatively subjective. Soil loss from awatershed need to be quantified using empirical models, namely, RevisedUniversal Soil Loss Equation (RUSLE) or Water Erosion Prediction Project(WEPP). The values for management factor © and conservation practice factor(P) could be derived from fine resolution PAN stereo and multi-spectral data fromIRS-1C / 1D and the state-of-the-art RESOURCESAT satellites. Furtherimprovement in the level of such information is feasible from better spatialresolution data which is likely to be available from IRS-P5 (Cartosat – 1), thefuture Indian mission.3.5 Forests and Ecosystems Satellite Remote Sensing and Geoinformatics has enabled generation offorest cover maps and to monitor changes therein at operational level. In India,the management of forest resources presently involves a three-tier monitoringsystem. At the national level, biennially forest cover mappings is carried out usingsatellite data by the Forest Survey of India (FSI) on 1:250,000 scale, and therelevant inputs required for forest management at the state level are generated at1:50,000 scale or even at 1:15,000 scale. The advent of high resolution IRS-1C/1D L-III and PAN data has enhanced the capability to prepare forest type andlarge-scale stock maps. The complementary role of PAN data to that of aerial Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 78. 77photography has substantially reduced the cost factor. The grassland mapping isyet another area where remote sensing has played a key role.Remote Sensing holds very promise for providing reliable and timely informationon potential, extent and composition of various eco-systems. In addition, therates of afforestation / deforestation could also be assesses using multi-temporalsatellite data. Currently, the forest fire damage assessment and the detection ofactive fire scars are amenable to remote sensing techniques. The assessment offorest damage due to minimizing activities also could be made using temporalmulti-spectral data.Efforts need to be concerted on monitoring the atmospheric carbon dioxideresulting from afforestation/deforestation as well as forest fires using data fromthe proposed IRS-2 (ATMOS-1) and EOS-CHEM. The forest fire risk modelscould be developed by integrating the information on topography, climate and insitu observation with the satellite-derived vegetation maps in a GIS domain.Besides, the environmental management plan (EMP) could be developed byintegrating the information on land, water and atmosphere in a GIS environment.The assessment models; monitoring urbanization and heat island formation, andstudy of biogeochemical cycles may be attempted using measurements/observations made by future missions.3.6 Land Use / Land Cover Space borne multi-spectral data have been used to generate land use/land cover maps, urban land use and sprawl maps and wasteland maps atoperational level. Nationwide land use/ land cover mapping on 1:250,000 scaleusing IRS 1A /1B LISS I data has been carried out. The IRS-1C/1D WiFS dataoffer a unique opportunity to generate the land use/ land cover maps at regionallevel. Merging high spatial resolution IRS-1C / 1D PAN data with multi-spectralLISS III data provides adequate details for town planning. Wasteland maps on1:50,000 have provided a sound database for agro-climatic regional planning forincreasing food production, whereas information on wastelands helped Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 79. 78reclamation of degraded lands respectively. In addition, nation, -wide wetlandmapping has been carried out using IRS LISS –II data for comprehensiveplanning of wetland ecology and inland fisheries.The future high resolution satellites have a potential for (i) Development ofSpatial Decision Support System (SDSS) for land use classification (ii)Wasteland monitoring at larger scale, and (iii) Development of Land InformationSystem (LIS) and Urban Information System (UIS); and urban / rural resourcesconflict models, among many other uses.3.7 Water Resources The Current satellite remote sensing capabilities for irrigation watermanagement include end-of-season evaluation of canal command areas at thedisaggregated level and diagnostic analysis of problem distributaries to enablefollow –up corrective management. For through-the-season management, IRS-1C /1D WiFS data with a receptivity of 5 days in conjunction with multi frequency,multi-look angel and multi-polarization SAR microwave data could be used. Thedetection of physical degradation such as canal seepage and excessivesedimentation or weed growth in canals, through high resolutions panchromaticdata from IRS-1C/1D/P5 supported by LIS-III / LISS –IV multi-spectral data fromIRS P-6, may be attempted.The information on near-real time flood inundation, and damage assessment formonitoring flood events, post-flood river configuration to assess vulnerability offlood control structures, preliminary flood hazard risk zone mapping and floodforecasting could be generated using currently available satellite data. However,comprehensive flood monitoring would call for integration of groundmeasurements and aerial / satellite remote sensing data along with the GIS onthe flood plain characteristics including topography in a GIS domain. The floodrisk zone maps need to be refined with high spatial resolution data and digitalelevation models based on close contour information. Furthermore, the multi-temporal satellite data have been used for assessment of water spread in thereservoir. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 80. 79Currently, seasonal snowmelt forecast is being given for sutlej river and weeklyforecasts for Beas and Parbati basins. There is a need to develop improvedsnow-melt run-off models using multi-frequency, multi-look angle and multi-polarization SAR data for deriving information on snow cover characteristics.Using Landsat – TM, IRS 1A / 1B LISS II data maps at 1:250.000 scale and1:50,000 scale the extent and spatial distribution of glaciers have beengenerated. Further improvement could be made using IRS 1C / 1D LISS III andPAN and proposed Cartosat 1 PAN and IRS P-6 and LISS IV merged data.Efforts need to be made to fine tune various hydrologic models, namely, rainfallrun off prediction using multi-temporal high spatial resolution space borne multi-spectral data.3.8 Geosciences With the currently available space borne multispectral data, the geological,geomorphological and hydrogeomorphological maps on 1:250,000 scale havebeen prepared at operational level. The National Drinking Water TechnologyMission Project encompassing generation of hydrogeomorphological maps forentire country at 1:250,000 scale is an example of such capability. However, forsome areas such maps have also been prepared at 1:50,000 scale. By mergingLISS III and PAN data, detailed maps up to 1:15,000 scale covering smaller alsoarea are being generate. Besides, targeting the areas for mineral exploration aswell as the detection of thermal anomalies arising out of volcanic eruption andunderground coalfire, have also been undertaken. The IRS-1C LISS III and PANmerge data enabled detection of areas for diamond exploration. In addition toexisting techniques, stress need be given on new methods incorporatingcomputer based mathematical models, particularly for concealed deposits.The aeromagnetic observations are powerful tools for geological mapping andmineral exploration. The integration of aeromagnetic data with remote senseddata has not only helped in delineation of sub surface basement structurescontrolling the occurrence of hydrocarbon-bearing sediments, but also in theestimation of the thickness of sediments in the Cauvery and Kutch basins. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 81. 80Conjunctive use of multi-spectral thermal data, satellite altimetry, radar,a ndaeromagnetic data may be made for better prospecting of oil field detection.The hyperspectral measurements in the visible / NIR / SWIR / TIR region with aspectral resolution of 10 nm have been found to be quite useful for identificationof different rock forming minerals. The geological application potential of such asensor has to be explored in detail in the Indian context. Apart from suchstudies, operational models for ground water yield may be developed frominformation on ground water recharge, draft and balance derived from remotesensing data.The information on phase difference obtained from microwave signals can beeffectively used to detect the micro-relief changes resulting from earthquakesand landslides, and other dynamic phenomenon which is an important area fortaking up pilot studies. In addition, landslide-prone areas could be delineatedusing higher spatial resolution data with stereo coverage from IRS-1C / 1D andfuture IRS-P5 missions. The GPS network may be useful in monitoring tectonicmovements.3.9 Integrated Surveys For sustainable development of any region, the information on availableland and water resources need to be suitably integrated with other collateral andsocio-economic data in GIS domain to arrive at locale-specific prescriptions on awatershed basis. The locale-specific action plans, to illustrate, include waterharvesting structures, soil conservation through terracing and contour bunding,afforestation, agro-forestry and agro-horticulture, and fuelwood and fodderdevelopment. Currently, the IRS-1B LISS II data are being used for generatinginformation on land and water resources at 1:50,000 scale under IntegratedMission for Sustainable Development resources at 1:50,000 scale underIntegrated Mission for Sustainable Development (IMSD) project. The IRS-1CPAN data are also being also used for identification of individual fields where a Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 82. 81specific action plan is to be implemented by digitally superimposing the cadastralmap boundaries over digital PAN data.For generating action plan at village / micro watershed level, cadastral-levelmaps for land and water resources need to be prepared using proposedCartosat-1 PAN stereo data with 2.5 m spatial and better than 5 m Z-axisresolution in conjunction with the multispectral LISS-IV data with better than 10mspatial resolution available from future IRS-P6 mission and integrating in GISdomain. The IRS-1C LISS-III data are currently used for impact assessment ofthe implementation of action plan. It could be further improved with theavailability of higher spatial resolution multispectral data LISS IV from IRS P6.The National (Natural) Resources Information System (NRIS) with the digitaldatabase on natural resources and related cadastral information is beingestablished at district / taluk headquarters to enable decision makers andplanners to use this information for planning and implementation of locale-specific prescriptions / action plan at gross-root level.The rule-based expert system for objective integration of information on land andwater resources, and socio-economic data need to be developed for generationof action plan. It could be achieved by developing a general model andsubsequently incorporating the values for locale-specific variables to suit thelocal conditions.3.10 Ocean Applications The sea surface temperature (SST) and potential fishing zone (PFZ) mapshave been generated routinely using NOAA-AVHRR data. Currently, the PFZmaps are generated bi-weekly on every Monday and Thursday using ¾ daysSST composite. These PFZ maps are of very coarse resolution. A PFZ mapalong with the SST and PFZ image over north Indian Ocean is given in Figure –13. The PFZ maps have helped fishermen to get more fishes. The catch perunit effort (CPUE) is more wherever PFZ maps have been used as compared tosituations where it was not done so. To be more effective, high resolution PFZ Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 83. 82maps showing the maximum details for easy approach need to be generated.The integration of Sea Surface Temperature (SST) with chlorophyll concentrationis required for PFZ forecast which could be achieved using the current and futureplanned ocean colour missions like Sea WiFS (SeaStar), ADEOS-OCTS andOCM aboard OCEANSAT-1 and 2. Using IRS P3 MOS-B data, attempts havebeen made to retrieve chlorophyll, suspended sediments, and yellow substanceand aerosal optical thickness using linear inverse PCA model. The estimation ofcolumner primary productivity using spectral and non-spectral models to predictthe mixed layer production for fisheries forecasting and carbon assimilationstudies in the oceans are in progress.The information on altitude of the satellite orbit provided by altimeter aboardcurrent and future missions, may help studying the deviation in the ocean geoids.Microwave sensors play an important role in monitoring the spread of oil slicks.An operational methodology for identification and estimation of its precisethickness and spread need to be perfected.Sea topography variations derived from altimeter, sea surface winds fromscatterometer, sea-surface temperature from AVHRR / ATSR and salinity from L-band microwave radiometer are some of the inputs to ocean circulationprediction models-both wind-driven and thermohaline types. The altimeter andOcean Colour Monitor (OCM) data from the proposed OCEANSAT could be usedfor generating information on wave energy and directional spectrum is essentialand extremely useful for coastal zone development and execution of off-shoreprojects. Coastal zone mapping for entire Indian coast has been carried outusing IRS-1B LISS-I/II data which has enabled defining coastal regulation zoneto protect coast line from exploitation and helped generating optimal land useplanning. In addition, coral reef mapping was also carried out using IRS-1A/1B/1C LISS-II / LISS-III data which has enabled identifying and ultimatelyprotecting areas of active coral reef and helped earmarking some areas asmarine parks. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 84. 833.11 Atmospheric Applications The information on various atmospheric parameters, namely temperatureand humidity profile, wind, atmospheric pressure, sea surface temperature,ocean circulation, swells, etc. are extremely important for weather forecasting.Currently, information on cloudiness and winds derived from INSAT data and seasurface temperature and humidity profile from NOAA data are being used forweather forecasting. Improved forecasting seems feasible from improved /additional information on surface pressure, cloud height, precipitation, and seasurface and mid-level winds derived from future space missions. Thetemperature profiles from the surface to 10 mbar level, water vapour content, andozone content derived from TOVS-TIROS operational vertical sounder could beused for numerical weather prediction (NWP). Timely and reliable information oncyclone development and movement is a pre-requisite for taking upprecautionary measures for combating disaster as it results in saving severalhuman lives and property. The INSAT-VHRR / DWS is currently used for disasterwarning which is, by and large, satisfactory. Efforts are, however, on for furtherimprovement in the efficiency and precision of existing disaster warning system.The EOS-CHEM-Ozone Dynamics Ultraviolet Spectrometer (ODUS) and EOS-AM-! And Measurement of Pollution in the Troposphere (MOPITT) may provideinformation on air pollution whereas MOS aboard IRS-P3 may provide thedesired information on large-scale air pollutants and the upwelling zones.The satellite remote sensing has been found to be very useful in the assessmentof spatial distribution and concentration of ozone. The sensors aboard IRS-2series of satellites, Total Ozone Mapping Spectrometer (TOMS) and OzoneDynamics Ultraviolet Spectrometer (ODUS) aboard EOS-CHEM series mayenable regular monitoring of global ozone. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 85. 843.12 Climate / Geo-sphere and Biosphere Programme Realizing the importance of space borne measurements in providinginformation on climate change due to anthropogenic disturbances, the IndianSpace Research Organixation (ISRO) has initiated a programme titled “ISRPGeo-sphere and Biosphere Programme”. The programme includes around 40research projects dealing with each core theme of the International Geosphereand Biosphere Programme (IGBP). The salient features of the programmeincludes the development of digital database on land use / land cover, Indiaevapotranspiration modeling, development of biophysical algorithms, studies ontrace gas fluxes and development of models for biomass and net primaryproductivity using IRS data. Future plans include development of soil-vegetation-atmosphere model using spaceborne multispectral measurements in conjunctionwith in situ observations.4 Geo-Spatial data Access & Dissemination:4.1 Means of Geo-spatial data access: The geo-spatial data includes not only data, which have already beencaptured in a digital format, but also those, which have the potential to beprocessed and stored in this way (Nigel, 2001). We can also define access togeo-spatial data sets as the opportunity for an individual or organizations to makeuse of data for specific application or general use. Rhind (1988) suggested thatthere were four factors affecting the spread and development of informationtechnology: the availability of hardware, software, live ware and data.Nigel (2001) represents the growth in geo-spatial data since the 1960 when suchinformation started to be processed on computer system, and distinguishesbetween two types of geo-spatial data: first, those existing in a non-machinereadable form that have to be entered for computer processing, and secondly,those already held on or captured onto electronic media in a digital format. In theearly years the data and information was captured and stored in a paper format Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 86. 85as hardcopy data. To use this data and information for any further analysis needdigital conversion from hard copy to computer readable softcopy format. Withinthe last 15 years the direct data capture into computer readable format becomemore significant. As the computer and information technology grows rapidly itmay be predictable that more and more geo-spatial data will be captured directlyonto a computer system in digital format.4.2 Access to Non-Digital Geo-spatial Data The main problem with conventional non-digital data is the identification oflocation and source of data. The non-digital data may available in simple paperformat either as a map sheet, typed or hand written document in decentralizedfashion. Organizations, which hold non-digital geo-spatial data, range fromnational to local, and are either in government or private ownership. In IndiaSurvey of India (SOI), National Remote Sensing Agency (NRSA), GeologicalSurvey of India (GSI), Forest Survey of India (FSI) and other local levelorganizations, land record offices and libraries are the major sources forhistorical geo-spatial data.4.3 Access to Digital Geo-spatial Data The data standard and format are key questions relating to access ofdigital format of geo-spatial data. There are a close connection between theformat in which geo-spatial data is stored and the capability of the user’ssoftware. If the digital format of data is not compatible with available applicationsoftware of user’s than the availability and accessibility of geo-spatial databecomes less useful.Technical questions relating to the interchange of digital geo-spatial data concernboth the hardware and software that are used for data preparation, storage andanalysis. As the media for storing digital data has moved through a sequencefrom punch card and tape, floppy disk, compact disk, DVD and network baseaccess, transfer and sharing, it is possible to see how a wide range of hardware Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 87. 