WE1.L10 - IMPLEMENTATION OF THE LAND, ATMOSPHERE NEAR-REAL-TIME CAPABILITY FOR EOS (LANCE)

G
Land Atmosphere Near real-time Capability for EOSDIS (LANCE) Karen Michael, Kevin Murphy, Dawn Lowe, Jeanne Behnke - ESDIS Project, GSFC  Martha Maiden, NASA HQ  Chris Justice (UMd), Michael Goodman (NASA HQ) UWG Co-Chairs
The Land, Atmosphere Near-real-time Capability for EOS (LANCE) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
LANCE System Architecture lance.nasa.gov ,[object Object],[object Object],[object Object],TERRA  AQUA / AURA
High Operational Availability with Measurable Latency Metrics reports are updated weekly and available from the LANCE website
LANCE vs. Standard Product Latency – MODIS Example Standard Processing LANCE Processing (typical) Product Category Terra(hrs) Aqua(hrs) Terra/Aqua (hrs) L1/Cloud Mask 8 25 1.7 L2 Snow 8 25 1.8 L2 Sea Ice 8 25 2.0 L2 Fire 8 25 1.9 L2 Clouds 32 32 2.2 L2 Aerosol 32 32 2.2 L2 LSR 40 41 2.1
Near Real-Time vs. Science Quality Products – MODIS Example Science Product Near Real-Time Product Land Surface Reflectance  Cloud Top Temperature
Near Real-Time vs. Science Quality Products – MODIS Example ,[object Object],[object Object],[object Object],Short Name Science Data Match  (% Global) #pixel  (%Global) Omission Error  #pixel (%) Commission Error #pixel (%) MOD09 LSR-B1 98.94 N/A N/A N/A MOD09 LSR-B2 99.12 N/A N/A N/A MOD09 LSR-B3 99.32 N/A N/A N/A MOD09 LSR-B4 99.16 N/A N/A N/A MOD10 L2 Snow 99.97 31831094 (2.1%) 39751 (0.13%) 44255 (0.14%) MOD29 L2 Sea Ice 99.95 14471848 (5.5%) 8383 (0.06%) 14812 (0.1%) MOD14 L2 Fire 99.97 3207 (0%) 2 (0.06%) 3 (0.09%)
Brokerage and Direct Access ,[object Object],[object Object],[object Object],Application Brokers  Application Brokers Direct Access
AIRS/MLS Products LANCE-AIRS-Aqua  Icelandic Volcano Ash Plume Eyjafjallajokull  April 15, 2010 ,[object Object],[object Object],[object Object],[object Object],Visible 3km  SO2 10km  Processing Lead: Bruce Vollmer Instrument Product Categories Average Latency AIRS Radiances, Temperature and Moisture Profiles, Clouds and Trace Gases 75 – 140 minutes MLS Ozone, Temperature 75 – 140 minutes
AMSR-E Products LANCE-AMSR-E-Aqua Hurricane Alex, July 1, 2010,08:26 UTC ,[object Object],[object Object],[object Object],Processing Lead: Helen Conover Instrument Product Categories Average Latency AMSR-E Brightness Temperatures, Soil Moisture, Rain Rate, Ocean Products 80 - 135 minutes
OMI Products LANCE-OMI-Aura Icelandic Volcano  Eyjafjallajokull  April 15, 2010, 11:58-12:04 UTC ,[object Object],[object Object],Processing Lead: Curt Tilmes Instrument Product Categories Average Latency OMI Ozone, Sulfur Dioxide, Aerosols 100 – 165 minutes Latency excludes L3
MODIS Products LANCE-MODIS-Terra Oil Spill in Gulf of Mexico  May 24, 2010 16:50 UTC ,[object Object],[object Object],[object Object],Processing Lead: Edward Masuoka Instrument Product Categories Average Latency MODIS Radiances, Cloud/Aerosols, Water Vapor, Fire, Snow Cover, Sea Ice, Land Surface Reflectance, Land Surface Temperature 90 – 145 minutes Latency excludes L2G and L3
MODIS Global Time Fires Last 10 days
Fire Information for Resource Management ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],University of Maryland,  NASA GSFC, Sigma Space, UN FAO  FIRMS Fire Information for  Resource Management
Active Fire Mapping Source: http://activefiremaps.fs.fed.us/index.php USDA/USFS
Flood Mapping  Dartmouth Flood Observatory
Sea - Ice Monitoring  Source: http://www.ec.gc.ca/glaces-ice/default.asp?lang=En&n=D32C361E-1 Canadian Ice Service
Dust Detection Over Land The Application:  Depicting dust storms over the bright deserts through enhanced imagery. DoD Context: Mission planning, aircraft routing/launch/recovery, weapons selection. Source: Jeff Hawkins Naval Research Laboratory  Monterey The Approach: Use multi-spectral MODIS data to identify dust via color, thermal, spectral (11/12) contrast, and 1.38 cirrus filtering. (  ) Vis/NIR Index Temperature  Cirrus Flag Split Window dust
Drought Monitoring  Source: NASA MODIS NDVI Source: NASA MODIS NDVI Mean Vegetation Index Drought Impacted Vegetation Index (2007-08) USDA FAS / UMD / GSFC Dec 3-18, 2007 Dec 19-Jan1, 2008 Jan 1-Jan 16, 2008 Jan 17 – Feb 1, 2008 Feb 2 – Feb 17, 2008 Feb 18 – March 4, 2008 March 5- March 20, 2008 March 21- Apr 5, 2008 April 6- Apr 21, 2008 Vegetation Index Time Series for Cropped Areas in Iraq Vegetation Index Date Current Season (2007-2008) Mean (2000-2007) average average average
GEO Agricultural Monitoring Community of Practice ,[object Object],[object Object]
Way Forward  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
1 de 21

