1. Operational Remote Sensing
Applications
MVR Sesha Sai
Head, Agriculture Division (LRG)
National Remote Sensing Centre (ISRO)
Hyderabad – 500625 INDIA
IIRS, June 16, 2010
2. STRUCTURE OF THE PRESENTATION
Our Vision Statement
Institutional mechanism
Natural Resources Census
Operational Thematic Applications
Agriculture, Soils / Land, Water Resources,
Forestry, Geology, Urban Studies; Watershed
mgt.
Disasters: Drought, Flood
Enhanced Outreach
Ground / Field Data Collection
Conclusion
3. Our
Vision
Indian space programme driven by vision of
Dr Vikram Sarabhai,
the father of the Indian Space Programme
“There are some who question the relevance of space activities
in a developing nation. To us, there is no ambiguity of purpose.
We do not have the fantasy of competing with the economically
advanced nations in the exploration of the moon or the planets
or manned space-flight. But we are convinced that if we are to
play a meaningful role nationally, and in the community of
nations, we must be second to none in the application of
advanced technologies to the real problems of man and
society.”
4. Components of National Natural Resources
Management System
PC – NNRMS
Chair : Member (Science),
Planning Commission
STANDING
COMMITTEES
Chair: Secretaries of GoI
Department of
SC-A : Agriculture & Soils
Space (Nodal SC-B : Bio-resources &
Department) Environment
ISRO Centres and NE- SC-C : Cartography & Mapping
SAC SC-G : Geology & Mineral
Resources
SC- OM: Ocean Resources &
Meteorology
SC- R: Rural Development
SC-T : Training & Technology
SC-U : Urban Development
SC- W : Water Resources
State Support for
Natural Ministries /
Departments /
Resources Departments
District
Management
5. NATURAL RESOURCE INVENTORY USING SATELLITE D
National level 180m 60m 24m 6m
State level
District level
RICE
Mandal level
Village level
Rice Cotton
BANANA
MAIZE
TOBACCO
CHILLIES
IRS WIFS AWiFS IRS LISS-III LISS-IV data
6. LULC-250K
Land Degradation LULC-50K
Geomorphology LAND DEGRADATION
Wasteland
IRS Data
Soils SOIL
Ground water GROUND WATER
Wetlands
VEGETATION TYPE
Biodiversity BIODIVERSITY
Forest &
Vegetation WASTELAND
Land Use Land GEOMORPHOLOGY
Cover
Snow Cover
/Glacier
SNOW/GLACIERS
• AWiFS –250 K WETLANDS
• LISS III – 50 K
BHOOSAMPADA
7. National Land use Land cover Map using
Multi-temporal AWiFS data
LULC 2007-08
2004-05
2005-06
2006-07
2007-08
All interim Kharif and integrated LULC assessments were completed as per the
schedule and reports were submitted by 31st December of each year
8. BHOOSAMPADA
4 yearly Assessments:
Released on 28th Jan 2004-08
2009 Maps, Reports
Integrated queries with
socio-economic data:
Seasonal crop areas
Seasonal water spread
Seasonal snow cover
Integrated LULC assessment
9. APPLICATIONS IN AGRICULTURE
• IDENTIFICATION AND ACREAGE ESTIMATION
- MAJOR CROPS
- MULTIPLE CROPS
- HORTICULTURAL CROPS
• AGRICULTURE DROUGHT ASSESSMENT
• CROP PRODUCTION ESTIMATION
• CROPPING SYSTEMS STUDIES
10. recasting Agricultural Output using Space, Agrometeorology an
Land based Observations (FASAL)
na Re
tio Land
v en o Observation RS Se mot
on l Agr ology s Re. , Mod. ns e
C ete
o r ing
M T em
por
y al R
metr Cropped
Re S, H
.
no Sin i gh
o Crop da
Ec area
condition t e gle
Crop
acreage
Crop
yield
MULTIPLE IN-SEASON FORECASTS
Pre- Early- Mid- Pre- Pre- Revised
Season Season Season Harvest Harvest Incorporatin
State State District g Damage
11. Forecasting Agriculture output using Space, Agro-
meteorology & Land based observations (FASAL)
Nationwide Multiple Wheat & Rice Crop Forecasting
o In-season Crop Forecasts Spectral, Agromet &
Final Econometric Models
o Impact of Drought & Flood Estimate o Integrated Yield Mode
Assessment
o Early Warning – Crop condition
& Stress Scenario Spectral – Agromet
Third Models
o FASAL Centre /NCFC with
Estimate oSpace Images
Ministry of Agriculture
oMeteorological data
Forecasts oGround data
Crop Year Acreage Production Agromet Models
(mha) (mt) Second
oSpace Images
Rice 2009-10 31.31 64.55 Estimate
oGround Data
Wheat 2008-09 26.96 73.59 oTemp./Rainfall
Wheat 2009-10 28.33 81.21* First Econometric Models
*Delayed onset & extended monsoon , increased Estimate
acreage & favourable met conditions enhanced Rabi
crops productions
Pre-harvest Production Forecast at National, State and District levels
for Major Crops like Paddy, Wheat, Sorghum, Rapeseed, Mustard, ...