86and software combinations have eventually been reduced to a more restrictedset of standard features.One important advantage of digital data is the potential easiness with which aparticular datasets can be accessed, either making copies of the datasets can bedistributed to the users via conventional means on computer storage media, ormulti user access of the same datasets can occurs simultaneously in a networkenvironment. In the conventional method of digital data distribution the data canbe copied into any memory media and can be distribute to number of user bysimple postal system. The multi user access and sharing of digital data isachieved by using network system (LAN, WAN, VPN etc)4.4 Desktop GIS Desktop or single PC base GIS system provides an interactive system toaccess and analyze complex geo-spatial data. The desktop GIS is a entry level,low cost solution that provides basic viewing and querying of geo-spatial data, aswell as basic map production and spatial analysis tools in single userenvironment. Desktop GIS applications provide sophisticated analysis at thefingertips of specialized staff, helping them analyze patterns and problems,resulting in the information required to craft land management solutions. DesktopGIS may provide a collection of software products that runs on standard desktopcomputers. Desktop GIS environment provides a facility to create, import, edit,query, map, analyze, and publish geographic information.In a simple desktop base GIS (Fig. 1 and Fig.2.) the digital geo-spatial datastorage mechanism vary from simple file system to RDBMS/ORDBMS storageand management environment. Typically the geo-spatial data is created andstored either in raster or vector data format. The raster and vector format of geo-spatial data storage have certain advantages and disadvantages over eachother. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 88. 87 User GIS Applications GIS Data Fig 1 Simple desktop GIS for geo-spatial data access Various desktop GIS software products are available either as opensource or commercial products. Most popular commercial GIS software productsinclude ArcINFO, ArcGIS, Arc GIS Server, MapINFO, ERDAS, EAIM, ENVI etc.In other side the recent developments in desktop GIS is development andutilizations of open source or freeware software products. Various internationaland national organizations and societies are active to promote open source andfreeware desktop GIS products like GRASS GIS, OSSIM, Quantum GIS, gvSIG,etc for research and operational uses. In other side various geospatial librarieslike FDOGDAL/OGR, GEOS, GeoTools, MetaCRS, PostGIS etc are freely available forGIS software development and customizations.The different desktop GIS software product uses various data storage methodseither in their native data format or in open standards like Geotif or shape file, but Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 89. 88in the same time they also provides facility to exchange the data formats forbetter utilizations and accessing. Some of the most popular data storage formatincludes Shape file, Arc Coverage, TIFF, IMG etc. As the information technologyhas taken quantum jump from simple file system to database managementsystem for digital data storage, the GIS professional also start to useDBMS/RDBMS technologies for geo-spatial data storage and management. Fig. 2. Desktop GIS environment -Open source and commercial4.5 Distributed/ Enterprise GIS Geographic Information System (GIS) is an emerging multidisciplinarytechnology involving disciplines namely geography, photogrammetry,cartography, remote sensing, surveying, GPS technology, statistics and otherdisciplines concerned with handling and analyzing spatially referenced data. Thetechnology is growing at very fast speed and has taken a quantum jump from theera of mainframe computer to workstation and to desktop-based PC systems.With the recent advances in broadband and wireless communicationtechnologies as well as the dramatic increase in internet technology it ispromising to extend further the reach and range of GIS user working in officesand laboratories in the field or at home would lead to the development of networkbase GIS. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 90. 89In the enterprise GIS environment the geo-spatial data is stored and managed incentralized fashion with standard data format. The authorized user (s) of geo-spatial data can access and also edit the data in the same time. The GIS clientapplication will responsible for establishing the link between GIS server and clientthrough secure network connection. In the distributed GIS environment thecentral server can be replaced with physically distributed server and available toclient as a single entity to access the geo-spatial data.In practical terms any GIS system is only as good as the information it canprovide to an end user. For instance, even if the most sophisticated analysis canbe performed in a short time it is meaningless if the deliberate recipient cannotinterpret the end results. In order to present information, GIS employ a variety ofmethods ranging from the composition and printing a map image to aspreadsheet style report of tabular information. Many systems allow the user tocreate a Layout, which can include charts, maps, tables, text and so on. Theimportant point to bear in mind when creating this output is its fitness for purpose.The best outputs are those, which use the right geo-spatial tools rather than all ofthe available ones.4.6 Internet/ Web GIS The new development in Internet and GIS technologies leads to develop aweb base GIS solution to enhance the outreach and access of geo-spatial data inmulti user environment, where a server provides geo-spatial data (vector orraster) or query results over the Internet through a web browser such asMicrosoft Internet Explorer, Netscape Navigator, Mozila etc. Internet or webbased GIS is the most common way of sharing data though is to save data to adisk, which can be accessed by more than one user of the same GIS (Client-server model). In a traditional GIS, unfortunately it will not necessarily open allformats of data. For instance, Vendor X’s GIS may open Vendor Y’s data typebut not Vendor Z’s. This is because some formats are proprietary or because asystem is not designed to open other data. To counter this phenomenon, many Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 91. 90GIS allow data to be exported or converted into a format, which can be read byother systems. There are also many commercial packages, which will translatedata from one format to another.Traditionally, GIS was dominated by commercial software and data, user,application, organization and technologies independent of each other’s. Thus, ithas reduced in some way fully integrated development of GIS technologies, butnow with the power of interoperability, flexibility, Open GIS solutions andnetworking via Internet, the GIS community can better exchange spatialinformation and build application even with different solutions. In fact, GIS hasbecome one of the best user-friendly tools to integrate and analyze spatial / non-spatial information in a tremendous wide range of sectors (e.g. health, geology,disaster management, environment assessment). GIS technology, if usedproperly, can assist any organization that has the will of seeing decision-makingin an open “geospatial” perspective.The internet is a vast communications network that today links together morethan 4 million computers all over the world. Krol (1992) coined the term “Internet”,to a global network of computers connected through communication devices toone another for information sharing. The rapid growth in Internet activity over thelast few years has produced a literal explosion of information and revolutionizedthe way it is disseminated. The most important capability of the Internet is tointegrate information from various sources in a seamless fashion (Green, 1994).The web environment enables users all over the world to share their data andpractice cooperation on scales that was earlier impossible. The Internetconnectivity is increasing at a very fast rate and it becomes unique source ofmany application areas such as internet web publishing, voice email/electronicmail, online interactive training, telnet applications, online library information,online shopping/advertising and internet GIS.The integration of geo-spatial technology with Internet technologies is allowingGIS professionals to solve one of the most important problems inhibitinginformation utility: How to provide access to information and data withoutburdening end users with complicated and expensive software (Karnatak, 2005). Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 92. 91Internet is a perfect means of geo-spatial data accessing, dissemination,analyzing and transmission. The World Wide Web, FTP (file transfer protocol)and HTTP programs make it convenient to access and transfer data files acrossthe Internet. The Internet provides GIS users easy access to acquire GIS datafrom diverse data source in distributed environment. GIS users can use anddownload the data by sending the request through web browser application.The World Wide Web is fast becoming a standard platform for geo-spatial dataaccess and dissemination. It is a means for GIS users to exchange geo-spatialdata, conduct GIS analysis and present GIS output in the form of maps. Internethas facilitated three major changes in GIS (Zhong and Ming, 2003): (i) Access todata; (ii) Transmission of data; and (iii) GIS Data analysis. Therefore, Internetbase geographic information system is a special tool that uses Internet as ameans to access and transmit remote data, conduct GIS analysis and makespatial output. The network base geo-spatial data access has several potentialadvantages over standalone system include-i) Worldwide access; ii) Standardinterface and iii) Cost-effective maintenance etc.Typical client/server architecture for geo-spatial data access and dissemination isgiven in Fig. 3. A client/server application has three components: a client, aserver, and a network. The client sends a request to the server, which processesthe request and returns the result to the client, the client then manipulates thedata and/or results and presents to the user. Internet GIS applies theclient/server concept in performing GIS analysis tasks in multi user environment(Karnatak et.,al, 2007). Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 93. 92 Fig. 3. Typical architecture for Internet base geo-spatial data accessThe Internet GIS is a distributed system and can access distributed database inorder to perform distributed processing (Hall, 1994). Internet GIS use thiscapability of Internet for data sharing, analysis and querying. Web GIStechnology is dynamic, for example, once any client (s) or database administratorupdates the data or information at server end, it will available for all the clients onweb at the same time. The Internet GIS can also link with real time information,such as satellite images, traffic movements and accident information by real timeconnection with the relevant information sources.Web GIS Application- Case study In order to make the spatial information on natural resources available touser community, the Department of Space, Govt. of India has launched aprogramme titled “National Natural Resources Repository (NRR)”. LULCassessment on 1:250,000 have been taken up as part this activity to providerapid assessment for LULC to understand and assess intra and inter annualchanges. The project focuses on generating information on Kharif cropped areaat the end of the season and to prepare LULC map at the end of each year since2004-2005 crop year. In addition, the project also aims to generate the nationallevel assessment of seasonal water body and snow cover distribution usingmulti-temporal AWiFS data by applying automatic feature extraction technique.The web based information system based on national level programme on RapidAssessments of land use/ land cover changes of India using AWiFS data hasbeen developed as BHOOSAMPADA web portal(http://applications.nrsc.gov.in:15001/). This portal provides a multi-user crossplatform to access, query and analysis geo-spatial data in a simple web browserenvironment without having any specific GIS/ image processing softwareinstalled at client end. Various GIS tools and functionalities are available to itsusers for spatial output generation (Fig.4). The web portal serves its data andinformation as web service format which is an industry standard mechanism to Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 94. 93share and distribute data and information to its user without physical transfer ofdata. Fig. 4. Bhoosampada- interactive web GIS application.4.7 Services Base Data Access The services base data access mechanism is becoming more popular inInternet base GIS solutions for geo-spatial data access and disseminations. Webservices are self-contained business functions that operate over the Internet. Interms of geo-spatial features, this means one can perform specific geo-spatialactivities over the network. The web service concept defines the relationshipsbetween the three major actions in geo-spatial data access: • Service providers who publish services • Service requestor who search and use services • The service registry that matches the request with the existing services.Web services allow building a highly distributed infrastructure, where each webservices can be dedicated to a specific task. Applications built on these webservices can access a set of well-know services or a set of services that aredynamically discovered and chained to solve a specific problem.In GI domain the OGC (Open GIS Consortium) specifications for web servicesare internationally accepted standards. The OGC compliant web services areimportant for interoperable GIS solution. The following services arerecommended from OGC: Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 95. 94 • WMS- filters and portrays spatial data as static maps/images. • WCS-similar to WMS, but provides actual data (not images). Best for raster. • WFS-defines the interfaces between web-based clients and servers for accessing feature-based geo-spatial data. Recommended for vector data. • WRS- Allows data searchable.Service based data sharing- Case study The Bhoosampada web portal developed by NRSC provides a webservice based data access and disseminations where WMS specifications ofOGC are adopted and implemented. For example the WMS of land use landcover map of India (Year 07-08) is accessible through following services:GetCapability-http://applications.nrsc.gov.in:15002/cgi-bin/mapserv.exe?map=/ms4w/apps/lulc/Mapfiles/lulc0708.map?SERVICE=WMS&VERSION=1.1.1&REQUEST=GetCapabilitiesGetMap-http://applications.nrsc.gov.in:15002/cgi-bin/mapserv.exe?map=/ms4w/apps/lulc/Mapfiles/lulc0708.map&A Web Map Service (WMS) is a standard protocol for serving georeferenced mapimages over the Internet that are generated by a map server using data from aGIS database. GetCapabilities URL of WMS returns parameters about the WMSand the available layers. The available layer can be accessed through given URLin any WMS compatible software. The map generated at client end using givenURL in desktop GIS application is shown in Fig.5. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 96. 95 Fig. 5 Accessing WMS layer from Bhoosampada in Quantum GIS.4.8 Mobile GIS and mappingMobile GIS is another growing technology for geo-spatial data access anddissemination. Mobile GIS is the combination of geographic information system(GIS) software, global positioning systems (GPS), and mobile computingdevices. Mobile GIS fundamentally changes the way information is collected,used in the field, and shared with the rest of an organization. A mobile GIS allowsyou to visualize information in a digital map, collect information where youobserve it, and interact directly with the world around you, while improvingproductivity and data accuracy (ESRI, 2004). Mobile GIS greatly improves thedata collection and processing in real time or near real time environment.4.9 Spatial data InfrastructureThe term "Spatial Data Infrastructure" is used to denote the relevant basecollection of technologies, policies and institutional arrangements that facilitatethe availability and accessibility of the spatial data. The SDI facilitatesmechanism for spatial data discovery, evaluation and application for users and Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 97. 96providers within all levels of government, the commercial sector, the non-profitsector, and academia and by citizens in general.The term "infrastructure" typically brings to mind public facilities such as roads,rail, sewer lines, electric lines, airports, medical facilities and similar physicalstructures or networks in which government has played a major role in theirconstruction or ongoing support. Thus, terms such as the National InformationInfrastructure (NII) and National Spatial Data Infrastructure (NSDI) typically bringto mind the facilities being provide to allow the more efficient transmission andcommunication of data and information in support of the general and widespreadinterests of broad sectors of society. The government sector plays an importantrole in developing the fundamental spatial information infrastructure because ofits activities in the systematic collection, maintenance, and dissemination of geo-spatial data. These resources have significant uses beyond their governmentalpurposes. Fig. 6. A typical hierarchy of SDI The success of developing any type of spatial data infrastructures heavilydepends to on individuals realizing the need to cooperate with each other. Thetypical hierarchy of any SDI varies from global to corporate SDI. A typical SDI Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 98. 