Recomendados

FR1.L09.2 - ONBOARD RADAR PROCESSING CONCEPTS FOR THE DESDYNI MISSION por
FR1.L09.2 - ONBOARD RADAR PROCESSING CONCEPTS FOR THE DESDYNI MISSIONFR1.L09.2 - ONBOARD RADAR PROCESSING CONCEPTS FOR THE DESDYNI MISSION
FR1.L09.2 - ONBOARD RADAR PROCESSING CONCEPTS FOR THE DESDYNI MISSIONgrssieee
409 visualizações18 slides
TU2.T10.1.pptx por
TU2.T10.1.pptxTU2.T10.1.pptx
TU2.T10.1.pptxgrssieee
450 visualizações28 slides
IGARSS2011_radarvolcanology.pptx por
IGARSS2011_radarvolcanology.pptxIGARSS2011_radarvolcanology.pptx
IGARSS2011_radarvolcanology.pptxgrssieee
218 visualizações27 slides
2003-12-04 Evaluation of the ASOS Light Scattering Network por
2003-12-04 Evaluation of the ASOS Light Scattering Network2003-12-04 Evaluation of the ASOS Light Scattering Network
2003-12-04 Evaluation of the ASOS Light Scattering NetworkRudolf Husar
363 visualizações42 slides
Backscatter Working Group Software Inter-comparison Project Requesting and Co... por
Backscatter Working Group Software Inter-comparison ProjectRequesting and Co...Backscatter Working Group Software Inter-comparison ProjectRequesting and Co...
Backscatter Working Group Software Inter-comparison Project Requesting and Co...Giuseppe Masetti
2.7K visualizações38 slides
TU1.L10 - Globwave and applications of global satellite wave observations por
TU1.L10 - Globwave and applications of global satellite wave observationsTU1.L10 - Globwave and applications of global satellite wave observations
TU1.L10 - Globwave and applications of global satellite wave observationsgrssieee
265 visualizações22 slides