12. FASAL: Nationwide Crop Forecasting
National / State level estimations
Wheat (AWiFS)
Rabi cropped area (RCA) by end of January
First estimate of wheat acreage by end of February
Final wheat acreage estimate by end of March
Kharif Rice (Radarsat)
• First estimate (F1) of rice acreages by Sept 30
• Second estimate (F2) by Oct 31
• Final rice acreage estimate by Jan 31
Winter Potato (AWiFS)
o Haryana and Punjab by Dec 15
o Uttar Pradesh by Dec 31
o Bihar and West Bengal by Jan 15
1. National Wheat 2. National kharif Rice
Nov, Dec, Jan, Jul 13 (Date-1) Aug 06 (Date-2) 2 date FCC
F-1 (33.7Mha) Aug 30 (Date-3) 3 date FCC
RCA (32.0Mha) Feb- wheat-1 (26.6Mha)
Mar- NDVI profile Wheat-2 (27.25Mha)
Backscatter Profile F-2 (35.8 Mha)
Wheat, Grams,
Mustard, Potato,
Early Mid Late
Multi-date Resourcesat-1 AWiFS data Three date Radarsat SN2 data
13. CHANGES IN DISTRIBUTION OF KHARIF RICE OF ANDHRA PRADESH
RAW DATA
2000 2002 2004
CLASSIFIED DATA
RICE
2.64Mha 1.72Mha 2.36Mha
14. CHANGES IN DISTRIBUTION OF KHARIF RICE OF ANDHRA PRADESH
RAW DATA
2000 2002 2004
CLASSIFIED DATA
RICE
2.64Mha 1.72Mha 2.36Mha
15. Changes in spatial distribution of rice and cotton in Karimnagar dist. A.P.
2006: Normal year
2002: Drought year
Crop acreages (lakh hectares)
CROPS 2006 2002
RICE 1.44 1.11
COTTON 1.14 0.45
16. Inter seasonal changes in kharif rice & wheat cropped area
(2007 vs. 2006)
2007 2006 2007 2006
Part of Assam Part of
Rajasthan
Part of Part of UP
West Bengal
Part of AP Part of Bihar
17. Cropping Systems Analysis
Post kharif rice fallow lands – Potential for pulse cultivation
IRS-1C/1D WiFS DATA OF SOUTH ASIANS NATIONS
Acreages of kharif rice & fallows
Country Rice Fallows
(Mha) (Mha)
India 40.18 11.65
CLASSIFIED DATA OF SOUTH ASIAN NATIONS Bangladesh 6.36 2.11
Nepal 1.45 0.39
RICE
Pakistan 2.45 0.14
WHEAT
OTHER CROPS
KHARIF RICE
FALLOW LANDS
19. Village Resources Maps Monitoing of Land Degradation Land productivity
assessment
1997
2006
Action Plan
Land capability
1992 2006
Watershed studies
Land suitability
SOIL MAP
Land irrigabilty
Micro-watershed
Critical Areas Map Cotton Paddy
S3 S1 S
3
Cotton
N1
S1
N2 N2
Action plan map
20. Types of Remote sensing data for Soil Mapping
• purpose of the study,
• scale of the study,
• characteristics of targets
• climatic condition of the study area
Scale Sensors Level of Soil mapping Useful for planning at
1: 250 000 LANDSAT - MSS Subgroups/ Soil Family National, State and
IRS – LISS, WiFS and their association regional level
1: 50000 IRS – LISS II, III Soil series and their District/ sub district
LANDSAT- MSS association level
SPOT
1: 25000 IRS – LISS III +PAN Soil series and their Block / Taluk /Mandal
merged data association level
1: 12500 IRS – LISS III+PAN, Soil series, soil Phases Village level
1: 8000 or LISS IV Association of soil
larger IKONOS- MSS+PAN phases
CARTOSAT-1/2
21. METHODOLOGY FOR SOIL MAPPING
RS Satellite data Preliminary Visual Interpretation Ancillary data
(summer season) SOI Topo maps
Climatic data
Published literature
etc
Soil Profile Study Ground truth collection Soil samples collection
Soils -pH, Ece, ESP Soil Sample Analysis Soils Characterization
Finalization of thematic map
Soil / Land Degradation Map
22. SOIL MAPPING AT VARIOUS SCALES
Over the years, remotely sensed data like Landsat-MSS / TM , SPOT and IRS -
LISS-I, II, III, IV etc., were employed to map soils at different scales ranging from
1:250,000 scale to 1:50,000 scale and even to 1: 12,500 scale.
Small NBSS&LUP mapped soils of entire country using Less
Landsat MSS / TM data on 1: 250,000 scale.
Under IMSD Project, soils were mapped at 1:50,000 scale
using IRS-LISS-II/ Landsat-TM data for various parts in
Level of detail
India covering an area of about 83.3 million hectares.
Scale
Under NATP soil maps at 1:12,500 scale were prepared
for different micro-watersheds under different crop
production systems /agro-climatic zones of the country.