97hierarchy of SDI is shown in fig. 6. Spatial data infrastructure can contain severalcomponents, including Geo-Spatial Web Services. If the host organization uses aWeb Service to access and disseminate the geo-spatial data, these web servicesthen play a major role in the SDI. Fig. 7. Spatial Data Infrastructure4.10 Indian National Spatial data Infrastructure In India also the geo-spatial data is available with diverse organizationslike Survey of India, National Remote Sensing Agency, Geological Survey ofIndia, Forest Survey of India, etc in different data standard and format. There is aneed to create a metadata and also data browsing and sharing mechanism tomake available these geo-spatial data to public domain. Department of Scienceand technology (DST) with collaboration of Department of Space Government ofIndia (DOS) has taken an initiative to establish a Indian National spatial dataInfrastructure (NSDI) for public domain in participation of other governmentorganizations, private sectors, academia, research centers and NGO’s. A typicalstructure of NSDI is shown in Fig.7, Fig.8. The Indian NSDI is available as a webportal under URL http://gisserver.nic.in/nsdiportal. The India NSDI Portal makesdata access and sharing of geo-spatial data easier, faster, and less expensive forall levels of government and the public.Indian NSDI focuses on de-centralized approach with main emphasis on: • Develop and maintain standard digital collections • Develop common solutions for discovery, access and use of spatial data • Build relationships among organizations Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 99. 98 • Increase the awareness and understanding of the vision, concepts and the benefitsIn the NSDI framework the data provider of geo-spatial data will make availabletheir data under single web portal as a web services. There is a NSDI clearinghouse for browsing and accessing the geo-spatial data. The NSDI secretariat willcheck the user request and authorize for data access and download.Fig. 8 Indian NSDI Network system for geo-spatial data access and sharing4.11 Data Interoperability The problem of data heterogeneity is the major concern for considerationin geo-spatial domain. Various organizations have huge geo-spatial data but inheterogeneous data formats and standard, which makes it difficult to utilize thesedata for an application on a common platform. To overcome such problems andto make data interoperable, many countries have developed their data standardand formats. Government of India also has taken initiatives with theestablishment of National Spatial Data Infrastructure (NSDI) and hasrecommended NSDE (National Spatial Data Exchange) data format to be usedby all the Indian geo-spatial data providers. The situation can further be improvedif some fast data-sharing medium like Internet is taken into consideration, so thedata can be shared and viewed on web Browser. For this data should be in alanguage, which can be understood by browsers, OGC recommended GML is Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 100. 99popularly accepted as the language for spatial data exchange and sharing overthe web.Indian Space Research Organization (ISRO/DOS) has also taken an initiative todevelop a common standard for geo-spatial data creation under National NaturalResource Management System (NNRMS). The NNRMS standards address thevarious level of geo-spatial data creation issues. With these specified standards,the problem of heterogeneity among data of different organizations could besolved, but easier and faster access of data is another requirement. This canonly be achieved by transferring maps through Internet and hence this datashould be encrypted into a language that can be understood by web browsers,like XML (Extensible Markup Language). The Open GIS Consortium (OGC)recommended Geography Markup Language (GML), an XML language, isspecially designed to solve most of the issues in geo-spatial data interoperability(Henning, S., 2001; Chang, C. et al). By mapping from the NSDE format to GMLdocument, the existing local GIS bases are moved into global domain.4.12 Practical problems: The main practical problems for many users seeking access togeographical data from secondary sources relate to finding out what data areavailable, whether these data satisfy the users requirements, and whether theyare reliable (Nigel, 2001). In general terms the answers to these questions areprovided by what is refereed to as metadata, or information about data anddatasets. The collection of such metadata is not only for the benefit of end-usersbut also for the personnel working in organizations which provide a data service,the data suppliers.Metadata can be divided into three categories. These categories can be relatedto the three main questions, which a user of geo-spatial data from secondarysources needs to be able to answer: Nigel (2001) categories the metadatacategory under three main questions: Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 101. 100 • What data are available? - Whether suitable data set exists – match precisely with users requirements • Where are they available? - Where data are stored in a computer system or archive; and, secondly where data re held - Which concerns data suppliers – whether the organization responsible for data collection. • How are they stored? - When the intension is to access the raw data, the user also needs to know about the datasets file and record structure, data item types and software format. The structure and format also especially important when using datasets, which were generated some time ago.The development of such metadata the information systems should enhance thepotential users ability to identify metadata sets, which fulfill their needs, althoughclearly their value is dependent upon the maintenance of an accurate andcomplete directory.5 Conclusion: Environmental and natural resource management problems are bothspatially distributed and determined by complex processes and relationships.Geoinformatics as a tool plays a vital role for managing our environment andnatural resources. To understand the nature and its spatial distribution andcomplex relationship for better management involves numerous interactingelements with multiple attributes. Geographic Information System (GIS) is apowerful tool in which spatial information can be stored, organized, and retrievedin a user friendly environment. Conjunction of satellite remote sensing data andancillary data in GIS environment combined with the Global positioning system(GPS) data is a potential tool to environment management. The awareness andutilization of these technologies and the power of spatial information systemsspecifically oriented towards decision making or resource management isgrowing rapidly in our country.The spatial data access and dissemination issue becomes more challenging taskdue to complex data structure, volume of data, format and standard and security Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 102. 101issues. Integration of geo-spatial technologies with information andcommunication technology provides a tremendous opportunities as well aschallenges in spatial data storage, access, analysis and dissemination.With the advent of new technologies in spatial data access and disseminationsentire globe being digital and every part of earth surfaces being integratedthrough digital data products, distribution/ dissemination of spatial data assumesgreater significance. The geo-spatial technology has grown tremendously fromsimple desktop GIS to web GIS, Mobile GIS.Integrating GIS with Internet is an inevitable trend of the future in GIS community.It is important for the GIS community to monitor and define the course of itsdevelopment and deployment. It is essential for Internet base geo-spatial dataaccess and disseminations to be able to take advantage of the distributedprocessing to access analysis models and distributed data on the network inorder to achieve high interoperability. It is also desirable for end users to be ableto download and save data in his/her local machine. However, apart frombandwidth constraints, the technology involved in web applications offers someunique challenges for application developers more research and case studies arerequired to wide the horizon of this important technology. The spatial databasemanagement using relational database management system (RDBMS) and theconcept of the geo-database opens new windows for future development.The web services base data access and dissemination methods are opening anew window for future data access where the distributed geo-spatial data can beaccessed through a web base application under single portal. The spatial datainfrastructure (SDI) and NSDI are challenging task for enhancing the outreach ofgeo-spatial data. As the information and communication technology will grow, theoutreach of geo-spatial data and information will increase.References: • Chang, C., Chang, Y., Chuang T., (Bridging Two Geography Languages: Experience in Mapping SEF to GML, http://homepage.iis.sinica.edu.tw/~trc/papers/gml2003 (last accessed 22nd Nov 2003). Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 103. 102• Clarke, K. and Gaydos, L.J. (1998) Loose-coupling of a cellular automaton model and GIS: long-term urban growth prediction for San Fancisco and Washington/Baltimore. International Journal of Geographical Information Science, 12(7), pp. 699-714.• Fedra, K. (1994) GIS and environmental modeling. In: M.F. Goodchild, B.O. Parks and L.T. Steyaert [eds.] Environmental Modeling with GIS. 35- 50, Oxford University Press.• Fedra, K. 1993. Distributed models and embedded GIS: Strategies and case studies of integration. Second International Conference/Workshop on Integrating GIS and Environmental Modeling. Breckenridge, CO. Sept. 1993.• Green, D.G. 1994. Databasing diversity – a distributed public-domain approach. Taxon 43, 51-62.• Hall, Carl L. 1994. Technical Foundations of Client/Server Systems, New York: John Wiley & Sons, Inc• Harish Chandra Karnatak, Sameer Saran and P. S. Roy, 2005 “ Spatial services, a click away” article in Geospatial Today Volume 3 Issue 5 pp- 42-46 January-February 2005.• Harish Chandra Karnatak, Sameer Saran, Karamjit Bhatia and P.S. Roy, (2007), “Multicriteria Decision Analysis in Web GIS Environment”, Geoinformatica, (2007) 11, pp: 407-429: International Journal of Advance Computing and GIS- Springer Science Publication DOI 10.1007/s10707- 006-0014-8.• Henning, S., 2001, Geography Markup Language- the foundation of Geo- Spatial Interoperability?, Nordic GIS Conference 2001 Helsinki, 8- 10.October 2001.• Krol, E. 1992. The Whole Internet User Guide and Catalog. O’Reilly & Associates, Sebastopol CA.• Kurt Fedra (2006), Embedded GIS in environmental management, GIS@development, February 2006. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 104. 103• Mueller-Dombois, Dieter and Ellenberg (1974), Aims and methods of vegetation ecology Dieter Mueller-Dombois and Heinz Ellenberg ISBN- 0471622907-9780471622901.• Nigel Walford, 2001 Geographical data John Wiley publication ISBN 0- 471-97085-9.• Raper, J. and Livingstone, D. (1993) High level coupling of GIS and environmental process modeling. Second International Conference/Workshop on Integrating GIS and Environmental Modeling. Breckenridge, CO. Sept. 1993.• Rhind D.W. (1988) Computing, academic geography and the outside world, in Remodeling geography (ed.W.MacMillan), Blackwell, Oxford. Technical document on Mobile GIS ESRI (2004).• Technical document on Mobile GIS ESRI (2004).• Zhong-Ren Peng, Ming-Hsiang Tsou “Internet GIS: Distributed Geographic Information Services for the Internet and Wireless Networks” ISBN: 0-471-35923-8m March 2003. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 105. 104 APPLICATIONS IN AGRICULTURE AND SOILS S.K. Saha Agriculture and Soils Division1. Information Needs for Sustainable Agriculture Agriculture is the backbone of Indian economy, contributing about 40 per centtowards Gross National Product (GNP) and providing livelihood to about 70 per cent ofthe population. So, for a primarily agrarian country like India, accurate and timely infor-mation on the types of crops grown and their acreages, crop yield and crop growthconditions are essential for strengthening countrys food security and distributionsystem. Pre-harvest estimates of crop production are needed for guiding the decisionmakers in formulating optimal strategies for planning, distribution, price fixation,procurement, transportation and storage of essential agricultural products. Sustainableagriculture development in any country can only be achieved if the natural resourceslike soils and water etc. which it relies is well managed. In a country like India, whereagriculture is the backbone of the national economy, there is an urgent need togenerate and disseminate a specific system for the management of crops, soils, inputand natural resources to sustain high productivity and maximum profit while preservingthe fragile agro-ecosystem. With the advent of Remote Sensing Technology, satellite data are being used formapping, monitoring and assessment of agricultural and soils resources of a givenarea. Space –borne sensor data being repetitive and multi-spectral in nature, is anideal choice for use in monitoring and assessing dynamic agricultural resources. GISacts as computerized database management tool, offering solutions for planning andproblem analysis related to agriculture. Remote Sensing and GIS techniques arebecoming fast and effective tools for extracting information of complex and dynamicagricultural system. Conventional system of crop production forecasting have severalproblems - Lack of timely information; variations in statistical figures; lack of availability Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 106. 105data (e.g. horticultural crop) and difficult in storing and retrieval Advantages of remotesensing based agricultural resource survey over conventional survey are listed below: • the potential for accelerated survey, • capability to achieve synoptic view under relatively uniform illumination conditions, • availability of multi-spectral data providing increased information, • capability of repetitive coverage to depict seasonal and long term changes, • permitting direct measurement of several important agro-physical parameters which are used in crop growth assessment and yield prediction, • relatively inexpensive - monitoring from space, and • remotely sensed data provide a permanent record.2. Applications in Agriculture and Soils Remote Sensing and GIS technology are being effectively utilized in India in several areas of Agriculture and Soils. The major areas of Remote Sensing and GIS applications in Agriculture and Soils include – Crop / land use inventory (crop acreage and yield estimation; crop condition assessment; cropping system analysis); Soils resource inventory; Land degradation study; Soil erosion hazard assessment and Soil conservation planning of watershed; and Land evaluation for land use planning. Integrated use of Remote Sensing and GIS technology in these areas in India are discussed in the following sections:2.1 Crop / Land Use Inventory Crop inventory related applications comprise of identification/discrimination ofcrop covers and acreage estimation, predicting crop yield and crop growth conditionassessment and cropping system analysis. Use of satellite data for crop inventory inIndia faces tougher technical challenge due to (a) small field sizes; (b) large diversity ofcrops sown in an area; (c) large field-to-field variability in sowing and harvesting dates, Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 107. 106cultural practices and crop management; (d) large areas under rain-fed /dry landagriculture with poor crop canopies; (e) practice of inter-cropping and mixed croppingand (f) extensive cloud cover during kharif crop season (Sahai, 1985). However,significant success has been achieved in crop inventory study using R.S. and GIStechniques in India due to intensive efforts in this direction.2.1.1 Crop acreage estimation Crop discrimination is based on differential spectral response of various crops in amulti-dimensional feature space produced by different spectral bands, or time domain orboth. The crop acreage estimation procedure broadly consists of: i) completeenumeration, and ii) or sample segment approach. All these approaches use currentseasons ground truth data and supervised classification algorithm(s) on digital imageprocessing system. In the complete enumeration approach (for small study area), thestudy area (Blocks, or district boundary is super-imposed on the satellite data and allthe pixels within this boundary are analysed. Estimation of crop acreage for large areasrequires handling of a very large volume of data, larger efforts in ground truth datacollection. To overcome this problem, stratification sampling technique sample segmentbased procedures have been developed under CAPE. The stratification is done usingGIS, based on Crop concentration statistics, agro-physical and/or agro-climatic. Eachstratum is divided into number of segments of 5 x 5 km, 7.5 x 7.5 km or 10 x 10 km sizedepending on field sizes and number of crops grown in each stratum. 10% of thesegments in each stratum, selected randomly is digitally processed to estimate cropacreage per segment. These segment-wise estimates are aggregated at each stratumand finally at state level. A large of variables such as choice of spectral bands, spatialand radiometric resolution of the sensor, acquisition date of satellite data, and imageclassification techniques, influence the results of crop identification using RS data. The satellite based studies on crop inventory graduated from visual to digitalanalysis and by launch of IRS-1A (Indian Remote Sensing Satellite) in 1988, large cropinventory project called CAPE (Crop Acreage and Production Estimation) sponsored by Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 108. 