Mais conteúdo relacionado

Mais procurados

5 IGARSS_Riishojgaard July 25 2011_rev2.ppt por
5 IGARSS_Riishojgaard July 25 2011_rev2.ppt5 IGARSS_Riishojgaard July 25 2011_rev2.ppt
5 IGARSS_Riishojgaard July 25 2011_rev2.pptgrssieee
220 visualizações20 slides
CAMS GA Aerosols por
CAMS GA  AerosolsCAMS GA  Aerosols
CAMS GA AerosolsCopernicus ECMWF
278 visualizações14 slides
20 bethke hammer_timeseries_of_spectrally_resolved_solar_irradiance_data_from... por
20 bethke hammer_timeseries_of_spectrally_resolved_solar_irradiance_data_from...20 bethke hammer_timeseries_of_spectrally_resolved_solar_irradiance_data_from...
20 bethke hammer_timeseries_of_spectrally_resolved_solar_irradiance_data_from...Sandia National Laboratories: Energy & Climate: Renewables
1.2K visualizações25 slides
CAMS GS Global Analyses por
CAMS GS Global Analyses  CAMS GS Global Analyses
CAMS GS Global Analyses Copernicus ECMWF
292 visualizações12 slides
CAMS General Assembly Fires by Kaiser por
CAMS General Assembly Fires  by Kaiser CAMS General Assembly Fires  by Kaiser
CAMS General Assembly Fires by Kaiser Copernicus ECMWF
394 visualizações13 slides
NDGISUC2017 - Development of an Open Source Alternative Climate Database Utility por
NDGISUC2017 - Development of an Open Source Alternative Climate Database UtilityNDGISUC2017 - Development of an Open Source Alternative Climate Database Utility
NDGISUC2017 - Development of an Open Source Alternative Climate Database UtilityNorth Dakota GIS Hub
148 visualizações15 slides

Mais procurados(20)