Under VRC programme, DOS is mapping soils on 1:10,000
or 1:8,000 scale using IRS-P6 LISS-IV and Cartosat data
to provide soil resources information at village level
Large More
23. SOIL MAPPING USING SATELLTE DATA
Satellite data SOIL MAP IRS-LISS-II FCC SOIL MAP
1:250000 Scale 1:50,000 Scale
IRS PAN + LISS-III IRS PAN + LISS-III IKONOS PAN +Multispect
1:25,000 Scale 1:12,500 Scale 1:8,000 Scale /
1:4,000
24. SOIL MAP AT PHASE LEVEL , ERRAMATTI TANDA VILLAGE, NALGONDA DISTRICT, A.P.
SOIL LEGEND
Map Soil- Description of Soil Phases
Unit Physiography
1 Residual EMT-1, Very shallow, gravelly sandy
Hill loam, steeply slopping, strongly stony +
associated with rocks
Erramatti Tanda Gently slopping upper pediplain
3 Moderately EMT-3, Mod. shallow, sandy loam,
eroded gently slopping, mod erosion, mod stony
4 Moderarely EMT-3, Mod. shallow, loamy sand,
PAN + MSS IKONOS DATA
eroded gently slopping, mod erosion, strongly
stony
5 Severely EMT-4, Shallow, loamy sand, gently
eroded slopping, severe erosion, slightly stony
Very gently slopping upper pediplain
6 Slightly EMT-5, Moderately deep, sandy clay
eroded loam, very gently slopping, slight erosion,
Erramatti Tanda slightly stony
7 Slightly EMT-6, Moderately deep, loamy sand,
eroded very gently slopping, slight erosion,
slightly stony
8 Moderately EMT-7, Moderately deep, sandy loam,
eroded very gently slopping, moderate erosion,
Settlement slightly stony
SOIL MAP
25. Evaluation of Soils Information
Land irrigabilty
Land capability assessment
Land productivity assessment
26. Land evaluation for different crops
Uppugunduru village, Prakasam district, Andhra Pradesh
S3
Cotton
N1
S1
N2
SOIL MAP Cotton
S3
S1 S1 S1
N2
N1
S1 S1
N2
N2
Paddy Chillies
27. Natural Resources Census: Land Degradation Mapping (1:50K)
SALIENT FEATURES ….
SALIENT FEATURES …. LD CLASSIFICATION SCHEME …..
LD CLASSIFICATION SCHEME …..
Land degradation processes (8)
Land degradation processes (8)
••Mapping and monitoring land
Mapping and monitoring land Water erosion, Wind erosion, Waterlogging, Salinisation / /alkalization,
Water erosion, Wind erosion, Waterlogging, Salinisation alkalization,
degradation (1:50 K) of entire
degradation (1:50 K) of entire Acidification, Glacial, Anthropogenic and Others.
Acidification, Glacial, Anthropogenic and Others.
country.
country.
Land degradation type (18)
Land degradation type (18)
••Use of multi-temporal IRS
Use of multi-temporal IRS Sheet erosion, Rills, Gullies, Ravines, Stabilized/partially stabilized
Sheet erosion, Rills, Gullies, Ravines, Stabilized/partially stabilized
LISSS- III satellite data.
LISSS- III satellite data. dunes, Un-stabilized dunes, Surface ponding, Saline soils, Sodic soils,
dunes, Un-stabilized dunes, Surface ponding, Saline soils, Sodic soils,
Saline-sodic soils, Acidic soils, Frost heaving, Mining, Brick kiln areas,
Saline-sodic soils, Acidic soils, Frost heaving, Mining, Brick kiln areas,
••Personal Geodatabase
Personal Geodatabase Industrial effluent affected areas, Mass movement / /mass wastage, Barren
Industrial effluent affected areas, Mass movement mass wastage, Barren
(NNRMS standards)
(NNRMS standards) rocky/stony waste and Miscellaneous.
rocky/stony waste and Miscellaneous.
Severity classes (5): Slight, Mod, Severe, Very severe & Extreme.
••Land Degradation Information
Land Degradation Information Severity classes (5): Slight, Mod, Severe, Very severe & Extreme.
System for easy query & Landform classes (4): Hills, Undulating plains, Plains & Valley.
Landform classes (4): Hills, Undulating plains, Plains & Valley.
System for easy query &
retrieval Land use classes (4): Agriculture, Forest, Plantation, Open scrub
Land use classes (4): Agriculture, Forest, Plantation, Open scrub
retrieval
LAND DEGRADATION MAPPING – SALT AFFECTED SOILS
Slight Saline-sodic
JAN
MAR FCC Feb, 06 Apr, 06 Nov, 06 Mod Saline-sodic
APR
Strong Saline-sodic
Delivariables: Statewise seamless database Soils Division, ERG, RS&GIS AA, NRSA
29. MAPPING METHODOLOGY
Temporal IRS LISS III data
Kharif, Rabi & Zaid
Image Enhancements Data Processing Geo-rectification
Ground truth
Map legend On screen data interpretation
Legacy data
Soil sample
Final thematic map analysis
Base map & attribute data Accuracy assessment
(Settlement, Drainage,
Waterbodies …..)
Geo-data base creation
Map template
Map outputs Report Area statistics State Mosaics
Color / symbol
scheme
30. APPROACH
Land Degradation Map 1:50K
(Ancillary database: Admin boundary, Watershed boundaries …..)