107Ministry of Agriculture, was implemented covering large area crop acreage, yieldprediction and condition assessment for important crops such as wheat, rice, cotton,groundnut, mustard and sorghum (Anonymous, 1995). The two major objectives ofCAPE project were: (i) to develop methodology for state level acreage and productionestimation of important crops and (ii) to transfer technology to state level agencies for itsoperational applications. Under CAPE mainly IRS-1A, 1B, 1C & 1D LISS-I, II & IIIdigital data were being used for district and state levels acreage estimation. The CAPEprocedure is being continuously revised and upgraded to improve upon accuracy andtimeliness of crop estimates. These efforts are related to improving sample design;ground truth data collection; optimizing date of acquisition; including data fromadditional spectral regions in the digital analysis; use of higher spatial resolution satellitedata; use of microwave data for crop inventory in Kharif (rainy) season; adoptingdifferent classification procedures. Ministry of Agriculture demanded to develop a system providing multiple inseason crop assessment after successful results of CAPE project. ForecastingAgricultural output using Space, Agro-meteorology and Land based observations(FASAL) has been conceptualized to meet this requirement. An integrated approachadopted that uses multiple sources of data such as econometric, weather and remotesensing. FASAL aims at (a) Institutionalizing the operational use of RS data for diverseapplications in agriculture, (b) Developing a system for multiple in-season cropassessment and forecasting in near real-time, and (c) Integrated use of tools such asGIS, large databases, modelling and networking. The concept of FASAL thusstrengthens the current capabilities of early season crop estimation from econometricand weather-based techniques by adding the tools of remote sensing in a major way(Figure 1). Components of FASAL have been developed and tested for making multiplein-season crop acreage and production forecasts (Parihar and Oza, 2006) Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 109. 108 l Re na Land mo n tio Observations te e RS Se nv o , Tem Mod. ns Co Agr ology in g r por Re. teo al Me RS y Sin , Hi et r gle gh om Cropped on area da Re. Ec Crop condition te Crop acreage Crop yield MULTIPLE IN-SEASON FORECAST Pre- Early- Mid- Pre- Pre- Season Season Season Harvest Harvest State State District Fig. 1. Conceptual diagram of forecasting agricultural output using space, agro- meteorology and land-based observations (FASAL).2.1.2 Crop yield modeling Crop yield and its variability are two important components required forsustainable agricultural development. Crop yield is influenced by the culmination ofseveral factors such as crop genotype, soil characteristics, agronomic practices,weather conditions and biotic stresses, and the spectral data of crop is an integratedmanifestation of the effects of all these factors on crop growth. A large number ofexperience has been gained in India to use of space-borne R.S. data for yield modeldevelopment and their use in pre-harvest yield forecasting of variety of crops.Methodological aspects of various modelling approaches are briefly presented in thefollowing sections –Spectral yield models: These are empirical models which directly relate multi-spectralsatellite data or derived parameters (Spectral Vegetation Indices, SVI) to crop yield. Inthis approach, SVI at particular growth stage (normally, maximum vegetation growth) isrelated to final crop yield through regression techniques and pre-harvest crop yield is Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 110. 109predicted with the assumption that no accident occurs after that growth stage. In Indiadistrict level yields of major crops like wheat, paddy, sorghum etc. in various parts of thecountry are being predicted under CAPE project following this modeling approach usingempirical relationships between district yields with corresponding area weightedaverage spectral indices (Anonymous, 1995).Agromet – spectral yield models: Agriculture and climate are closely inter-linked in thesense that crop growth, development and production are affected by variation in agro-meteorological parameters during crop growth period. The optimum agro-meteorologicalparameters requirements vary according to crop type and growth stages. In thismodeling approach remote sensing derived SVI is coupled with meteorological indicesand or the yield derived from meteorological models. This approach is better comparedto spectral yield model because the influences of weather on crop yield are noteffectively manifested to that extent in remotely sensed data.Integrated yield models: Yield of a crop is largely determined by the agro-climaticconditions, the management practices adopted and intrinsic genotype of the crop. Thuscrop yield modeling requires relating various spatial biotic factors data layers anddiscrete data through mathematical functions. Use of GIS in integrated yield modelingis very effective because it has capability to handle, manipulate and analyse spatial andnon-spatial data from different sources. In integrated modeling approach, GIS is usedto integrated spatial data of agro-climatic, soil edaphic and management practices inconjunction with satellite derived spectral vegetation indices (SVI) to develop a yieldmodel.Linking Remote Sensing and Crop Growth Simulation Models: These modelspredict crop growth and yield as well as soil and plant water and nutrients balances as afunction of environmental conditions and crop management practices. Biophysicalsimulation models are designed to simulate the time profile of main crop state variables(leaf area index, biomass of various organs, development stages etc.) and of energy,carbon, water and nutrient fluxes at the crop-soil-atmosphere interfaces. Models are Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 111. 110available for the major crops in the world (IBSNAT, 1993). RS can provide actual stateof crop parameters viz. LAI, crop distribution, surface canopy temperature etc., whileGIS allow spatial organization of soil, weather, crop parameters and management dataand display of crop model simulated results. In India, an attempt has been made todevelop a prototype Crop Growth Monitoring System (CGMS) fro wheat usingWTGROWS simulation model in GIS environment for generating daily crop growthmaps and predicting district-wise grain yield (Sehgal et al., 2002)2.1.3 Agricultural Drought Assessment and Monitoring A RS and GIS based integrated method on agricultural drought mitigation,National Agricultural Drought Assessment and Monitoring System (NADAMS)operationally used in India (Rao, 1996), which forms one of the strategies forsustainable agriculture development. NADAMS integrates NOAA satellite derivedtemporal Vegetation Index (NDVI) and land use/land cover and ground meteorologicalstation observed rainfall and aridity anomaly with ancillary crop cultural informationthrough GIS, to provide realistic assessment of agricultural drought.Cropping system analysis Information on existing cropping system of a region is important for finding outagricultural areas with varying crop productivities where sustainable increase in cropproduction can be achieved by adaptation of suitable agronomic managementpackage. GIS technology can play vital role for cropping system analysis of an area, byspatially integrating temporal crop inventory information of various crop seasons of thatarea. Satellite RS and GIS have come up as an ideal tools to analyze cropping systemdue to their capability to provide spatial information on crop, soils, weather andmanagement practices. In India, utility of satellite data for cropping system, inparticular, cropping pattern analysis is well demonstrated (Panigrahi, 2002) Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 112. 1112.2 Soil Resource Inventory Soil resource inventory provides an insight into the potentialities and limitations ofsoil for its effective exploitation. It is a vital input for sustainable land use planning.Various RS and GIS based analysis techniques are used for soil resource inventory andland use planning with respect to soil resource mapping, assessment of degradedlands, soil erosion inventory and soil conservation planning and land evaluation for landuse planning.2.2.1 Soil resource mapping The soil maps are required on different scales varying from 1:1 million to 1: 4,000to meet the requirements of planning at various scales. Though conventional soilsurveys were provided information on soils, they are subjective, time consuming andlaborious. RS techniques have reduced field work to a considerable extent and soilboundaries are more precisely delineated than in conventional methods. Soil mappingusing RS technique needs identification of numbers of elements such as land type,vegetation, land use, slope, elevation, relief which control soil variability. Number ofstudies have been carried out in India on multi-scales (small, medium & large) soilmapping in different soil scapes following visual interpretation of various satellite data(Landsat MSS, TM, IRS-LISS I, II ,III & IV) (Dwivedi, 2001). Recently, attempts havebeen made to use IRS-LISS III and PAN, IRS-LISS IV and Cartosat -1 merged digitallythrough suitable image fusion techniques like HIS, principal component analysis etc.and generating soil maps subsequently through systematic visual interpretation(Dwivedi, 2001).2.2.2 Assessment and monitoring of degraded land Soil degradation is often related to decline in soil quality, caused through itsmisuse by humans. It refers to a decline in the soils productivity through adversechanges in nutrient status and soil organic matter, structural attributes, and Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 113. 112concentration of electrolytes and toxic chemicals (Lal and Stewart, 1990). Thecharacterization of the surface and the estimation of dynamics in surface properties arefound to be essential for interpretation and classification of multi-temporal satellite datain land degradation studies. Several degraded lands viz. salt-affected, water logged;ravenous have been mapped and monitored using IRS satellite data following bothvisual and digital techniques (Dwivedi, 2202).Under National Wasteland / degraded landmapping project, 84 critically affected districts in various states of India, 12 categories ofdegraded lands have been mapped by visual interpretation of Landsat TM and IRS-LISS II & LISS III data.2.2.3 Soil erosion inventory and soil conservation planning The formulation of watershed programme for sustainable agriculturedevelopment needs an inventory of the quantity of soil lost to erosion and prioritydelineation of watersheds for soil conservation measures. A number of modellingapproaches both empirical and physically processed based are used to quantitativelyassess soil erosion hazard through estimation of erosional soil loss. These modelsrequire input parameters in terms of spatial information on soil, land use/land cover,slope, soil characteristics, drainage and rainfall agro-climatic data etc. Most of thiscould be obtained from multi-spectral remote sensing data. GIS technique is veryeffective tool for integrating above inputs for modeling approach in erosional soil lossassessment. GIS technology is also being used for soil conservation planning byintegrated analysis of information on soil erosion hazard, soil, slope, land use/landcover etc. RS and GIS based Universal Soil Loss equation (USLE) model has beenwidely used for soil loss estimation and erosion risk assessment (Patel and Saha,2003)2.2.4 Land evaluation for land use planning The decline of soil productivity due to environmental degradation poses a greatthreat to sustainable agricultural production. It calls for correct evaluation of land Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 114. 113resources in order to optimize and sustain agricultural productivity. Land evaluation, ingeneral refers to matching land qualities with requirements of a particular land usesystem. RS derived soil and terrain information are prerequisite for optimal land useplanning. The most widely used indices and approaches for land evaluation are landcapability, land productivity and FAO Frame Work of Land Evaluation based soil & landsuitability analysis. RS and GIS technique based integrated techniques were used forassessing land capability, land productivity and soil suitability for various crops LandUtilization Types (LUTs) which are vital components for suggesting suitable croppingand farming system for sustainable agriculture development (Martin and Saha, 1999).2.2.5 Integrated Mission for Sustainable Development (IMSD): Sustainable naturalresources development requires holistic approach, maximizing the production aftertaking into account pre-carious environmental condition. In this context, the Indianexperience of using RS and GIS techniques for Integrated Mission for SustainableDevelopment (IMSD) become relevant. The primary goal of IMSD is to integrate in GISenvironment, the information on natural resources derived from satellite RS such assoils, land use/land cover, slope and surface and ground water potential etc., withrelevant collateral socio-economic data at each watershed level, to arrive at locale-specific action plans for sustainable development of each region (Rao, 1996).3. Precision Agriculture Precision agriculture also known as prescription farming, variable rate technology(VRT) and site specific agriculture - is a current buzz word among agricultural circlesand considered as the agricultural system of the twenty first century, as it symbolizesbalance between reliance on traditional knowledge, and management intensivetechnologies. Precision farming technologies provide three basic requirements forsustainable agricultural management. These are, (i) ability to identify exact location offield, (ii) ability to gather and analyze information on spatio-temporal variability of soiland crop conditions at field level, and (iii) ability to adjust input use and farmingpractices to maximize benefits from each field location. Precision agriculture involves Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 115. 114integrated technologies, such as GPS, GIS, Remote Sensing, variable rate technology(VRT), Crop models, and yield monitors. Precision farming is a collection of many high-tech tools, but there is no need to adopt all the PF technologies at once to startbenefiting from them. Even a part of them, such as high resolution remote sensing, GISand GPS, can show field variability in crop and soil conditions for making farmingdecisions. A satellite has the inherent quality of providing information on the spatio-temporal variability of crops caused by natural and agronomic practices. Remotesensing data provide a convenient way of converting point observations, for example,from soil test samples, and ground measurement of biophysical variables like a leafarea index, to distribute information within the GIS. Various image classification andgeostatistical approaches can be implemented in order to achieve this conversion.Many of the soil and crop parameters of interest to farmers are dynamic with time,henceforth, timely repetitive coverage from satellites is an attractive source ofmonitoring information. High resolution imagery, acquired prior to sowing, translatesresults of grid based soil properties, that is, texture, nutrients, organic matter, soilmoisture, and salinity, to a spatial coverage for the whole field4. Conclusions and Research Thrust Areas Various studies carried out in several areas of Agriculture and Soils in India byintegrated use of aerospace data and GIS have clearly indicated that RS and GIStechnologies are very effective tool for suggesting / adopting management strategies forsustainable agriculture development in the country. However research efforts in severalareas are needed for operational crop and soil resources inventory, monitoring andmanagement. Some of them are listed below:• Operational atmospheric correction of earth resources satellite data using satellite derived geophysical products;• Combine use of optical and microwave satellite data;• Use of hyperspectral data and indices;• Retrieval of crop and soil biophysical parameters using satellite data; Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 116. 115• Use of crop growth simulation models;• Use of soil process based soil degradation model;• Retrieval of agro-meteorological parameters using satellite;• Precision crop management using high resolution RS data• Development of DSS and information systems for field level crops and soils managementReferencesAnonymous (1995). Manual for crop production forecasting using space borne remotely sensed data, Space Applications Centre, Dept. of Space, Govt. of IndiaDadhwal, V.K., Singh R.P., Dutta, S. and Parihar J.S. (2002). Remote Sensing based crop inventory:A review of Indian experience. Tropical Ecology, 43(1), 107–122Dwivedi, R.S. (2001). Soil resource mapping: a remote perspective. Remote Sensing Review, 20, 89-122.Dwivedi, R.S. (2002). Spatio-temporal characterization of soil degradation. Tropical Ecology, 43(1), 75–90.Dwivedi, R.S. and Sinha A.K. (1999). Remote sensing applications for soils: retrospective and perspective. Proc. ISRS National Symposium, Bangalore, pp. 105–119.Martin, D. and Saha, S.K. (1999). Land evaluation by integrated use of Remote Sensing and GIS for cropping pattern analysis. Proc. Trends in Geoinformatics Technology and Applications, IIRS, Dehradun, 134–142 pp. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 117. 116Patel, N.R. and Saha, S.K. (2004). Satellite Remote Sensing and GIS applications in sustainable agriculture, In: Geoinformatics for Tropical Ecosystems (ed. P.S. Roy), pp. 376-462.Rao U.R. (1996). Space Technology for Sustainable Development. Pub. Tata McGraw- Hill Publishing Company Ltd., New Delhi.Rao, U.R., Chandrasekhar, M.G. and Jayaraman, V. (1995). Space and Agenda–21: Caring for Planet Earth. Prism Books Pvt. Ltd., Bangalore, India.Saha, S.K. (2000). Crop yield modeling using satellite remote sensing and GIS – current staus and future prospects, Proc. International Symposium on Geoinformatics Beyond 2000, Dehradun.Sahai, B. (1985). Agricultural Remote Sensing in the Indian Context. Proc. Indo–US Symposium–cum–Workshop on RS Fundamentals and Applications, SAC, Ahmedabad, India.Web Linkshttp://nespal.cpes.peachnet.edu/pa/home/http://www./soils.rr.ualberta.ca/soils210/lectures/index.htmlhttp://www.itc.nl/~rossiter/research/rsrch_ss_apps.html#usslhttp://www.fao.org/waicent/faoinfo/agricult/agl/agll/aez.stmhttp://www.css.cornell.edu/landeval/landeval.htmhttp://soils.usda.gov/technical/manual/http://websoilsurvey.nrcs.usda.gov/app/http://topsoil.nserl.purdue.edu/weppmain/wepp.htmlhttp://soilerosion.net/doc/models_menu.htmlhttp://www.soils.orghttp://www.nrcss.org/ Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 118. 