5 IGARSS_Riishojgaard July 25 2011_rev2.ppt por grssieee
5 IGARSS_Riishojgaard July 25 2011_rev2.ppt5 IGARSS_Riishojgaard July 25 2011_rev2.ppt
5 IGARSS_Riishojgaard July 25 2011_rev2.ppt
grssieee220 visualizações
CAMS GA Aerosols por Copernicus ECMWF
CAMS GA  AerosolsCAMS GA  Aerosols
CAMS GA Aerosols
Copernicus ECMWF278 visualizações
CAMS GS Global Analyses por Copernicus ECMWF
CAMS GS Global Analyses  CAMS GS Global Analyses
CAMS GS Global Analyses
Copernicus ECMWF292 visualizações
CAMS General Assembly Fires by Kaiser por Copernicus ECMWF
CAMS General Assembly Fires  by Kaiser CAMS General Assembly Fires  by Kaiser
CAMS General Assembly Fires by Kaiser
Copernicus ECMWF394 visualizações
NDGISUC2017 - Development of an Open Source Alternative Climate Database Utility por North Dakota GIS Hub
NDGISUC2017 - Development of an Open Source Alternative Climate Database UtilityNDGISUC2017 - Development of an Open Source Alternative Climate Database Utility
NDGISUC2017 - Development of an Open Source Alternative Climate Database Utility
North Dakota GIS Hub148 visualizações
CAMS General Assembly EUMETSAT por Copernicus ECMWF
CAMS General Assembly EUMETSATCAMS General Assembly EUMETSAT
CAMS General Assembly EUMETSAT
Copernicus ECMWF505 visualizações
20160614 CAMS GA Acquisition by Suttie por Copernicus ECMWF
20160614 CAMS GA Acquisition by Suttie20160614 CAMS GA Acquisition by Suttie
20160614 CAMS GA Acquisition by Suttie
Copernicus ECMWF254 visualizações
The New SCIPUFF Air Dispersion Model, with Comparison against CALPUFF por IES / IAQM
The New SCIPUFF Air Dispersion Model, with Comparison against CALPUFFThe New SCIPUFF Air Dispersion Model, with Comparison against CALPUFF
The New SCIPUFF Air Dispersion Model, with Comparison against CALPUFF
IES / IAQM1.9K visualizações
Enhanced Historical Installation Assessment por Andy Carroll
Enhanced Historical Installation AssessmentEnhanced Historical Installation Assessment
Enhanced Historical Installation Assessment
Andy Carroll448 visualizações
Comparison Of Elevation Collection Technologies por PaulDavidShaw
Comparison Of Elevation Collection TechnologiesComparison Of Elevation Collection Technologies
Comparison Of Elevation Collection Technologies
PaulDavidShaw300 visualizações
Keeping a Sentinel Eye on the Volcanoes – from Space! por Advanced-Concepts-Team
Keeping a Sentinel Eye on the Volcanoes – from Space!Keeping a Sentinel Eye on the Volcanoes – from Space!
Keeping a Sentinel Eye on the Volcanoes – from Space!
Advanced-Concepts-Team78 visualizações
Linked Sensor Data cube por Laurent Lefort
Linked Sensor Data cubeLinked Sensor Data cube
Linked Sensor Data cube
Laurent Lefort1.6K visualizações
The Use of WSR_88D radar data at NCEP_2015_AMS_20141222 por shun liu
The Use of WSR_88D radar data at NCEP_2015_AMS_20141222The Use of WSR_88D radar data at NCEP_2015_AMS_20141222
The Use of WSR_88D radar data at NCEP_2015_AMS_20141222
shun liu423 visualizações
1990-2050 sulphur dioxide emissions data from ECLIPSE v5a for use in Met Offi... por David Wallom
1990-2050 sulphur dioxide emissions data from ECLIPSE v5a for use in Met Offi...1990-2050 sulphur dioxide emissions data from ECLIPSE v5a for use in Met Offi...
1990-2050 sulphur dioxide emissions data from ECLIPSE v5a for use in Met Offi...
David Wallom140 visualizações
Air quality challenges and business opportunities in China: Fusion of environ... por CLIC Innovation Ltd
Air quality challenges and business opportunities in China: Fusion of environ...Air quality challenges and business opportunities in China: Fusion of environ...
Air quality challenges and business opportunities in China: Fusion of environ...
CLIC Innovation Ltd516 visualizações
DSD-INT 2015 - Satellite based near-real time information services for aquati... por Deltares
DSD-INT 2015 - Satellite based near-real time information services for aquati...DSD-INT 2015 - Satellite based near-real time information services for aquati...
DSD-INT 2015 - Satellite based near-real time information services for aquati...
Deltares1.2K visualizações

Destaque

Land resources of Cambodia by Sovuthy Pheav por
Land resources of Cambodia by Sovuthy PheavLand resources of Cambodia by Sovuthy Pheav
Land resources of Cambodia by Sovuthy PheavFAO
426 visualizações6 slides
Dissemination of new agricultural technologies in africa making extension work por
Dissemination of new agricultural technologies in africa making extension workDissemination of new agricultural technologies in africa making extension work
Dissemination of new agricultural technologies in africa making extension workWorld Agroforestry (ICRAF)
1.8K visualizações19 slides
Siana's Agricultural Land Use Presentation por
Siana's Agricultural Land Use PresentationSiana's Agricultural Land Use Presentation
Siana's Agricultural Land Use Presentation13413
698 visualizações25 slides
C.C.A.F.S. “Agricultural and Land-use Databases for Climate Smart Agriculture.” por
C.C.A.F.S. “Agricultural and Land-use Databases for Climate Smart Agriculture.”C.C.A.F.S. “Agricultural and Land-use Databases for Climate Smart Agriculture.”
C.C.A.F.S. “Agricultural and Land-use Databases for Climate Smart Agriculture.”World Agroforestry (ICRAF)
662 visualizações15 slides
Sustainable Intensification: A New Paradigm for African Agriculture 2013 Mont... por
Sustainable Intensification: A New Paradigm for African Agriculture 2013 Mont...Sustainable Intensification: A New Paradigm for African Agriculture 2013 Mont...
Sustainable Intensification: A New Paradigm for African Agriculture 2013 Mont...World Agroforestry (ICRAF)
1.1K visualizações16 slides
Cbp Management Structure por
Cbp Management StructureCbp Management Structure
Cbp Management StructureWorld Agroforestry (ICRAF)
198 visualizações5 slides