Area Statistics Projection
Data Model
LULC layer
Geo-spatial Database State / district layer
Wasteland layer
(metadata, spatial & attribute
data) Digital vector layers -
Forest layer SOI
Different season theme layers
Ground truth
On-Screen Interpretation
Satellite data Zaid Ortho-rectification
Satellite data - Rabi
Geo-rectification
Satellite data -
Kharif
31. Land degradation in Devadurga Taluk, Raichur Dt., Karnataka
Apr’06 Feb’06
Oct’06 Land degradation map
Hemnur
Saline-sodic Rill erosion
Sheet erosion - water Barren rocky/ stony waste
32. Karnataka: Land Degradation Map and Database
Land Degradation
map of Karnataka
F
i
e
l
Legend d
Hmd p
Nml
h
o
Tbs
t
Wri2 o
Wsh1
s
Attributes of one mapping unit
Bidar district, KN
Land degradation map database
33. National Wastelands Monitoring Project
User: DoLR, Ministry of Rural Development, GOI
Objective:
To update spatial information on wastelands, identify and
delineate areas where changes occurred lace
34. National Land Use // Land Cover Mapping on 1:50.000 scale with
Land Use Land Cover Mapping on 1:50.000 scale with
multi-temporal IRS LISS III Data
multi-temporal
Objective Approach
•Generate land use/ land •Use of multi temporal
7
geo-rectified LISS- III
cover data base on data covering kharif,
rabi, zaid seasons of
1:50,000 scale using three 16
20 2005-06
seasons (Kharif, Rabi & 4
3 •Creation of LULC:50 K
Zaid) LISS III satellite 17
19 3
13
integrated map based
data for the period 2005-
2 18
8
12
on On-Screen
Interpretation
06 14
15
11
•GT , legacy and L-IV
data used / consulted
for interpretation.
1
6
10
Web-Enabled Information Syste
Expected 9
14
Uses 14
5
•Benchmark database for future Legend
mapping cycles-2005-06
•Digital LULC database for 2005-06 for
various
users at district level
•Monitoring of dynamic features …
•Identification of “hotspot” areas from 2nd
36. Snow Hydrology
Snowmelt runoff forecast
Forecast of seasonal snowmelt runoff
inflows into Bhakra reservoir during
April-May-June months in the first
week of April every year to Bhakra
Beas Management Board
Snow Cover Depletion Curves
Snow Cover in Sutlej Basin as on 1st
April, 2005
Runoff (lakh cusec days)
Year
Forecast Actual % Variation
2000 14.0 13.21 -5.5%
2001 11.5 10.44 -10.1%
2002 21.0 19.90 -5.5%
2003 17.5 21.50 +18.6%
2004 9.5 9.24 -2.8%
2005 17.0 15.10 -12.6%
37. Reservoir Sedimentation
Temporal water spread
26-Sep-94
map
05-Feb-95
Reduction in
04-May-95 18-May-95 reservoir
capacity
38. Irrigation Water Management
Baseline inventory of command areas
Cropping pattern, cropping pattern deviation and compliance
monitoring
Estimation of crop yield and crop cutting experiments design
Irrigation system performance evaluation
Through-the-years performance monitoring to assess impact
of developmental programs
Diagnostic evaluation of problem pockets
Water logging and salinity problems
Evapotranspiration studies
Irrigation scheduling
39. Irrigation Command Area Monitoring
Progression of(19Crop Sowings using
th
Dec 2003 to 29 March 2004) th
Performance indicators
AWIFS data
Cropping Pattern
Area under crop
Irrigation potential utilized
Irrigation Intensity
Crop Production
Water Utilization Index
Prior to Irrigation Irrigation Supplies Initiated Transplantation
Transplantation, Emergence, Tillering
Active Tillering, Heading
41. Irrigation Water Management
Through-the-years
Rabi 2001-02 Rabi 1994-95 Rabi 1992-93
performance monitoring
Rabi Crop Area (ha)
Standard FCC
102591.81
100000 95269.32 97076.52
90000
H e ct a r e
80000
70000
60000
50000
1992-93 1994-95 2001-02
Crop Map
Paddy
Non
paddy
Area Irrigated per unit of Water
(ha/M.cu.m)
Paddy Transplantation Variability
100
90 8 4 .3 5
Barpali 80 7 0 .8 8
7 4 .7 8
70
ha / M . cu.m
60
50
40
30
20
Early
10
Normal 0
1 9 9 2-9 3 1 9 9 4 -9 5 2 0 01 -0 2
Late
Hirakud Command Area
42. Ground Water
Rajiv Gandhi National Drinking Water Mission
Scientific database on ground water
for identifying drinking water sources
Objective
to the NC/PC habitations on sustainable basis
Ground Water Prospects Map
(on 1:50,000 Scale)
Potential zones Locations & Priority
for Ground water areas for constructing
occurrence Recharge structures
Availability Quality Sustainability
Potential zones Constituents distribution Site specific Recharge
structures
yield and depth BIS Standards Priority
43. Mapping of Ground Water Prospects
Validation results • Map Unit • Probable Depth Range Of Wells
No. of Wells Drilled 204923
• Rock Type & Geological • Expected Yield Range Of Wells
Sequence Probable Success Rate Of Wells
Success rate 94%
• Geomorphic • Reference No. of Observation
No of Recharge 9744
Unit/Landform Wells
Structures Planned
No of Recharge 7030
• Recharge Conditions • Ground Water Irrigated Area
Structures • Nature Of The Unit • Recharge Structure Suitable
Constructed • Type Of Wells Suitable
46. Forestry Applications
Forest cover mapping
Vegetation type mapping
Preparation of the working plans
Forest Bio-diversity at patch scale
Forest fire mapping
Protected area mapping
47. Forestry Applications
•Forest Cover
•Biodiversity
Characterisation
• Trees Outside Forests
•Environmental Impact:
Vegetation and Land cover
•Forestry Forest Fire
monitoring
Vegetation type
•CDM – Afforestation and mapping
Deforestation
•Climate Change – NAPCC
Working Plan
Biodiversity characterization at landscape level
Statistical tests
Bootstrapping
Statistical
Graphs Charts Engine
Design based
Model based
geostatistical Estimation GIS
Engine Engine
Database Web support
Engine
Spatial &
Non-spatial
Data Sample
Reports Maps Accuracy Queries
Entry Points
Indian Forest Fire Response &
Assessment System
48. National Vegetation Type Map using IRS data
Landscape level Biodiversity Characterisation : DOS – DBT Initiative
Field Sample
Locations
113 vegetation types and other land use
classes, hierarchical classification
scheme
Forests, grasslands, scrub,
plantations,orchards, agriculture
PHASE 1 – 2000, PHASE 2 – 2003, PHASE
3 - 2006 Visual Interpretation of IRS LISSS III Data
49. National Forest Cover Assessment
National Forest cover assessment done on biannual basis, since two decades
State of Forest cover Report (SFR) placed in Indian Parliament
Forest Cover of India 25
Closed forest cover
21.6 Total forest cover
(State of the Forest Report , 2003)
19.47 20.55
19.52 19.44 19.47 19.27 19.39
19.45
20
Source : Forest Survey of India
F or e st a r ea in p er c e n t
Based on IRS LISS III data of 2002 14.12
15
12.68
11.71 11.72 11.73 11.48
11.51 11.17
10.88
10
Legend
Very Dense Forest (>70 %)*
Moderately dense forest(40 % - 70 %) 5
Open Forest(10 % - 40 %)
Scrub
Nonforest 0
1972- 1981- 1985- 1987- 1989- 1993- 1995- 1997- 2001-
Waterbodies 75* 83* 87** 89** 91** 95** 97** 99** 2004
State boundaries Year
Since 1997-98 cycle mapping carried out on
1:50,000 scale
*% Crown density in parenthesis
Forest cover assessed in terms of Very Dense (> 70%), Moderately Dense (40 -70 %) and Open (10-40%)
crown density classes using digital approaches
Forest Survey of India carries out the task with the technical know-how transferred in 1986 by Dept.Of Space
51. Landscape level Biodiversity Characterization : DOS – DBT Initiative
Products Vegetation Type Map Field sample Data Disturbance Index Map
Biological Richness Map
Eastern Ghats
Bioprospecting area prioritization - SFDs,
CIMAP, IIPM, RRL
NTFPs surveys - SFDs,
Tribal Ministry
Conservation Prioritization - Wild life
agencies, SFDs
Biodiversity Registers - AP
Biodiversity Board
Climate Change studies - DOS,
Around 350 patches of > MOEnF
200 sq km size which
have varied potential for Eco-development - NGOs,
bio-prospecting & SFDs
conservation identified Working Circles - SFDs
Impact Assessment - Pollution
52. Forest Working Plans – Geospatial inputs
Forest Inventory and Data
Analysis System (FIDAS)
DAS Ver 1.2 installed at Orissa Forest Dept Readily adoptable by other SFDs across n
53. Protected Area Management Plans
Spatial Inputs
Forest Cover ,type ,water
holes, tourism, wildlife
habitat fire lines, eco-
development Rehabilitation,
conservation zoning
Demonstrated and implemented in
several protected areas by
ISRO/WII
WII working towards national
effort under SC-B/MOEnF for all
protected areas
GB Pant Institute submitted a
proposal for 15 Biosphere
reserves to develop
comprehensive management
plans
55. Burnt area characteristics – Case study Western in ras ff
Ghats
False Colour Total Burnt area – 1,060 sq.km
Composite Total Forest area – 7,1461 sq.km
of entire Western
Ghats : IRS AWIFS 400 90
data of 2007
350 80
Maharastra
70
300
60
250
% No of Burnt Patch
Burnt Area (Sq.Km)
50
200
40
150
30
Goa 100
20
50 10
Karnataka
0 0
( <5 ha ) (5-40 ha) (40-100 ha) (100-1000 ha) (>1000 ha)
Burnt Area % No of Patch
50% of the burnt area is composed of patches
Kerala
less than 100 ha (90% of the total patches)
Tamilnadu
60% of the burnt areas are in deciduous forest
and 20% on the scrub forest.
56. ROLE OF REMOTE SENSING IN GEOLOGICAL THEMES
THEMES ROLE OF REMOTE
SENSING
Lithological mapping Updating Of Existing
Maps
Geomorphological All the major landforms
Mapping can be identified
Structural Mapping Lineament Mapping, Trend
lines, Strike Slip Fault,
Structural Landforms
Stratigraphic Mapping Difficult
57. National Geomorphological and
lineament mapping for the entire
country on 1:50,000 scale under Fire
NRC in association with GSI
dynamics in
Hyperspectral studies for Jharia coal
mineralized belt in the country in fields using
association with GSI thermal
Landslide Hazard Zonation studies data
in association with ITC and GSI for
vulnerable belts
SAR interferometry studies for
understanding cosesimic
displacement for earth quake CARTOSAT-1
studies
captures
Aeromagnetic data and satellite
data integration for hydrocarbon landslide
explorations after the
earthquake
A
in J&K
GUD
SIRISULT
FA
CH
SEARIS Co-seismic
A X
displacem
BAR
EA R ent in
FAU APUR
LT Turkey
earthquake
using
Aeromagnetic contour data DINSAR
58. OVERVIEW OF NRC GEOMORPHOLOGICAL MAPPING ON 1:50,000 SCALE
Groundwater Glacier Melting
1 5
5
2
(Playa) (Outwash plain)
Disasters Illegal Mining
2 1 6
6
8
(Landslide) (Opencast mine)
Mineral Exploration Coastal inundation
3 7
• •Total 307 landforms in the country
Total 307 landforms in the country
are envisaged for mapping.