117 APPLICATIONS IN FOREST MANAGEMENT S.P.S. Kushwaha Forestry and Ecology Division1. Forest Management Issues India has 20.60 per cent of its geographical area under forests, of which 10.12per cent forests are medium dense, 8.82 per cent open and 1.66 per cent very denseforests (FSI, 2008). Of all forests in the country, 77.70 per cent are tropical, 9.5 per centsub-tropical, 7.00 per cent temperate and 5.8 per cent alpine and other forests(Champion and Seth, 1968). India has 12 per cent of global plant and animal wealth andmuch of it is possessed by the forests. Forest cover in India has fairly stabilized afterearly eighties because of the strict legislative control on the use of forestland for non-forestry purposes. The diversion of forestland for various developmental purposes withprior approval from Government of India, however, still continues. Forest degradation isa major issue currently. Majority of our forests are fragmented due to ever-increasingdemand for cultivable land to feed the overgrowing human and livestock populations. Aspressure over the forests mounts, our concern for their protection and conservationthrough temporal monitoring must also increase. The conventional methods of forest resources assessment and monitoring aretime consuming and fraught with various inadequacies. Many a times they do not matchwith the forest dynamism and hence, become obsolete by the time the results areavailable. The reliability of the results obtained through such methods is oftenconsiderably less. The remote sensing, GIS and GPS technologies have positivelyimpacted the process of forest resource assessment, monitoring and management.Remote sensing has greatly reduced the tedious groundwork in addition to bringinghigher accuracy. It is perhaps the only of its kind tool, which allows retrospectivemonitoring of the forests. Forest management is a multi-faceted activity involving forestchange monitoring, forest fire prevention and monitoring, biodiversity assessment, Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 119. 118protected area management, terrestrial biomass/carbon assessment, eco-developmentplanning, forest damage detection and forest development planning. Each one of theseinvolves generation of the factual spatial and non-spatial data/information using groundsurveys, remote sensing or both as well as data integration and analysis in GIS domain.2. Use of Remote Sensing and GIS2.1 Forest Change Monitoring: The temporal aerial photographs and satellite imageinterpretation facilitates forest change detection and monitoring over time. This wasdemonstrated by National Remote Sensing Agency (1983) using Landsat MSS datawhen entire country was mapped on 1:1M scale for two periods i.e. 1972-75 and 1980-82 using visual interpretation. This was the first-ever nationwide mapping involvingsatellite imagery by ISRO/DOS or forestry sector. The technology has been used byForest Survey of India since then for biennial forest monitoring and change detection.Changes could also take place due to the encroachment of forestland by settlers and inone such case the Space Application Centre, Ahmedabad assessed the encroachmentsin Sanjay Gandhi N.P. in Mumbai, which helped Maharashtra state forest department towin the court case between State and the settlers. The IIRS monitored the changes inthe mangroves of Sunderban Biosphere Reserve recently. There are several suchcases of forest change monitoring in India and elsewhere illustrating good use ofgeoinformatics. Table 1 shows the proper season for aerial and satellite data acquisitionfor forest applications in India.Table 1: Proper season for aerial/satellite data acquisition for forest applications Vegetation Type/Forest Region Season Humid/moist evergreen and semi-evergreen January-February forests of western and eastern ghats Humid and moist evergreen and semi-evergreen February-March forests of north-east India and Andaman and Nicobar Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 120. 119 Islands Tropical moist deciduous forests of northern and central December- India January Temperate evergreen forests of western Himalayas March-May Temperate, sub-alpine, alpine evergreen, deciduous forests September- of Jammu and Kashmir October Arid and semi-arid dry deciduous and scrub forest October- December Mangrove forests February-March, low tide period2.2 Forest Fire Detection and Monitoring Forest fires are a major cause of degradation of Indias forests. While data on fireare weak, it is estimated that the forest area prone to forest fires annually ranges from33 per cent in some states to over 90 per cent in others. Deciduous and coniferousforests experience more fires than other types. Among various floristic regions, thenorth-eastern region suffers maximum from the fires due to the age-old practice ofshifting cultivation and spread of fires from jhum fields. About 90 per cent forest fires inIndia are started by humans. Forest fires cause wide ranging adverse ecological,economic and social impacts. Early warning of fires through risk modeling, fire alertsand monitoring are required for proper mitigation and management. Many studies onfire risk assessment, fire detection and monitoring involving remote sensing, GIS, GPSand fire history have been done throughout the world. The IIRS has developed a riskmodel to assess the proneness of forests for fire. The Global Fire Monitoring Centre(GFMC) of the Freiburg University, Germany uses satellite-based fire monitoringtechniques globally. Fire could be monitored during day and night using thermal infraredbands. The NRSC has developed INFRASS model to detect fires and disseminate theinformation to users in real time. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 121. 1202.3 Biodiversity Assessment Remote sensing can also play a very useful role in the assessment ofbiodiversity. This can be done through forest type mapping, landscapecharacterization wherein a digitally or visually forest type map is taken as direct inputfollowed by ground-based assessment of biodiversity. Many landscape parametersviz., porosity, patch size and shape, interspersion and juxtaposition etc. have adirect relationship with a variety of vegetation features like biodiversity,physiognomy, composition etc. The biodiversity value estimated from field survey isattached to each landscape unit to generate the biological richness maps on1:250,000. A nationwide project on biodiversity characterization covering three-forthof the geographical area of India was carried out by IIRS between 1998 and 2007. Asoftware, SPLAM was developed for this purpose. The Phase-III part of the projectcovering remaining area is currently in progress. Fig. 1 shows a typical output. Very Low Low Medium High Very High Abandoned Jhum Non-Forest Grassland Sand Water Shadow Snow/Cloud Fig. 1. Biological richness in north-eastern India (IIRS, 2002) Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 122. 1212.4 Terrestrial Biomass/Carbon Estimation The global scientific community has put the study of global environmental changeas the highest research agenda. To resolve the major uncertainties in understanding thefunctioning of earth system in relation to climate change, the scientific community hasevolved International Geosphere Biosphere Programme. The National committee onIndian Geosphere Biosphere Programme has been entrusted the task to coordinate theresearch in the above area. Indian Space Research Organization has taken initiative toformulate ISRO Geosphere Biosphere Programme (ISRO-GBP) to study the climatechange using aerospace technology. The carbon pools and fluxes including vegetationcarbon, soil carbon, carbon exchange between forest/vegetation canopies and theatmosphere are the focus of this programme at IIRS since past one year. The study isexpected to throw reveal whether terrestrial systems, including forest and agro-ecosystems, are net source or sink of carbon.2.5 Protected Area Management Remote sensing provides state-of-art information on bio-physical parameters ofthe wildlife habitat, which significantly helps in the monitoring and evaluation of thehabitat for a particular wild animal. The USDA has developed more than 200 habitatmodels mainly for Amphibians. Alfred et al. (2001) used a remote sensing and GIS-based model to find out the habitat suitability for chinkara (Gazella bennetti) inRajasthan. Kushwaha and Roy (2002) have reviewed the contemporary research onwildlife habitat evaluation. A web-enabled wildlife information system (WILIS) is neededto enable the people interested in similar studies as well as for exchange of informationon wildlife-related issues. Time is now ripe to initiate action towards realization of suchan information-cum-decision support system. The wildlife Institute of India and IIRShave collaborated in various wildlife habitat studies since early eighties. A full-fledgedRS and GIS laboratory was created at WII with help from IIRS for operationalization ofwildlife habitat management studies. Fig. 2 illustrates the paradigm of wildlife habitatevaluation. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 123. 1222.6 Eco-development Planning Protected areas (PAs) in India are under tremendous pressure due to ever-growing needs of an over-growing human population. Ecological development of theareas surrounding the PAs is considered as one of the effective measures to reduce thedependability of the people on the PAs. World Bank in 1984 sanctioned an eco-development planning project for some PAs with guidelines to use remote sensing andGIS for database creation on PAs and surroundings. The IIRS participated in thisprogramme and created spatial database for Ranthambhore N.P. in Rajasthan. Thefield staff was specially trained by IIRS for continuity of the programme. Some stateshave taken keen interest in the programme and demonstrated encouraging results.Needless to mention that RS and GIS plays an important role to play in the eco-development planning.2.7 Forest Damage Detection Forests are vulnerable to the damage caused by the insects and pestsinfestation. Teak plantations are often infested by insect, which eats away its leaves.The defoliation reduces tree productivity and vigour. Teak defoliation is easilydiscernible on satellite imagery and hence, could be monitored. The coconut wiltdisease in Kerala was detected using colour infrared aerial photographs in earlyeighties. The borer infested sal forest in Doon valley could be identified and mapped forremedial action by IIRS recently. The spectral behaviour of the borer-infested sal forestis distinct from that of healthy one and hence, ease in interpretation, mapping andmonitoring.2.8 Forest Development Planning Degraded natural forests and forest plantations are developed to supply goodsand provide services to the society. This requires assessment of degraded forests for Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 124. 123their degradation status as well as identification of the areas for taking up gap planting,soil conservation etc. The site suitability analysis for forest plantations is a major activityin forestry. Remote sensing and GIS help tremendously in this task by generating inputdatabase for site suitability analysis. In one such study in Puruliya district carried out forthe Forest department of West Bengal, IIRS effectively demonstrated that remotesensing and GIS could greatly assist in scientific forest land use planning than withoutthem. GIS also helps in creation of different alternative management scenarios beforefinalization of the best suited one. The technology is also currently being used for CleanDevelopment Mechanism (CDM) project planning throughout the world. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 125. 124 Survey of Satellite Field India Imagery Survey ToposheetsContour Digitization Radiometric and Geometric Correction Vegetation Sampling Digital Elevation Model Visual Interpretation Habitat Use Data Aspect Map Ground Truthing Slope Map Forest Type Map Elevation map Statistical Data Settlement Map Analysis Road Map Forest Density Map Drainage Map Principal Component Analysis Cluster/ Spatial Modeling in GIS Correlation Analysis •Forest Type Map Analysis of Variance •Forest Density Map Bilinear Multiple Logistic •Slope Map Regression •Aspect Map •Elevation Map •Proximity to Settlement/Road •Proximity to Water Source Habitat Use by Wild Animal Habitat Suitability Map Fig. 2. Paradigm of habitat suitability evaluation Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 126. 1253. Time and Cost Advantage Not many studies have concentrated on the time and cost involvement in theremote sensing-based studies. In one study on the timber volume assessment in a12,000 km2 forest area in southern Karnataka involving satellite imagery and mediumand high resolution aerial photographs using the multi-phase sampling design, Köhl andKushwaha (1994) reported reduction in the cost by a factor of 3.5 and time by a factor of6. Another study on the wildlife habitat evaluation in Chilla Sanctuary of Rajaji N.P. inU.K. by Kushwaha et al. (2004) showed Rs. 2000/- as the cost of per km2 wildlife habitatevaluation. This included the cost of satellite data, data processing and analysis, salaryof the scientist for the project period, ground truth collection and field validation of themodel output. The cost, however, is expected to vary from place to place dependingupon the accessibility of the area. A cost-benefit analysis by ISRO Hq., Bangalore about20 years ago also concluded that remote sensing drastically reduces the time and costotherwise needed for ground-based surveys.4. Future Prospects The need for higher spatial, spectral and radiometric resolutions for forest typesand species (associations) has been emphasized over time. As time passes by, themapping and monitoring scenario is expected to be a lot better than ever before. Thespatial and radiometric resolutions have already improved considerably. The world nowis waiting for major improvements in spectral resolution. Some hyperspectral andnarrow band data from MODIS and ASTER sensors is already in store. Currently manyof the sensors provide spectral resolutions of the order of about 100 nm per band. The10 nm hyperspectral resolution will roughly mean 10 bands in each present day band.Sensing using continuous spectra is expected to help not only in better speciesidentification, association/formation and forest/vegetation type level mapping but alsoresult in higher accuracy timber volume and biomass estimations by highlighting thesubtle difference in the physiognomic properties of the vegetation. The hyperspectralimagery will also provide us an opportunity to understand the ecological state of the Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 127. 126biodiversity and the vegetation continuum across ecosystems, landscapes and biomesin an unprecedented manner. The radar polarimetry, interferometry and lidar-baseddigital terrain and surface models have already revolutionalized the process. The spatialdata generated using remote sensing and GIS have found increasing utility in climatemodeling and this trend is expected to continue further.ReferencesAlfred, J.R.B., Kankane, P.L., Kumar, A., Roy, P.S., Singh, S. and Verma, M. 2001. Habitat suitability analysis of chinkara, Gazella bennetti in Rajasthan- a remote sensing and GIS approach. Rec. Zool. Surv. India, Occasional Paper No. 189, 1- 73.Champion, H.G. and Seth, S.K. 1968. A Revised Survey of the Forest Types of India. Manager of Publications, Government of India, New Delhi.FSI, 2008. State of the Forest Report 2005. Forest Survey of India, Ministry of Environment and Forests, Government of India, Dehradun.IIRS, 2002. Biodiversity characterization in India at landscape level using remote sensing and geographic information system. Report, Indian Institute of Remote Sensing, Dehradun.Köhl, M. and Kushwaha, S.P.S. 1994. A four-phase sampling method for assessing standing volume using Landsat-TM data, aerial photography and field measurements. Commonwealth Forestry Review 73(1), 35-42.Kushwaha, S.P.S. and Roy, P.S. 2002. Geospatial technology for wildlife habitat evaluation. Tropical Ecology 43(1), 137-150. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 128. 127Kushwaha, S.P.S., Khan, A., Habib, Bilal, Quadri, Arshia and Singh, Aditya 2004. Evaluation of sambar and muntjak habitats using geostatistical modelling. Current Science 86(10), 1390-1400.NRSA, 1983. Forest cover mapping in India from satellite imagery for the periods 1972- 75 and 1980-82. Report, National Remote Sensing Agency, Hyderabad.Web Linkshttp://India.gov.inwww.fao.org/docrep/006www.fire.uni-freiburg.dewww.biodiversityhotspots.orgwww.envfor.nic.inwww.fsi.nic.inwww.wri.orgwww.landcover.org Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 129. 128 APPLICATIONS IN GEOSCIENCES P. K. Champtiray Geosciences Division1. Introduction The knowledge of Geosciences is very essential as it forms the basis for alldevelopmental activities. Geoscientific survey includes making of surfaceobservations, identifying relevant terrain features and delineating them suitably,drawing inferences about surface and subsurface conditions, and representing themin proper map forms for applied geoscientific investigations. Remote sensing is nowan important and powerful tool for geoscientific studies and mapping, best used inconjunction with field work. The remote sensing data permits the evaluation of regional geology, structuraltrends, lineaments, circular features, outcrop areas, landforms and alluvial / coveredareas for generating thematic maps for various geoscientific applications. Terrainmapping combining the findings by remote sensing as well as ground checks allowsfor better, updated map preparation in a "cost effective manner". In certain areasfairly accurate maps can be prepared almost twice as fast using remote sensingtechniques with selective ground checks in comparison to conventional methods ofsurveys. However, the amount of information extracted from remote sensing data isdirectly related to the field experience of the interpreter.2. Application Areas An overview of some of the major applications of remote sensing and GIS ingeoscientific investigations is highlighted here -2.1 Geological Mapping The interpretation of remote sensing data for geological mapping can beaccomplished by visual interpretation techniques with the understanding of spectral Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 130. 129property of earth/ rock materials, and their appearance on the images. Air andspaceborne remote sensing data have been widely used in different parts of theworld, for delineating broad categories of rock formations by analyzing their spectralproperties along with various geotechnical elements, namely landforms, vegetationcover, drainage, erosion pattern, and land use (Macias, 1995). Structural geological interpretation can be carried out by integratingknowledge on physiographic and tonal characteristics of the terrain elements,geomorphology and outcrop pattern of geological features. Such knowledge helps inextrapolation of remote sensing responses into meaningful 3-D structural model.Major structural features like fold, fault, and lineament may be identified and mappeddirectly based on their physiographic and tonal expressions or indirectly based on thealignment of the trend lines in litho formations, drainage/ridge lines, landforms, andvegetation pattern. With the introduction of high spectral and spatial resolution sensors(Multispectral Sensors namely, Landsat TM, ETM+, SPOT MX, IRS LISS-III, LISS-IV,ASTER, ALOS PRISM, AVNIR-2; high spatial resolution sensors namely SPOT PAN,IRS PAN, CARTOSAT-1 PAN, CARTOSAT -2 PAN, IKONOS, QuickBird), geologicalmapping has become much easier than before. Besides, there is a significantimprovement in digital image processing and enhancement techniques namely,colour transformation, image fusion, spatial filtering, principal component analysis,band ratioing, and construction of spectral index images which facilitate to highlightsubtle differences among the rock units and spatial contrast for mapping the structuralfeatures. With the advent of airborne and spaceborne hyperspectral remote sensing,hundreds of narrow spectral channels of an imaging spectrometer (e.g., 242 channelsin Hyperion covering visible and SWIR regions) can now map the earth surface over acontinuous reflectance spectrum. Imaging the earth materials within the diagnosticnarrow spectral absorption peaks of minerals and rocks makes it possible to identifyand map them more precisely than before. Recently, airborne and spacebornehyperspectral remote sensing has been found to be an important technique formineral abundance mapping (Hubbard et al., 2005). Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 131. 130 On the other hand, imaging radar provides important supplementaryinformation to optical remote sensing. Geological interpretation of radar imagery isbased on the analysis of surface morphology, landform and specific surface elementsviz., surface roughness, structures (macro and micro) and moisture-content. Nowdays, multi-frequency, multi-look angle and multi-polarization airborne andspaceborne SAR data are available which facilitate to understand and characterizeterrain and surface material properties in terms of radar backscattering strength andscattering mechanism. Multi-frequency and multi-polarization SAR data areparticularly useful for distinguishing between the rock types (Blom et al., 1987).2.2 Mineral Exploration The biggest challenge before the geoscientists today is to discover newmineral deposits, as most of the shallow deposits have either been located or arebeing exhausted (Rao, 1996). The key to locate the favourable zones lies inunderstanding the geological processes involved in the formation of the mineraldeposits to help formulate an appropriate exploration strategy, including role of RSand GIS techniques in providing information about the geologic controls and surfaceguides. A known mineral deposit forms the control area for this purpose, and theexploration strategy is extended from the known area to the unknown areas. AlthoughRS and GIS techniques are restricted to the initial stages of mineral explorationprogrammes, but they provide insight into understanding the controls of mineralizationand first-hand information for exploring the unexplored areas for possible presence ofeconomically viable deposits where further detailed ground-based geological,geophysical and geochemical surveys, are to be carried out, followed by drilling forproving the deposit. Satellite imagery are typically used for identifying and mapping key variables,referred as guides e.g. (1) lithologic guide, (2) structural guide, (3) geomorphic orphysiographic guide, (4) mineral alteration guide, and (5) geo-botanical guide. Amongthese guides, RS data have unique advantage in mapping alteration minerals,especially clay minerals and iron-oxides, which are associated with hydrothermal andsupergene enrichment type of mineral deposits. RS data also have promise for Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 132. 131detecting and mapping geo-botanical indicators, but the technique has not yet beenoperationalised. The strength of RS data in mapping the lithologic, geomorphic andstructural guides is already proven beyond doubt for more than four decades. The air-borne and space-borne geophysical and geochemical data (magneticand gamma ray spectrometry) are also used to obtain the subsurface informationwhich is then coupled with surface/near-surface information derived fromconventional RS data and other collateral data in the GIS domain with appropriategeospatial models with an emphasis on spatial segmentation of the area in terms offavourability of mineral occurrence. National Remote Sensing Agency (NRSA) hascarried out airborne aeromagnetic and gamma ray spectrometry surveys, includingprocessing of data and preparation of final maps, for different core geologicalorganizations, viz. Geological Survey of India (GSI), Oil and Natural Gas Corporation(ONGC), Directorate of Hydrocarbons (DGH) and Atomic Minerals Directorate forExploration and Research (AMD). The high quality database generated in suchcampaigns is being used for planning the exploration programmes. The first major study in India where RS data have been integrated withconventionally acquired ancillary data was undertaken jointly by the GSI and Dept. ofSpace under the project “Vasundhara.” GSI, AMD and ONGC are routinely using theRS and GIS tools in their exploration programmes. NRSA in collaboration with AMDand State Geology and Mining Departments have also carried out certain pilot studiesfor locating favourable areas for occurrence of base metals, atomic minerals,kimberlite pipes and coal in parts of Rajasthan, Madhya Pradesh and AndhraPradesh. The results of these studies have been quite encouraging. In the context of management of mineral resources, other applications of RSdata include identification, mapping and monitoring of illegal mining area, addressingthe geo-environmental issues associate with mining, assessing the mining hazards,such as subsidence, etc.2.3 Ground Water The major applications of RS and GIS in ground water development andmanagement are – (1) exploration and assessment of ground water resources, (2) Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 133. 132estimation of natural recharge distribution, (3) selection of artificial recharge sites, (4)GIS-based subsurface flow and pollution modeling, (5) ground water pollution hazardassessment and protection planning, and (6) hydro-geologic data analysis andprocess monitoring. Among these applications, RS and GIS techniques have beenmainly used for ground water exploration (Waters et al., 1990), which includesqualitative characterization of the hydro-geological mapping units and detection ofrelevant specific features (Meijerink, 1996). This has been demonstrated to be cost-effective (Meijerink, 1996) in terms of improving success rate of drilling, and inreducing time and cost of geophysical and hydro-geological surveys in different partsof the world. There are basically two types of remote sensing based approach aregenerally used for ground water exploration (Waters et al., 1990). The first is appliedto hard rock aquifers to map zones of secondary permeability, especially lineamentsthat are often positively correlated with well yields. The second approach deals withintegration of remotely sensed data with other ancillary information to create hydro-geological/ hydro-geomorphological maps for ground water exploration, and areapplicable to all kinds of geologic setting. In one of the unique studies being carried out by the Department of Space(DOS) (e.g. DOS, 1988; NRSA, 2008) under Rajiv Gandhi National Drinking WaterMission project, ground water prospects maps have been prepared on 1:50,000 scalefor ten States (Andhra Pradesh, Chattisgarh, Gujarat, Himachal Pradesh, Jharkhand,Karnataka, Kerala, Madhya Pradesh, Orissa and Rajasthan). Mapping work is inprogress in another six States. These maps provide scientific database to meet dualobjectives: (1) to map prospective ground water zones and (2) to select tentative sitesfor artificial recharge structures. The feedback received from different States inutilization of these maps, indicate increase in success rate of wells.2.4 Geo-Environmental Studies Remote sensing technique has been found to have immense potential forgeo-environmental studies. Because of the repetitive coverage, satellite-basedremote sensing is ideally suited for geo-environmental monitoring and environmental Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 134. 133impact assessment (EIA) at a regular interval. Various earth processes andanthropogenic activities causing changes in the environmental condition over theearth surface fall under the clan of geo-environmental studies. Among variousgeomorphological processes operating over the earth surface, fluvial and coastalprocesses appeared to be highly dynamic which lead to fluvial and coastal regionsmore prone to changes. The changes in drainage network, coastline configuration,and spatial disposition of the landforms can be mapped efficiently from multi-temporalremote sensing data. Multi-temporal satellite-based remote sensing data wereeffectively used by the previous workers for monitoring the dynamics of fluvial andcoastal landforms. Remote sensing in thermal region has been found to be an importanttechnique for detection and delineation of high temperature objects like coal fire andactive volcano (Zhang et al., 2004). Satellite-based thermal IR data has the limitationof coarser spatial resolution (Landsat TM: 120m, ASTER: 90m, Landsat ETM+: 60m)whereas airborne thermal IR data may be acquired up to a spatial resolution of 1m.Airborne thermal IR data has been used by a number of workers for mapping coal fireaffected areas at larger scale (Mukherjee et al., 1991; Bhattacharya and Reddy,1992). Rapid improvement in the processing and analysis of thermal and short-waveinfra-red data has taken place recently. Dynamics of coal fire can be studied usingmulti-temporal thermal IR data aided by the knowledge of 3-d disposition of the coalseams and occurrences of the discontinuities across the coal seams (Chatterjee etal., 2007a). Recently, differential interferometric SAR (D-InSAR) potentially offers apowerful and cost-effective tool for measuring and monitoring land subsidencephenomenon. D-InSAR provides a deformation image on a pixel-by-pixel basis overan area of thousands of square kilometers. The phenomenon of land subsidenceresulting from heavy withdrawal of ground water in Kolkata City, India, has beendetected and the rate of subsidence to the tune of 5-6.5 mm/year has been measuredsuccessfully by spaceborne D-InSAR technique. In the coal fields, the problem of landsubsidence is more pronounced due to underground mining and sub-surface coal firepropagation. In Jharia Coalfield, an integrated approach using D-InSAR, GPS andprecision leveling techniques has been adopted to monitor and model land Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 135. 134subsidence phenomenon in relation to underground mining and subsurface coal firepropagation.2.5 Geo-Hazards Landslide, earthquake and volcanism are the major geological hazardscausing destruction to the human population, to the built-up environment and to theeco-system. Remote sensing technique plays a significant role in landslideinvestigations especially for carrying out landslide inventory. Recently available very-high-resolution satellite imageries (QuickBird, IKONOS, and CARTOSAT 1 & 2) haveimmense potential for detailed landslide mapping. Other approaches include shadedrelief images produced from LiDAR and InSAR DEM. In recent years there has beena significant progress on mapping, monitoring and modeling of landslide hazardsusing Earth Observation (EO) techniques and GIS based modeling. Landslide proneareas can be identified by landslide hazard zonation which refers to division of landsinto homogeneous units and their ranking according to the probability of occurrenceof landslides. Such landslide hazard maps can be generated by integrating terrainfactor maps derived from aerospace data with selective ground truths, under GISenvironment using geo-statistical and knowledge based approaches. Dept. of Space (DOS) has prepared an atlas showing various landslidehazard conditions along tourist and pilgrimage route in the Himalayas in the year2000-2001. The maps thus prepared are being validated regularly. The occurrence ofUttarkashi landslide in 2003, in an already demarcated high hazard zone validates theefficacy of the hazard zonation map. In recent times, there has been a significant progress in the application ofearth observation systems for earthquake studies, mainly for damage assessment,surface deformation, seismic micro-zonation and monitoring the subtle neo-tectonicchanges. Aerospace data have been widely used in different parts of the world bymany workers for damage assessment (Yamajaki et al., 1998). Similar attempts havealso been made in different parts of India by various workers to assess the changesin terrain conditions due to the medium to high magnitude earthquakes occurred inthe last two decades. Currently SAR Interferometry techniques are being used to Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 136. 135measure the ground deformation. This was first demonstrated during 7.3 magnitudeLanders earthquake of 28th June 1992, that ruptured over 85 km long complex faultsystem in Mojave desert of California (Massonnet et al., 1993). Active volcanoes pose a significant danger to mankind, as an estimated 10%of the world’s population lives in close proximity to them (Peterson 1986). In principle,satellite can record the observation of volcanic activity any where in the world. In aninnovative case study, has demonstrated how ERS 1&2 SAR data can be applied asan operational tool for monitoring of sub-glacial volcanic eruptions and their adverseeffects in Iceland. In general, there are two ways in which remote sensing cancontribute information on volcanic eruptions namely, plume observation and thermalmonitoring.3. Conclusions Remote sensing and GIS can be considered as powerful tools forrepresentation and analysis of various spatial and non-spatial features associatedwith geological studies. The constant improvements in the spatial, spectral andtemporal resolutions hold lot of promises for geoscientific community in the comingyears. The future generation of satellites like ISRO Resourcesat -2 (Multispectralmission) RISAT (Radar mission) for land application and oceansat-2 for oceanapplications will contribute to the better understanding of earth system sciences. Thenew emerging trends in sensor system like multispectral radiometers, multipolarization instruments, LiDAR, Radar altimeters and scatterometers coupled withnew technologies in data acquisition and processing strategies will help in betterretrieval of geophysical parameters and new insight to the geological processes.ReferencesBlom, R.G., Scheck, L.R., and Alley, R.E. 1987. What are the best radar wavelengths, incidence angles, and polarizations for discriminating among lava flows and sedimentary rocks? A statistical approach. IEEE Transaction on Geoscience and Remote Sensing, 25(2), 774-789. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 137. 136Bhattacharya, A. and Reddy, C.S.S. 1992. Airborne scanner survey and data analysis for underground and surface coal mine fire detection in Jharia Coalfield, Bihar. Report from the Geosciences Division Applications Group, National Remote Sensing Agency, Hyderabad, India, Report No. NRSA-AG- GD-TR-2/92.Chatterjee, R.S., Wahiduzzaman, Md.,Shah, A., Raju, E.V.R., Lakhera, R.C., and Dadhwal, V.K. 2007. Dynamics of coal fire in Jharia Coalfield, Jharkhand, India during the 1990s as observed from Space. Current Science, 92(1), 61- 68.DOS, 1988. Manual for hydro-geomorphological mapping for Drinking Water Mission. Unpublished Report, Dept. of Space (DOS)/ Indian Space Research Organization (ISRO), Govt. of India.Hubbard, B.E., Crowley, J.K. 2005. Mineral mapping on the Chilean-Bolivian Alte Plano using co-orbital ALI, ASTER and Hyperion imagery: Data dimensionality issues and solutions. Remote Sensing of Environment, 99, 173-186.Macias, L.F1995. Remote Sensing of Mafic – Ultramafic rocks; Examples from Australian Precambrian terrain. J.of Australian Geol Geophys, Vol 16. PP 163-171Massonnet, D., Rossi, M., Carmona, C., Adaragna, F., Peltzer, G., Feigl, K. and Rabaute, T., 1993. The displacement field of the Landers earthquake mapped by radar interferometry. Nature, 364, pp 138-142.Meijerink, A.M.J. 1996. Remote sensing applications to hydrology: groundwater. Hydrol. Sci., Vol. 41, pp. 549–561.Mukherjee, T.K., Badyopadhyay, T.K., and Pande, S.K., 1991. Detection and delineation of depth of subsurface coalmine fires based on an airborne Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 138. 137 multispectral scanner survey in a part of the Jharia Coalfield, India. Photogrammetric Engineering and Remote Sensing, 57(9), 1203-1207.NRSA 2008. Manual on ground water prospects mapping using remote sensing and geographic information system. Document No. NRSA/RS&GIS-AA/ERG/HGD/ TECHMAN/JAN), National Remote Sensing Agency (NRSA), Hyderabad, India.Peterson, D.W., 1986. Volcanoes: tectonic setting and impact on society, in Studies in Geophysics: Active tectonics, Panel on active tectonics, National Academy press, Washington D.C., pp. 1421-1422.Rao, T.M. 1996, Geophysics in Mineral Exploration. Proceedings of the Second International Seminar and exhibition on Geophysics Beyond 2000, Hyderabad, 19-21, November 1996(organized by Association of Exploration Geophysicist), pp. 173-180.Sophocleous, M. (2004), Global and regional water availability and demand: prospects for the future. Natural Resources Research, Vol. 13, pp. 61-75.Waters, P., Greenbaum, D., Smart, P.L. and Osmaston, H. 1990. Applications of remote sensing to groundwater hydrology. Remote Sensing Rev., Vol. 4, pp. 223–264.Yamazaki, F., Matsuoka, M., Ogawa, N., Hasegawa, H. and Aoki, H.,1998. Airborne and Satellite Remote Sensing Technologies for Gathering Damage Information, Proceedings of Multi-lateral Workshop on Development of Earthquake and TsunamiZhang, J., Wagner, W., Prakash, A., Mehl, H., Voigt, S., 2004. Detection of coal fires using remote sensing techniques. International Journal of Remote Sensing, 25(16), 3193-3220. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 139. 138Web Linkshttp://geology.usgs.gov/index.htmhttp://www.gisdevelopment.net/application/geology/mineral/index.htmhttp://www.itc.nl/ilwis/Applications/application14.asp Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 140. 140 APPLICATIONS IN HUMAN SETTLEMENT STUDIES AND MANAGEMENT B.S. Sokhi Human Settlement Analysis Division1. Urban Management Issues Indian urban population of 285 million as per 2001 census is more than the totalpopulation of many European nations put together. Never the less, living environment ofour cities is far from satisfactory by any standard. In 1901, less than 11 per cent of thepopulation of India lived in urban areas. By 2001, this increased to 27.78 per cent andby 2051, it is expected to rise to 47.50 per cent of the total. From Table 1, it is clear thatemerging canvas is towards an integrated urban-rural continuum as the key for abalanced urbanization. By 2051, it is expected that around 820 million people wouldreside in about just 6500 urban agglomerations, where as, over 912 million peoplewould be spread over nearly 570,000 rural settlements.Table 1: Growth in number of urban settlements (1901-2051) Census Urban Percentage of Number of urban Number of Rural Year Population Urban from total settlements/ Settlements (in million) population Agglomerations (in million) 1901 26 11.00 1827 0.59 1951 62 17.29 2845 0.58 2001 285 27.78 3969 0.58 2051* 820 47.50 6500 0.57 (Source: Census of India, * Projected) The trend indicates that settlements and their outward spread would continueeating into the lands required for agriculture, forest cover and even wetlands and by2051, it is forecasted that a further 10 million ha of good agricultural land would be lost Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 141. 