Destaque(9)

Land resources of Cambodia by Sovuthy Pheav por FAO
Land resources of Cambodia by Sovuthy PheavLand resources of Cambodia by Sovuthy Pheav
Land resources of Cambodia by Sovuthy Pheav
FAO426 visualizações
Dissemination of new agricultural technologies in africa making extension work por World Agroforestry (ICRAF)
Dissemination of new agricultural technologies in africa making extension workDissemination of new agricultural technologies in africa making extension work
Dissemination of new agricultural technologies in africa making extension work
World Agroforestry (ICRAF)1.8K visualizações
Siana's Agricultural Land Use Presentation por 13413
Siana's Agricultural Land Use PresentationSiana's Agricultural Land Use Presentation
Siana's Agricultural Land Use Presentation
13413698 visualizações
C.C.A.F.S. “Agricultural and Land-use Databases for Climate Smart Agriculture.” por World Agroforestry (ICRAF)
C.C.A.F.S. “Agricultural and Land-use Databases for Climate Smart Agriculture.”C.C.A.F.S. “Agricultural and Land-use Databases for Climate Smart Agriculture.”
C.C.A.F.S. “Agricultural and Land-use Databases for Climate Smart Agriculture.”
World Agroforestry (ICRAF)662 visualizações
Sustainable Intensification: A New Paradigm for African Agriculture 2013 Mont... por World Agroforestry (ICRAF)
Sustainable Intensification: A New Paradigm for African Agriculture 2013 Mont...Sustainable Intensification: A New Paradigm for African Agriculture 2013 Mont...
Sustainable Intensification: A New Paradigm for African Agriculture 2013 Mont...
World Agroforestry (ICRAF)1.1K visualizações
Agricultural Land Use Planning in Canada por Cherine Akkari
 Agricultural Land Use Planning in Canada Agricultural Land Use Planning in Canada
Agricultural Land Use Planning in Canada
Cherine Akkari850 visualizações

Similar a WE1.L10 - IMPLEMENTATION OF THE LAND, ATMOSPHERE NEAR-REAL-TIME CAPABILITY FOR EOS (LANCE)

FME Around the World (FME Trek Part 1): Ken Bragg - Safe Software FME World T... por
FME Around the World (FME Trek Part 1): Ken Bragg - Safe Software FME World T...FME Around the World (FME Trek Part 1): Ken Bragg - Safe Software FME World T...
FME Around the World (FME Trek Part 1): Ken Bragg - Safe Software FME World T...IMGS
1.1K visualizações76 slides
EOSDIS Status por
EOSDIS StatusEOSDIS Status
EOSDIS StatusThe HDF-EOS Tools and Information Center
409 visualizações11 slides
2008-02-11: EPA DataFed Presentation por
2008-02-11: EPA DataFed Presentation2008-02-11: EPA DataFed Presentation
2008-02-11: EPA DataFed PresentationRudolf Husar
503 visualizações53 slides
2004-07-28 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET por
2004-07-28 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET2004-07-28 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET
2004-07-28 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNETRudolf Husar
367 visualizações36 slides
Near real time automatic modis fire information por
Near real time automatic modis fire informationNear real time automatic modis fire information
Near real time automatic modis fire informationInstitute of Space Knowledge Development
401 visualizações69 slides
The National Elevation Data Framework por
The National Elevation Data FrameworkThe National Elevation Data Framework
The National Elevation Data Frameworkfungis
731 visualizações42 slides

Similar a WE1.L10 - IMPLEMENTATION OF THE LAND, ATMOSPHERE NEAR-REAL-TIME CAPABILITY FOR EOS (LANCE)(20)