are envisaged for mapping.
7 • •Project will be completed in 2013.
(Beach ridge) Project will be completed in 2013. (Coastal bar)
Building Material • •Quality of the maps will be checked Seismic Zonation
Quality of the maps will be checked
4 by experts from ISRO and GSI.
4 by experts from ISRO and GSI. 8
• •All state remote sensing centres
3 All state remote sensing centres
and academics are involved.
and academics are involved.
(Inselberg) (Lineaments)
59. National Urban Information System
Executed by NRSC/ISRO,SOI/DST & MoUD
Project Schedule: June 2008 – July 2010
Scope :
No. of Towns : 152
Generation of Multi scale (10K,2K&1K)
Hierarchical Urban Geospatial Database including Area : 55,755 sq.km
Thematic data for various levels of Urban
Planning, Infrastructure Development and e-
governance using Satellite, Aerial and GPR
techniques.
NRSC/ISRO Responsibility:
Providing High Resolution Satellite Data of IRS P5
Cartosat-1(Stereo)& LISS-IV MX Data.
Generation of Thematic Geospatial Database on
Metro - 11 cities
1:10,000 scale with 16 Layers of Base, Urban Class I – 72 towns
Landuse, Geology/Geomorphology, Soils themes Class II – 15 towns
from IRS Satellite data and Administrative, Class III – 19 towns
Municipal and Census data Class IV – 17 towns
Class V – 6 towns
Providing Aerial Photography on 1:10,000 Scale for
Class VI – 12 towns
generation of Geospatial Database at 1:2000 scale
for Core City areas.
61. APPROACH
Watershed level NATURAL RESOURCES Identification of critical areas
1: 50, 000 scale CHARACTERISATION Based on inherent soil
IRS LISS III /IV problems
Identification of a
micro- watershed
for detailed inventory
Micro-watershed
level ASSESSMENT OF
RESOURCES Action Plans
1: 12, 500 scale
IRS LISS IV / POTENTIALS /
CARTO 1& 2 CONSTRAINTS
Water harvesting structures
IMPLEMENTATION Soil conservation measures
Field level Crop HYVs / improved practices /
improved cropping intensity
62. THEMATIC MAPS OF NIPANA MICRO WATERSHED
SATELLITE DATA SOIL MAP LAND USE / LAND COVER
GROUND WATER PROSPECTS
CRITICAL AREAS MAP
63. ACTION PLAN FOR RAINFED COTTON PRODUCTION
SYSTEM NIPANA MICROWATERSHED, AKOLA Dt, MAHARASHTRA
Legend
Improved hybrid cotton and intercropping with G.gram,
B. Gram + Pigeon pea;CPGB, diversion ditches
Broad bed and furrow; CPGB; Cotton(PKV-2) and
intercropping with G.gram, B. Gram + Pigeon pea
CPGB +Stone filter ; Improved Desi Cotton
intercropping with pearl millet
Cotton (Nanded 44)+Green gram (1:1)/Maize +
Pigeon Pea (3:3/4:2) CPGB :Diversion ditches
ICT + Teak/Bambaoo:Diversion Ditches
ICT +Plantations – Dryland fruit crops
Silvipastoral system of Ailanthes excelsa +
Dinanath grass ; ICT
Brush wood gully plugs:Gap Plantation with
Hardy species
Farm ponds Maintenance of Existing land use
Nala bund
Gully plug
64. NIPANA MICRO WATERSHED AKOLA DISTRICT, MAHARASHTRA
Intermittent contour trenches Satellite data Recharged well with high water level
Action plan Good crop of cotton beside recharged well
Conservation pit graded bund
Cotton varietal trials
Cement gully plug
65. INTERMITTENT CONTOUR TRENCHES - VIEWED BY HIGH RESOLUTION SATELLITE
NIPANA MICRO WATERSHED, AKOLA DT. , MAHARASHTRA
Quickbird MSS data after implementation Quickbird PAN data after implementation
Intermittent contour trenches Farm pond
67. NATIONAL AGRICULTURAL DROUGHT ASSESSMENT AND MONITORING SYSTEM
Coverage Satellite data analysis
Drought
assessment
A
N N N AWiFS
N N N
N
N • AWiFS
A
• MODIS 250 m
A • MODIS 1 km
A
A=AWiFS • AVHRR
N N=NOAA
Indicators/information
being used in
Information reporting
drought assessment
•NDVI
•NDWI AVHRR
•EVI
•AMSR E soil moisture Integration with ground data
•CPC rainfall forecast Rainfall deviations
.
.