140to such expansion and associated activities. Accordingly, a decreased acreage of theagricultural land would be available for food production after protecting forest lands,water courses and wetlands. The proposed special economic zones (SEZs) are atypical example of this scenario. Also, it has to be underlined, that the number of urbansettlements has not increased in proportion to increase in urban population. Therefore,most urban settlements would get larger both through vertical and guarded horizontalexpansions. By 2051, India would be the most populous country in the world with over1.70 billion people on fixed quantum of land. By then, the land : man ratio would drop to0.19 hectares per capita (0.95 in China) against 1.28 in 1901 and 0.32 in 2001 (1.33 inChina). Land is, therefore, a scarce and diminishing resource.2. Issues in Human Settlement Management • Population growth and population movement • Regional imbalances • Urban growth and sustainable use of space • Land cover changes • Provision of basic services • Cadastral information • Transparency in governance3. Information Need and Mapping Requirements The need of the hour is to generate digital database of very sector of economy,demography and maps of natural as well as man-made resources at two levels – atnational or state level for making policies and programmes and at parcel level forimplementation of policies and programmes. Land use/Land cover maps, urban growthand land use changes are not only indicators to analysis the socio-economic changes inthe society. Conversion of land records into a digital mode would help to enhance therevenue generation, transparency in the land-dealings and taxation. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 142. 140 Each government has a unique set of circumstances that result in differentmanagement responses to improve community services. An important factor inimproving the delivery of customer service in through the investment in spatialinformation system known as Geographic Information System (GIS), Spatial informationis widely used for tax collection, management of infrastructure, town-planning schemeetc. Out of the prerequisites for spatial information management in government involvesthe establishment and maintenance of a database of relevant information in digitalformat. Access to reliable and up-to-date information reduces the uncertainty planningand management by helping identify, model and analyze situations and issues spatially.The value of the information and the effectiveness of the decision-making and planningprocesses are closely related to the quality and completeness of the information or thechallenges facing government is not whether to use spatial data but how best to usespatial data to enhance operational activities and community services for completetransparency. Therefore, low resolution or coarse resolution data like IRS -1C WiFS andIRS-P6 AWiFS are sufficient, but at implementation stage where very high accuracy isneeded high resolution data is required, for example, Cartosat, IKONOS, Quickbird.4. Future Prospects Future of human settlement studies and provision of facilities and theirmanagement lies with Geographic Information System through Mobile Mapping System.Every city/town should be linked through the net so that every citizen can getinformation about their administration and management technique, result andconsequences of any planning policy as well as increasing the transparency of everyaction of the Town Administrator. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 143. 140ReferencesState of World Population, 2007. Unleashing the Potential of Urban Growth, UNPF, United Nations, 2007.Web Linkswww.censusofindia.gov.inwww.mapsofindia.comwww.gisdevelopment.net/application/urban/overview/index.htmwww.unrisd.orgwww.unfpa.org/swp/2007 Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 144. 143 APPLICATIONS IN MARINE SCIENCES D. Mitra Marine Science Division1. Introduction The coastal zone is the interface where the land meets the ocean, encompassingshoreline environments as well as adjacent coastal water. Its components can includeriver deltas, coastal plains, wetlands, beaches and dunes, reefs, mangrove forests,lagoons, and other coastal features. The limit of coastal zone is often arbitrarily defined,differing widely among nations, and are often based on jurisdictional limits ordemarcated by reasons of administrative ease. It has often been argued the coastalzone should include the land area from the watershed to the sea, which theoreticallywould make sense, as this is the zone where biophysical interactions are strongest. Forpractical planning purposes, the coastal zone is a special area, endowed with specialcharacteristics, whose boundaries are often determined by the specific problems to betackled. Its characteristics are: • It is a dynamic area with frequently changing biological, chemical, and geologic attributes. • It includes highly productive and biologically diverse ecosystems that offer crucial nursery habitats for many reasons. • Coastal zone features such as coral reefs, mangrove forests, and beach and dune systems serve as critical natural defenses against storms, flooding and erosion. • Coastal ecosystems may act to moderate the impacts of pollution originating from land (for example, wetlands absorbing excess nutrients, sediments, human waste). • The coast attracts vast human settlements due to its proximity to ocean’s living and nonliving resources, as well as marine transportation and recreation. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 145. 144 3. Problems and Issues in Coastal Developments The coastal zones throughout the world are very precious and delicate ecologicalenvironments, both for man and for nature. Since they have often fertile soils, and are infavor by man through their location near the sea (ports, fisheries), the pressure on theyet undisturbed coastal zones is great. In addition, the coastal zones already inhabitedand cultivated encounter often difficulties caused by the complex nature of theenvironment and conflicts of interest between the different inhabitants and users. Thereare many coastal activities laying their own claims to the coastal zone. Main activitiesare transport, aquaculture, fishery, agriculture, forestry, human settlement, mining,recreation and tourism. For guiding and monitoring, the development of activities andtheir effects on the coastal zone, planning and management is needed to sustaincoastal resources. Some major problems encountered in coastal developments are: • The deterioration of coastal resources by destruction, over-exploitation and un- economical use. • Development activities along the coast, which create many adverse affects on coastal resources. • Upland development activities having negative impact upon the downstream coastal areas. • Sea level rise and land fall resulting in inundation of coastal lowlands.3. Primary Applications of Remote Sensing for Coastal Zone Study Remote Sensing is used to address a wide variety of management and scientificissues in the coastal zone. Due to its repetitive, multispectral and synoptic nature,remote sensing data has proved to be extremely useful in providing multi-spectralinformation on various components of the coastal environment, viz. Coastal wetlandconditions, mangrove and coral reef degradation, coastal landforms and shorelinechanges, tidal boundaries, brackish water areas, suspended sediment dynamics,coastal currents, air pollution etc. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 146. 145 Different wavebands of light penetrate water to varying degrees; red lightattenuates rapidly in water and does not penetrate deeper than 5 m or so, whereas bluelight penetrates much further (15 m), and in clear water, the seabed will reflect enoughlight to be detected by a satellite sensor even when the depth of water approaches 30m. The green light penetrates as far as 15 m in clear waters. NIR (0.7- 0.8 μm)penetrates to a maximum depth of 0.5 m and IR (0.8- 1.1μm) is fully absorbed (Mumbyand Edwards 2000). Importance of remotely sensed data for inventorying, mapping, monitoring ofcoastal zone was realized early. Due to its repetitive, multi-spectral and synoptic nature,remote sensing data has proved to be extremely useful in providing information onvarious components of the coastal environment, viz., coastal wetland conditions,mangroves and coral reefs degradation, coastal landforms and shoreline changes, tidalboundaries, suspended sediments dynamics, coastal currents, etc. IRS-1C/1D has LISSIII and PAN which have proved to be extremely useful in the discrimination of dominantmangrove community zones, mapping details of ports and harbour areas as well as inassessing damage due to cyclones in the coastal areas, delineation of coastalregulation zone, shoreline changes, etc. (Nayak et. al., 1996). Erosion/accretion andShoreline changes and can be seen from the Fig. 1. Fig. 1- Shoreline changes in a part of Khambhat, Gujarat. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 147. 1464. Ocean Colour Phytoplankton forms the first link in the ocean food chain and gives an indicationabout the standing stock of green biomass, which helps in predicting the third levelproductivity. The varying levels of phytoplankton pigment (chlorophyll-a) and otherconstituents impart colour varying from bluish to greenish to brownish. Hence, asatellite-based observing system having narrow spectral bands in the visible region isproviding better insight into our understanding of the ocean productivity. It will alsoprovide better understanding of the role played by ocean productivity in the uptake ofcarbon dioxide from atmosphere. IRS P4 OCM has been providing ocean colour dataevery two days for the Indian regions (Fig. 2). Various models are under development toestimate primary productivity Figure 2 Phytoplankton map of part of East Coast of India Fig. 2. Ocean colour data from IRS P4 OCM.5. Bathymetry The knowledge about depth values is important for coastal zone managers andnavigators, for exploration and exploitation of non-living and living resources, operations Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 148. 147on engineering structures and ocean circulation studies. Tides and currents constantlymodify the submerged land-mass which prove hazardous for navigators. Updating thebathymetric charts by conventional methods is time consuming and expensive. Remotesensing is relatively cheap and fast method for periodically updating navigational routes.It is also useful technique for detecting new reefs and shoals. The water depth thatpermits detection of the bottom depends upon water colour, turbidity, bottom reflectanceand intensity of incident light. The principal advantage of satellite data is the repetitivecoverage. IRS data can be used for updating medium and small scales nautical charts(Fig. 3). Techniques have been developed to retrieve depth values using high-resolutionsatellite data in shallow parts of sea and Synthetic Aperture Radar (SAR) image data incoastal regions. It was observed that inferred depths vary about 10-15 % as comparedto published charts. However, these methods are not routinely used for updatingnavigational charts. Fig. 3. Bathymetry predictions through satellite data in parts of Goa Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 149. 1486. Tsunami Warning System in India India unveiled its own tsunami early warning system put together by its scientists,three years after being caught off guard by the giant killer waves that wreaked havocalong the countrys southern coastline. The tsunami warning centre, which has takenshape at the Indian National Centre for Ocean Information Services (INCOIS), will issuealerts for the killer waves within 30 minutes of an earthquake. The Centre will generateand give timely advisories to the Ministry of Home Affairs for dissemination to the publicfor which a satellite-based virtual private network for disaster management support hasbeen established.7. Potential Fishing Zones India has high potential for marine fisheries development. The present fishproduction in the country is mainly from the coastal waters (up to depth of 50 m). Theremote sensing satellites with their capability to monitor large spatial areas over oceanson a routine- basis have proven to be of substantial economic benefit, particularly for anation like India having a long coastline and extensive EEZ. The AVHRR data fromNOAA satellites are being used in India to determine SST at 1.1 km2 pixel level overIndian oceanic region on daily and weekly (composite) basis by the National RemoteSensing Centre, Hyderabad. The potential Fishing Zone (PFZ) maps are generatedbased on oceanographic features such as thermal boundaries, fronts, eddies, rings,gyres, meanders and upwelling regions visible on 3-4 days composite map of SST. Theextensive validation of these SST estimates with data collected by researchvessels/drifting buoys has shown an accuracy of measurement of ± 0.7o. The majorinadequacy of thermal infrared sensors is that it will measure ocean surfacetemperature only through a cloud-free atmosphere and strictly, the ocean skintemperature. It was observed that such forecast are 70-90 per cent accurate results in70-100 per cent increase in catch, both pelagic and demersal (Solanki et al., 2003). Thebenefit to cost ratio has increased from 1.3 to 2.1 for those fishermen who have usedsatellite-based fishery forecast. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 150. 149 The technique developed for the PFZ (potential fishing zone) forecast (up to 2–3days in advance), which combines chlorophyll information from OCM and SST fromNOAA–AVHRR has been validated with a number of ship campaigns in the Indianwaters. Results have shown 70–90% success in PFZ identification. Ocean colour dataconjunctively with SST are operationally used to prepare fishery prospect charts to helpfishermen. The sensor characteristic of OCM was designed by keeping in mind therequirements of applications like PFZ, scale features of eddies, sediment transport nearports harbours, and dispersal of industrial pollutants in the coastal waters, shorelinechanges, etc. High radiometric accuracy (12 bit), eight spectral channels (bandwidth~20 nm) and spatial resolution of ~350 m with the repetivity of two days was designedto meet the above goals. Presently, INCOIS in Hyderabad is engaged in producing thePFZ maps and distribute to fishermen. Fig. 4. Potential fishing zone map derived from satellite data. Status on utilization of remote sensing data for coastal studies in India is given inTable 1. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 151. 150Table 1: Status on utilization of remote sensing data for coastal studies in IndiaResources/Parameters/Processes Remote Sensing Status compliancesMangrove, Coral reefs, Salt pans, Mapping and monitoring in Operational usingAquaculture, wetlands, Other different scale. high resolutionscoastal inland resources multispectral sensors data from IRS series.Fisheries Forecasting and Semi operational monitoring with NOAA and IRS-P4Mineral and Energy Exploration and Monitoring R & D stage with existing RS dataCoastal Geomorphology and Mapping and Monitoring in Operational Highshoreline changes different scales Resolution Data from IRS SeriesSST, Winds, Waves, Water Fishery forecasting, Operational withvapour content etc. Monsoon, Ocean and IRS –P4 and other atmospheric studies foreign satellitesUpwelling, Eddies, Gyres etc Fishery and Ocean Operational with Dynamics studies IRS-P4 and othersCoastal Regulation Zone Mapping and monitoring in Operational using 1:50,000 and 1:25,000 IRS 1C and IRS scale 1DSuspended sediment Mapping and Monitoring Semi operationalConcentration with IRS –P4Oil Slicks Mapping and monitoring Semi operational with IRS series and other foreign satellites Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 152. 151Chlorophyll concentration Mapping and monitoring Semi operational with IRS P4Currents and Surface Circulation Mapping and Monitoring Semi operationalPatterns with IRS series and other foreign satellites8. Major Projects carried out along the Indian Coast using Remote Sensing Data With the availability of Landsat sensors data in India, Government of Indiainitiated a major programme for mapping of coastal resources and for sustainableutilization. With the launch of IRS satellites coastal zone mapping and monitoring atNational Level became an imperative for planning and administrative purposes. SpaceApplication Centre (SAC) in association with Regional Remote Sensing Service Centresand State Remote Sensing Application Centres carried out several projects as follows: 1. Coastal zone mapping for the entire country in 1:250,000 and 1:50,000 scale 2. Wetland Mapping in 1:250,000 scale for the entire country and 1:50,000 scale in selected areas 3. Coral reefs and Mangroves area mapping in 1:50,000 scale 4. Shoreline changes for the entire Indian coast in 1:250,000 scale and 1:50,000 scale in selected areas 5. Coastal land form studies in 1:250,000 for the entire Indian coast and 1:50,000 in selected areas 6. Lagoonal/Lake studies in 1:50,000 scale 7. Mapping of Coastal Regulation Zone (CRZ) in 1:25,000 scale for the entire Indian Coast using high resolution data from IRS and SPOT 8. Integrated Coastal Management studies 9. Identification of suitable sites for brackish water aquaculture Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 153. 1529. Future Prospect and Challenges for remote sensing for coastal zone study • improving the accuracy, resolution, timeliness, and ease-of-use of remotely sensed data; • enhancing "rapid response" capabilities by providing high-resolution data of affected areas immediately following natural and human-induced disasters; • improving the delivery of remotely sensed data via the Internet, so that users can more easily find and retrieve the exact data and information they need; • developing ways to fuse data from multiple sensors, to allow multiple projects and programs to improve the quantity and quality of information available to the public; • maintaining communications with the many users of various remotely sensed data, to support a wide variety of specific applications; • using new remote sensing technologies to collect data in a more efficient and cost-effective manner so that accurate, current data are available for larger geographic areas; and • improving software so that remotely sensed data can be quickly and easily processed and analyzed to support various programs and simultaneously yield information needed by professionals and decision makers.ReferencesNayak, S. 1996. Monitoring of coastal environment of India using satellite data. Science, Technology & Development, Special Issue on The Environment and Development in India (Ed. Dipak Ghosh and Nitai Kundu) 14 : 100-120. Frank Cass & Co. Ltd. Essex, U.K.Mumby and Edwards, 2000. RS and GIS application for Tropical coastal zone management. UNESCO Publications. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 154. 153Solanki, H. U., Dwivedi, R. M. and Nayak, S. 1998b. Relationship between IRS MOS-B derived chlorophyll and NOAA AVHRR SST : a case study in the NW Arabian sea, India. In Proc. 2nd Inter. Workshop on MOS-IRS and Ocean Colour. Institute of Space Sensor Technology, Berlin, Germany. pp. 438-442.Web Linkshttp://www.nesdis.noaa.gov/http://www.ioccg.org/http://www.nodc.noaa.gov/SatelliteData/http://www.environment.sa.gov.au/coasts/management.htmlhttp://shorelines.dnr.state.md.us/coastalProcesses.asphttp://www.oceanexplorer.noaa.gov/technology/tools/mapping/mapping.html Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 155. 154 Applications in Water Resources Dr. S.P. Aggarwal Water Resources Division1. Management Issues Water is life, in all forms and shapes. This basic yet profound truth eludedmany of us in the second half of the 20th century. Water professionals and scientistsaround the world are ringing the alarming bells of an impending water crisis. Yetattempts to address some of the issues or to offer partial solutions met with limitedsuccess. The ever-growing population and concomitant expansion of agriculture andindustry have placed increasing demand on the limited water resources. Some of theimportant issues related to water resources, viz. challenges in water sector in the formof declining per capita availability of water, deterioration in quality, over-exploitation ofground water resources leading to lowering of water table in some areas, cost and timeoverruns in completion of irrigation and multipurpose projects and poor maintenance ofthe existing system. Further, natural disasters related to water i.e. floods and droughtare also required to be addressed in proper perspective. It remains a fact that climatechange and its effects are important issues such as impact on water resources water isalso to be addressed in using the technological advances. The average annual rainfall in the country is about 1170 mm with an equivalentvolume of rainwater of about 4000 billion cubic meter (BCM). After accounting for thelosses for evaporation and evapotranspiration, the average annual water availability hasbeen estimated to be about 1869 BCM. However, there is a very high degree ofvariability both in space and time. Owing to topographical constraints and hydrologicalfeatures, only about 1123 BCM has been assessed as utilizable which comprises 690BCM of surface water and about 423 BCM of replenishible ground water. As per theassessment made by the Standing Sub-Committee of the Ministry of Water Resources,the water requirement could be of the order of 1447 BCM by the year 2050 when thepopulation is expected to stabilize. The requirement can be reduced with adoption of Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 156. 155better management practices through improvement in efficiency. The NationalCommission for Integrated Water Resources Development has assessed that withintroduction of better management practice the ultimate water requirement would be ofthe order of 1180 BCM by the year 2050. Ministry of Water Resources Govt. of India feels that appropriate WaterResources Information System should be put in place at the earliest as this will helpconsiderably in better monitoring (http://www.indiawaterportal.org). Water ResourcesInformation system is possible only with the help of geo-information technology such as(remote sensing, GIS and GPS). The information available such as surface waterobservations (gauge and discharge) and their locations, inflows and out flows into thereservoirs etc, location and data of observation wells for water level fluctuations, hydro-meteorological data etc. should be put in a customized packages, so that the concerndepartments can use this information for the relevant analysis. The per capita storagecapacity created in India as a whole is of the order of 207 cubic meters only which isrelatively quite low compared to many countries viz. Russia (6103 Cum3), Australia(4733 Cum3), Brazil (3145 Cum3), Turkey (1739 Cum3), China (1111 Cum3) and SouthAfrica (753 Cum3). A properly planned storage for water will definitely help in mitigatingthe effects of flood and drought as well. We have also to approach rainwater harvestingin a mission mode. Before operational applications are discussed, introduction of thebasic terminology of hydrology, general circulation of the water is shown in Fig. 1. Fig. 1. The global hydrologic cycle Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 157. 1561.1 Hydrological CycleThe interdependence and continuous movement of all forms of water on the earth andin the atmosphere is known as hydrologic cycle. The hydrologic cycle can also bedefined as the processes and pathways involved in the circulation of water from landand water bodies (sea, rivers, lakes etc.) to the atmosphere and back again.1.2 Operational Use of RS and GIS All the studies related to water resources are confined to this hydrological cycleonly. List of studies that have been operationalised using remote sensing, GIS, GPSare, Surface water inventory, Watershed delineation and characterization, changedetection and monitoring, Flood plain/prone area mapping & flood risk zoning,Identifying, Inventory and assessment of irrigated crop and performance evaluation, andReservoir sedimentation. A brief description of the above applications are given here.1.2.1 Surface water inventory The majority of radiant flux incident upon water is either absorbed or transmittedand little is reflected. This results in sharp contrast between any water body andsurrounding land surface. Suspended sediment can be easily confused with shallow(but clear) water, since these two phenomena appear very similar, which need to beclarified by ground truth only.1.2.2 Watershed delineation and characterization, change detection and monitoring Inappropriate land use practices in the upstream catchment leads to acceleratedsoil erosion and consequent silting up of reservoirs. Watershed management in thus anintegral part of any water resources project. Space borne multispectral data have beenused to generate baseline information on various natural resources, namely soils, forest Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 158. 157cover, surface water, ground water and land use/ land cover and subsequent integrationof such information with slope and socio-economic data in a geographic informationsystem (GIS) to generate locale-specific prescription for sustainable development ofland and water resources development on a watershed basis. Fig. 2 shows IIRS P-6LISSIII satellite image and surface water body extracted. Fig. 2. IIRS P6 LISS-III satellite image (left) and surface water body extracted (right). The study covering around 84 Mha and spread over 175 districts, which includes247 watersheds has been carried out by the Department of Space, Govt. of India undera national level project titled “Integrated Mission for Sustainable Development (IMSD)”.Implementation of appropriate rain water harvesting structures in selected watershedsunder this programme has demonstrated the significant benefits by way of increasedground water recharge and agricultural development of once barren areas. Multi-yearsatellite data is also used to monitor the impact of the implementation of watershedmanagement programmes Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 159. 158Fig. 3. Input and output of IMSD project in Upper Hatni watershed, Jhabua district, M.P.1.2.3 Flood plain/ prone area mapping and flood risk zoning India is one among the disaster prone geographical zone of the world and sufferslosses worth more than $300 M as a result of flood and cyclone damage annually. It isalso worst flood affected country after Bangladesh (Agarwal et al., 1991) and accountsfor one fifth of global death count due to floods. About 40 Mha or nearly 1/8 th of India’sgeographical area is flood prone and the country’s vast coast line of 5700 km isexposed to tropical cyclones arising from Bay of Bengal and Arabian Sea. Space technology has made substantial contribution in every aspect of floodmanagement such as preparedness, prevention and relief (Rao, 1994). Informationacquired by remote sensing covers wide area, periodicity and spectral characteristicsand especially in the easiness to compare the data before and after a disaster. Theutility of the satellite remote sensing has been operationally demonstrated for mappingthe flood inundation areas, major floods and cyclones that occurred in the country weremapped in near real time and information was provided to the departmentsconcerned.Flood mapping is done predominanetly using RADARSAT satellite data Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 160. 159which is microwave data which can penetrate clouds during monsoon season. Inaddition to this when ever cloud free images of IRSP6 AWIFS/LISSIII, LISSIV data isalso used to generate regional / local / detailed information. A flow chart showing themethodology for near real time flood mapping is shown in Fig. 4.. Fig. 4. Methodology for near real time flood mapping Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 161. 1601.2.4 Identifying, inventory and assessment of irrigated crop and performance evaluation Irrigation tightens the intimate relationship of people (farmers, gate keepers,water policy makers), crops (irrigated areas, crop type, LAI development) and waterissues (crop water needs, crop water use, land wetness, water logging). Derivation ofdifferent object classes such as Cartography, Irrigated area (mono-crop and multiplecrop), crop communities, land cover and use from remote sensing that are useful forirrigation water management. Because productivity per unit of water is the focal point forevaluation of irrigation water management, regional yield data must be linked to regionalconsumptive use of water. The advantage of using remote sensing determinates is thatthey are based on standard international diagnostic techniques and that time-seriesmeasurements can be obtained from repetitive satellite coverage. Fig. 5 showsPerformance evaluation of chambal Irrigation command area. Fig. 5. Performance evaluation of Chambal irrigation command area. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 162. 1611.2.5 Reservoir sedimentation Many reservoirs built with huge investment are undergoing rapid silting and lossof storage capacity and consequent reduction in economic life of reservoir. The analysisof sedimentation data of India reservoirs show that the annual siltation rate has beengenerally 1.5 to 3 times more than the designed rate and the reservoirs are generallylosing capacity at the rate of 0.30 to 0.92% annually. Conventional hydrographicsurveys to reassess reservoir capacity are both costly and time-consuming. Multitemporal satellite data have been used an aid to capacity survey of many reservoirs inIndia. Central Water Commission has identified about 108 reservoirs in India to be takenup for reservoir sedimentation studies using satellite remote sensing techniques.Several organization, institutions are involved in this. While this technique helps inrevising capacity table between minimum and maximum draw-down level observed insatellite data, loss of dead storage capacity can be obtained only through conventionalhydrographic surveys. Fig. 6 Reservoir sedimentation survey of Tungabhadra reservoir. Fig.6. Reservoir sedimentation survey of Tungabhadra reservoir. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 163. 1622. Time and Cost Advantage Since remote sensing data can give synoptic coverage of the area, which will beuseful to analyses with limited ground truth. In view of this the cost of the remotesensing data is justified and economical to use.3. Future Prospects Precipitation Recognizing the practical limitations of rain gauges for measuring spatiallyaveraged rainfall over large areas and inaccessible areas, hydrologists haveincreasingly turned to remote sensing as a possible means for Quantitative PrecipitationInformation (QPI) especially in areas where there are few surface gauges. Improvedanalysis of rainfall can be achieved by improved inverse models, multi-sensor andblended products e.g., CPC rainfall (Passive, SAR, Thermal + Rain Gauge). A multi-sensor, observation technique is shown in figure 7. Useful data can be derived from satellites used primarily for meteorologicalpurposes, including polar orbiters such as The National Oceanographic andAtmospheric Administration (NOAA) series and the Defense Meteorological SatelliteProgram (DMSP), and from geostationary satellites such as Global OperationalEnvironmental Satellite (GOES), Geosynchronous Meteorological Satellite (GMS) andMeteosat, and Indian Satellite (INSAT) series. Whereas the visible/ infrared techniquesprovide only indirect estimates of rain, microwave techniques have great potential formeasuring precipitation because the measured microwave radiation is directly related tothe rain drops themselves. Fig. 7 shows a multi-sensor, observation technique. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 164. 163 EGPM Needs Techniques instruments Horizontal fields of Microwave imaging in precipitation 18 to 150 GHz windows Microwave radiometer Accuracy Microwave sounding in enhancement for light 50-60 GHz & 118 GHz liquid and solid bands precipitation High Sensitivity Microwave Profiles of backscattering at 36 Precipitation precipitation GHz Radar Fig. 7. A multi-sensor observation technique. Soil Moisture Soil Moisture is the most important component in understanding hydrology of anarea. This is difficult to measure in large spatial extents; where as remote sensing haslot of potential in estimating surface soil moisture. The revolution in mapping soilmoisture using remote sensing sensors is shown in Fig. 8. As far now, the soil moisturefields generated are at course resolution in terms of km. However future microwavemissions such as RISAT from India and Terra SAR-X with higher spatial resolution ofless than 10 m it will be possible to understand spatial spoil moisture variation atwatershed level. If the emerging hydrological sciences are to break away from thetraditional engineering hydrology, a number of general specific data needs are going tohave to be addresses and solved. Some of them are: • hydrological data are needed to measure fluxes and reservoirs in the hydrological cycle and to monitor hydrological change over a variety of temporal and spatial scales. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 165. 164 • detection of hydrologic change requires committed international long-term efforts and requires also that the data meet rigorous standards for accuracy. • synergism between model and data is necessary to design effective data collection efforts to answer scientific questions • a fundamental block to progress in using most hydrological data is our poor knowledge of how to interpolate between measurement points. There are potentially many new and exiting observations of hydrological cyclethat are going to be available from new satellite mission and their salient features aregiven here.3.3 HYDROS Hydrosphere States Mission • A NASA Earth System Science Pathfinder mission; • Surface soil moisture w/ ±4%vol. accuracy and Freeze/Thaw state transitions; • Revisit time: Global 3 days, boreal area 2 days • L-band (1.41GHz) Radiometer sensing 40km brightness temp. with H & V polarization; • L-band (1.26GHz) Radar measuring 1-3km backscatters with hh, vv, hv polarization; • Soil moisture products: 3km radar retrievals, 40km radiometer retrievals, 10km radar and radiometer combined retrievals and 5km 4DDA results. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 166. 165 Fig. 8. Soil moisture sensing over time3.4 SMOS –MISSION for Hydrological Applications • SMOS is a L-band (1.4 GHz) radiometer selected as one of ESA’s Earth explorer opportunity missions. This is due for launch in 2007. • Main objectives: Retrieval of surface soil moisture though measurement of surface brightness temperature. • Surface soil moisture retrieval (0- 5 cm): Spatial resolution < 50 km; temporal resolution < 3 days. Standard error < 0.04 m3/m3. • SMOS is an unprecedented opportunity to measure directly the near surface soil moisture, globally, at an intermediate spatial scale and sufficient revisit period. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 167. 1663.5 The Water Elevation Recovery Mission The features of this mission are given below. • 5-10 cm height accuracy (need height change for storage change, not absolute height) – River discharge, wetland/lake storage change • Map rivers > 100m width – Would like to go to smaller rivers • River slope accuracy: 10 mrad (1cm/1km) – River discharge • Revisit time: – Ideal: 3 days in the Arctic, 7 days in the tropics – Acceptable: 7 days in the arctic, 21 days in the tropics • Imager with resolution better than 100 m – River width, wetland/lake extent – Should distinguish vegetated/non-vegetated • Global coverage, sampling all major contributors to surface water, is not affected by clouds – Wetlands, rivers, lakes in tropics, Arctic thaw Fig. 9 shows Salient features of water elevation recovery mission. Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010
  • 168. 1673.6 LIDAR Missions LIDAR remote sensing techniques can be applied to measure a wide variety ofatmosphere co parameters important in hydrological sciences, including aerosoldistribution, cloud properties and ozone and water vapor concentrations and wind fields.The incoming solar radiation (isolation) that reaches the earth surface can be measuredusing remote sensing techniques. Radiation and latent and sensible fluxes areimportant processes in land-atmosphere exchanges, which can be quantified usingmeteorological and remote sensing data (NDVI, albedo, surface temperature etc.).ReferencesAgarwal, Anil and Sunita, Narain. 1991. Floods, Flood Plains and Environmental Myths.Rao, D.P., 1994. Space and Drought Management in Asia-Pacific region. Space Forum 4, 223-247.Web Linkswww.cwc.nic.inwww.indiawaterportal.orgwww.hydros.gsfc.nasa.govwww.esa.int/esaLP/LPsmos.htmlwww.bprc.osu.edu/water Remote Sensing: An Overview for Decision Makers IIRS/LN/DMC/2010