FME Around the World (FME Trek Part 1): Ken Bragg - Safe Software FME World T... por IMGS
FME Around the World (FME Trek Part 1): Ken Bragg - Safe Software FME World T...FME Around the World (FME Trek Part 1): Ken Bragg - Safe Software FME World T...
FME Around the World (FME Trek Part 1): Ken Bragg - Safe Software FME World T...
IMGS1.1K visualizações
2008-02-11: EPA DataFed Presentation por Rudolf Husar
2008-02-11: EPA DataFed Presentation2008-02-11: EPA DataFed Presentation
2008-02-11: EPA DataFed Presentation
Rudolf Husar503 visualizações
2004-07-28 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET por Rudolf Husar
2004-07-28 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET2004-07-28 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET
2004-07-28 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET
Rudolf Husar367 visualizações
The National Elevation Data Framework por fungis
The National Elevation Data FrameworkThe National Elevation Data Framework
The National Elevation Data Framework
fungis731 visualizações
2004-09-12 Data and Tools for Air Quality Management: por Rudolf Husar
2004-09-12 Data and Tools for Air Quality Management:2004-09-12 Data and Tools for Air Quality Management:
2004-09-12 Data and Tools for Air Quality Management:
Rudolf Husar345 visualizações
Two-year assessment of Nowcasting performance in the CASA system por grssieee
Two-year assessment of Nowcasting performance in the CASA systemTwo-year assessment of Nowcasting performance in the CASA system
Two-year assessment of Nowcasting performance in the CASA system
grssieee357 visualizações
#EarthOnAWS | AWS Public Sector Summit 2017 por Amazon Web Services
#EarthOnAWS | AWS Public Sector Summit 2017#EarthOnAWS | AWS Public Sector Summit 2017
#EarthOnAWS | AWS Public Sector Summit 2017
Amazon Web Services690 visualizações
WaPOR version 3 - Annemarie Klaasse - eLeaf - 05 May 2023.pdf por WaPOR
WaPOR version 3 - Annemarie Klaasse - eLeaf - 05 May 2023.pdfWaPOR version 3 - Annemarie Klaasse - eLeaf - 05 May 2023.pdf
WaPOR version 3 - Annemarie Klaasse - eLeaf - 05 May 2023.pdf
WaPOR 42 visualizações
2004-09-12 Data and Tools for Web-Based Monitoring and Analysis por Rudolf Husar
2004-09-12 Data and Tools for Web-Based Monitoring and Analysis2004-09-12 Data and Tools for Web-Based Monitoring and Analysis
2004-09-12 Data and Tools for Web-Based Monitoring and Analysis
Rudolf Husar332 visualizações
Adam Lewis–SPEDDEXES 2014 por aceas13tern
Adam Lewis–SPEDDEXES 2014Adam Lewis–SPEDDEXES 2014
Adam Lewis–SPEDDEXES 2014
aceas13tern517 visualizações
Navy Integrated Tactical Environmental System (NITES2) por guest4a1658
Navy Integrated Tactical Environmental System (NITES2)Navy Integrated Tactical Environmental System (NITES2)
Navy Integrated Tactical Environmental System (NITES2)
guest4a16585.6K visualizações
1 IGARSS 2011 JPSS Monday Goldberg.pptx por grssieee
1 IGARSS 2011 JPSS Monday Goldberg.pptx1 IGARSS 2011 JPSS Monday Goldberg.pptx
1 IGARSS 2011 JPSS Monday Goldberg.pptx
grssieee485 visualizações
DSD-SEA 2023 Global to local multi-hazard forecasting - Yan por Deltares
DSD-SEA 2023 Global to local multi-hazard forecasting - YanDSD-SEA 2023 Global to local multi-hazard forecasting - Yan
DSD-SEA 2023 Global to local multi-hazard forecasting - Yan
Deltares36 visualizações
RCM mission v2.ppt por grssieee
RCM mission v2.pptRCM mission v2.ppt
RCM mission v2.ppt
grssieee437 visualizações
EODATASERVICE.ORG - Digital Earth Platform to enable Muti-disciplinary Geospa... por EUDAT
EODATASERVICE.ORG - Digital Earth Platform to enable Muti-disciplinary Geospa...EODATASERVICE.ORG - Digital Earth Platform to enable Muti-disciplinary Geospa...
EODATASERVICE.ORG - Digital Earth Platform to enable Muti-disciplinary Geospa...
EUDAT54 visualizações