300 Sowing progress
•Rainfall 250
100
90
80
•Sown area 200
70
% of normal
% deviation
150 60
•Soils 100
50
40
30
50
•Cropping pattern 0
20
10
-50 . 0
•Irrigation support
5 Jun
12 Jun
19 Jun
26 Jun
3 Jul
10 Jul
17 Jul
24 Jul
31 Jul
7 Aug
14 Aug
21 Aug
31 Aug
11 Sep
18 Sep
25 Sep
30 Sep
-100
12/6 19/6 6/6 3/710/7 17/7 24/7 31/7 7/8 14/8 21/8 28/8 4/9 11/9 18/9 25/9
68. Methodology for agricultural drought assessment
Change in crop calendar
Drought warning
Lag between NDVI & (June, July, August)
rainfall
Normal
Abnormal weather events
Such as floods
NDVI anomaly Watch
Assessment
(1) Relative dev. Alert
(2) VCI
(3) In season
transformation Extent of NDVI Drought declaration
anomaly (Sep, Oct)
Agricultural Extent of rainfall
drought Mild
deviation
situation
Moderate
Extent of sown area
deviation Severe
69. Progression of NDVI : 2009 (nation)
Jun 2009 Jul 2009 Aug 2009
Sep 2009 Oct 2009 Nov 1fn 2009
70. Monitoring Crop Condition – 2009, AVHRR NDVI
July August
June
September October Agri. Drought
Assessment
71. Progression of NDWI : 2009 (nation)
Jun 2009 Jul 2009 Aug 2009
Sep 2009 Oct 2009 Nov 1fn 2009
72. Agricultural drought assessment: Kharif 2009
June July August
(part of the district) October
September
June 215 dist
July 226 dist
Aug 124 dist
Sep 115 dist
Oct 179 dist
74. Agricultural Drought Assessment
Drought impact assessment
Vulnerability mapping
Early warning systems
NDVI Spatial Decision Support Systems
I anomaly Country wide monitoring with high resolution AWiFS data
N Support from geo-stationery systems
P Rainfall 2007+ Utilisation of microwave data
U deviation Process based indictors (energy balance)
T
Sown area • IRS AWiFS based sub-district level assessment
S deviation • AVHRR based regional/district level assessment O
• Integration with ground data/multiple indices Drought warning:
June, July, Aug. U
• Decision rules for drought warning & declaration
2004 • Enhanced content & frequency of reporting
* Normal T
* Watch P
• Institutional participation & Capacity building
* Alert
U
• IRS WiFS based district / sub district level assessment Drought declaration: T
• Supplementation of WiFS with MODIS Sept, Oct., Nov.
2002 • AVHRR based regional/district level assessment S
* Mild
• Agricultural area monitoring
* Moderate
* Severe
• IRS WiFS based district / subdistrict level assessment
1998 • AVHRR based regional/district level assessment
USER DEPARTMENTS
• Participation of user departments
(Union & State Govts.):
• NOAA AVHRR
1988 • Regional/district level assessment
Agriculture Ministry
Relief Commissioners
75. Floods-2008
Introduction Kosi Breach
• June-Sept, 8 states mapped
• More than 400 flood maps 8
6
7
• State, district, detailed flood maps
• MHA, CWC, IMD, State Govt
• The breach in Kosi river embankment led to change in the river course, extensive flooding
and reduction in the old river course.
PRE FLOOD
Monitoring
POST FLOOD
11-Apr-08 20-Aug-08 23-Aug-08 27-Aug-08 2-Sep-08 7-Sep-08 18-Sep-08 20-Sept.-08 22-Sep-08 29-Sep-08
Detailed View Persistence of Flood Inundation
• More than 130 villages
are under submergence
for more than a month
PRE BREACH: CARTOSAT & LISS IV MX MERGED
IMAGE SHOWING BREACH LOCATION a
a b
b
POST BREACH: CARTOSAT IMAGE SHOWING
• Flood persistence map- Aug. 20th to Sep. 22nd, 2008-for part of Madhepura
BREACH LOCATION • Detailed views of the embankment breach
district
76. August 20, 08
Flood
Inundation
r
i ve
s iR
Ko
Kosi River
Breach
mk
1.7
Monitoring – every 2 days Info Dissemination
Impact Assessment : • MHA, CWC, IMD,
• 625 Villages Marooned •Govt. of Bihar
• 0.12 Mha 95000 Sq Km ASAR data Cartosat-2 image
collected in 3 resolutions 09 Sept. 08
77. Impact of Orissa flood on kharif rice cropped are
Classified data showing Rice Total Inundated area Inundated Rice
cropped area
14.0 Lakh ha 4.49 Lakh ha 1.83 Lakh ha
Total Inundated
Duration of
Data used inundated rice area
Flood
area (ha) (ha)
Scansar-N
01 day 18-09-08 204010 100135
Scansar-w
07 Days 24-09-08 73890 24806
Scansar-W
12 days 29-09-08 74305 21902
78. CARTOSAT-1 DTM
INDIAN COAST
Input Data : Cartosat-1 data
[Total No. of Scenes : 600 ( 270 East + 330
West)]
Control Source : ETM (X,Y) and
SRTM (Z)
Output DTM (Bare earth): Upto
20km inland buffer Cartosat-
1 and LISS-IV MX Ortho
Image
PILOT STUDIES
Visakhapatnam and
Nagappattinam Coast
80. Village Resource Centres (VRCs)
For Empowering Rural Community
Components of VRC
• Two way audio-video
link via satellite
• Advisory related to
Agri., Fisheries, …
• Natural Resources VRCs
Information As on January 2010
• Tele-Education, Tele-
Healthcare, …
• Disaster related
• Skill Development
• ……………. Natural Resource data at VRCs
Set-up:
~ 45 partner agencies
~75 Expert Centres/ Hospitals
Satellite data Road Network Geomorphology Landuse/cover are linked in the network
Over 6000 programmes conducted, more than 4 lakh people benefited
81. Space Based Information Support for Decentralized
Planning: SIS-DP (2009 Road 2015) Telephone
to
Background Canal Post Office Electricity Wells
Taken up at the behest of Planning Market
Commission’s and PC-NNRMS
resolution to facilitate GIS enabled
Resource Catalogue and make them School
available to the people at grassroots College Internet
Sanitation
Dispensary
level. Bore well Banks
develop
deploy Objectives
• Spatial depiction of land & water resources with attribute
information, by keeping cadastral data as base in seamless
engage manner for entire country
• Tools and utilities for providing user driven applications for
speedy, accurate and transparent decision making; and
empower
• Capacity building in state departments with the training of
advance
manpower in spatial data analysis.