Mais de grssieee

Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S... por
Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...grssieee
1.8K visualizações27 slides
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL por
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODELSEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODELgrssieee
1.3K visualizações18 slides
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET... por
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...grssieee
1.2K visualizações16 slides
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES por
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIESTHE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIESgrssieee
2.7K visualizações20 slides
GMES SPACE COMPONENT:PROGRAMMATIC STATUS por
GMES SPACE COMPONENT:PROGRAMMATIC STATUSGMES SPACE COMPONENT:PROGRAMMATIC STATUS
GMES SPACE COMPONENT:PROGRAMMATIC STATUSgrssieee
1.1K visualizações21 slides
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER por
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETERPROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETERgrssieee
1K visualizações47 slides

Mais de grssieee(20)

Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S... por grssieee
Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
Tangent height accuracy of Superconducting Submillimeter-Wave Limb-Emission S...
grssieee1.8K visualizações
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL por grssieee
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODELSEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
SEGMENTATION OF POLARIMETRIC SAR DATA WITH A MULTI-TEXTURE PRODUCT MODEL
grssieee1.3K visualizações
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET... por grssieee
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
TWO-POINT STATISTIC OF POLARIMETRIC SAR DATA TWO-POINT STATISTIC OF POLARIMET...
grssieee1.2K visualizações
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES por grssieee
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIESTHE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
THE SENTINEL-1 MISSION AND ITS APPLICATION CAPABILITIES
grssieee2.7K visualizações
GMES SPACE COMPONENT:PROGRAMMATIC STATUS por grssieee
GMES SPACE COMPONENT:PROGRAMMATIC STATUSGMES SPACE COMPONENT:PROGRAMMATIC STATUS
GMES SPACE COMPONENT:PROGRAMMATIC STATUS
grssieee1.1K visualizações
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER por grssieee
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETERPROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
PROGRESSES OF DEVELOPMENT OF CFOSAT SCATTEROMETER
grssieee1K visualizações
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR... por grssieee
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...
DEVELOPMENT OF ALGORITHMS AND PRODUCTS FOR SUPPORTING THE ITALIAN HYPERSPECTR...
grssieee1.1K visualizações
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A... por grssieee
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
grssieee915 visualizações
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A... por grssieee
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
grssieee718 visualizações
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A... por grssieee
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
grssieee919 visualizações
Test por grssieee
TestTest
Test
grssieee629 visualizações
test 34mb wo animations por grssieee
test  34mb wo animationstest  34mb wo animations
test 34mb wo animations
grssieee809 visualizações
Test 70MB por grssieee
Test 70MBTest 70MB
Test 70MB
grssieee552 visualizações
Test 70MB por grssieee
Test 70MBTest 70MB
Test 70MB
grssieee601 visualizações
2011_Fox_Tax_Worksheets.pdf por grssieee
2011_Fox_Tax_Worksheets.pdf2011_Fox_Tax_Worksheets.pdf
2011_Fox_Tax_Worksheets.pdf
grssieee764 visualizações
DLR open house por grssieee
DLR open houseDLR open house
DLR open house
grssieee592 visualizações
DLR open house por grssieee
DLR open houseDLR open house
DLR open house
grssieee608 visualizações
DLR open house por grssieee
DLR open houseDLR open house
DLR open house
grssieee534 visualizações
Tana_IGARSS2011.ppt por grssieee
Tana_IGARSS2011.pptTana_IGARSS2011.ppt
Tana_IGARSS2011.ppt
grssieee1.2K visualizações
Solaro_IGARSS_2011.ppt por grssieee
Solaro_IGARSS_2011.pptSolaro_IGARSS_2011.ppt
Solaro_IGARSS_2011.ppt
grssieee630 visualizações