Land Cover Settlement Well data Infrastructure Ex. Road widening
82. Space Based Information Support for
Decentralized Planning: SIS-DP
ISRO Role
Satellite Data NR Census layers
• Land Use / Land Cover
(Cartosat – 1, 2 / • Land Degradation
LISS MX IV) • Forest & Vegetation MIS
Periodic National Monitoring
• Wetlands
• Snow & Glacier Space
Land cover, Road, • Geomorphology based
Settlement, Drainage • Soil Monitoring
& WB, Soil*, GWP* Periodicity
(Revisit in 10 years) • Every 5 years
Slope (DEM) • Every 20 years
1:10 K
Customized State Data Repository
Communication
State Creation & Updating
Dissemination
Highway
Cadastral User Projects
(Digital Maps) • Ground Water Prospect District database
(RGNDWM) District Usage and updating
• Wastelands Resourcesat2,
-
Digital village cadastral • Irrigation Infrastructure Cartosat3
-
maps, attribute linking (AIBP) ……
(Existing digital maps if • Watershed ISRO EO
• National Urban Information Missions
available will be used) System Usage through
Panchayat customized interface
4/5 states, NLRMP • Biodiversity
• Watershed Prioritisation
• Tribal Development
Based upon Policy:
* Soil & GWP in prioritized G2G, G2C
areas only
New Existing/ongoing Assured Continuity New
(1:10K) (1:50K)
83. Geospatial approach for Climate change studies
• Long term historical •High resolution data
satellite data •Field based
• Long term climate data biophysical,
• Vulnerability patterns meteorological data
Process Models
National Spatial Database BAU + Dynamic
•Crop growth
•Projected climate Scenario Response
•Dynamic growth
•Socioeconomic vegetation/niche
•Hydrology Functional •Hydrology
•LULC Change Analysis •Urban heat and spread
Drought response Water conservation • Degradation Urban energy
Alternate cropping & balance systems • Species conservn zones conservation &
• Eco corridors augmentation
Food security Water security Ecological security Energy security
86. Mobile Device Based Solution for
Field Data Collection
Technology
Cellular
Photo Network
GPS Receiver
camera
Field Internet
Collecting GPS
coordinates,
photographs, field Mail
parameters Server
Database Central
GSM/GPRS Developed Server
Application
Observation Transmission Information Decision Action
Enables real time data collection & transmission
GPS coordinates, Digital Photos, user specified parameters People affected: 354
People died: 40
Data can be organized into database, viewed in geo-spatial form
Application demonstrated- Relief Shelters/Hospitals/Civil Godowns
Customized applications can be developed for other applications
87. Systems for Watch on Weather and Climate
Automatic Space Observations Doppler Weather Radar
Weather Station (AWS) (DWR)
EO instrument capabilities
• Radiometers &
Satellite Spectrometers
Transmitter
• Atmospheric Sounders • Continuous monitoring
of severe weather
• Rain Radars
events
• High resolution imagers
• Radar network for
Met.
Analysis Data • Polarimetric radiometers
Sensor Team/ User Processing
entire coastal areas, NE
Data Dept. Center • Altimeters/Scatterometers region, major cities, …
Providing inputs for meso-scale modeling
88. Indian EO Missions - The Near Future
Resourcesat- Oceansat-3
Ku Band
3 Scatterometer
LISS-3 WS
2012-13 DMSAR-1
C/X SAR
INSAT-3D RISAT-1 2010-11
Geo HR
VHRR, Sounder C-band SAR
Cartosat- Imager
2B Resourcesat – 2 50m resolution
LISS III, LSS IV , AWiFS
1 m res.
IMS -
AWiFS Cartosat- 2C/
60m, 740 km 2D
80 cm res.
Scan-SAT
Ku Band Scatterometer
SARAL Cartosat- 3
Ka band Altimeter 30 cm res.
MEGHA-
TROPIQUES
89. o RSC
st N
nk A, ts
ha A pu
T IS in
G he
S & or t
R f
Thanks
for your kind attention