WE1.L10 - IMPLEMENTATION OF THE LAND, ATMOSPHERE NEAR-REAL-TIME CAPABILITY FOR EOS (LANCE)

  • 1. Land Atmosphere Near real-time Capability for EOSDIS (LANCE) Karen Michael, Kevin Murphy, Dawn Lowe, Jeanne Behnke - ESDIS Project, GSFC Martha Maiden, NASA HQ Chris Justice (UMd), Michael Goodman (NASA HQ) UWG Co-Chairs
  • 2.
  • 3.
  • 4. High Operational Availability with Measurable Latency Metrics reports are updated weekly and available from the LANCE website
  • 5. LANCE vs. Standard Product Latency – MODIS Example Standard Processing LANCE Processing (typical) Product Category Terra(hrs) Aqua(hrs) Terra/Aqua (hrs) L1/Cloud Mask 8 25 1.7 L2 Snow 8 25 1.8 L2 Sea Ice 8 25 2.0 L2 Fire 8 25 1.9 L2 Clouds 32 32 2.2 L2 Aerosol 32 32 2.2 L2 LSR 40 41 2.1
  • 6. Near Real-Time vs. Science Quality Products – MODIS Example Science Product Near Real-Time Product Land Surface Reflectance Cloud Top Temperature
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13. MODIS Global Time Fires Last 10 days
  • 14.
  • 15. Active Fire Mapping Source: http://activefiremaps.fs.fed.us/index.php USDA/USFS
  • 16. Flood Mapping Dartmouth Flood Observatory
  • 17. Sea - Ice Monitoring Source: http://www.ec.gc.ca/glaces-ice/default.asp?lang=En&n=D32C361E-1 Canadian Ice Service
  • 18. Dust Detection Over Land The Application: Depicting dust storms over the bright deserts through enhanced imagery. DoD Context: Mission planning, aircraft routing/launch/recovery, weapons selection. Source: Jeff Hawkins Naval Research Laboratory Monterey The Approach: Use multi-spectral MODIS data to identify dust via color, thermal, spectral (11/12) contrast, and 1.38 cirrus filtering. (  ) Vis/NIR Index Temperature Cirrus Flag Split Window dust
  • 19. Drought Monitoring Source: NASA MODIS NDVI Source: NASA MODIS NDVI Mean Vegetation Index Drought Impacted Vegetation Index (2007-08) USDA FAS / UMD / GSFC Dec 3-18, 2007 Dec 19-Jan1, 2008 Jan 1-Jan 16, 2008 Jan 17 – Feb 1, 2008 Feb 2 – Feb 17, 2008 Feb 18 – March 4, 2008 March 5- March 20, 2008 March 21- Apr 5, 2008 April 6- Apr 21, 2008 Vegetation Index Time Series for Cropped Areas in Iraq Vegetation Index Date Current Season (2007-2008) Mean (2000-2007) average average average
  • 20.
  • 21.

Notas do Editor

  1. Examples of side-by-side comparisons of the standard and near-real time. The first shows a Land Surface Reflectance granule over the Midwest. There appears to be no difference between the products. However, under close examination the near-real time view shows slightly more haze West of the Great Lakes. In contrast, the second side-by-side comparison is for Cloud Top Temperature for the same granule and there are very obvious differences in the region West of the Great Lakes. This is as a result of the sensitivity of this product to the GDAS ancillary data.
  2. AIRS false-color 3-km visible image (left), and the SO2 brightness temperature difference at 10-km resolution (right) BT_diff_SO2 values under-6K have likely volcanic SO2. Information from multiple sensors indicates that this eruption is mostly ash with little SO2 being expelled into the atmosphere.
  3. This AMSR-E Brightness Temperature image with a GOES background shows Hurricane Alex entering Mexico, just as it is degraded to a tropical storm. Courtesy of US Naval Research Laboratory
  4. OMI image showing the ash cloud from the Icelandic volcano as flights are cancelled all across Europe, impacting tens of thousands of customers. Shown with MODIS “Blue Marble” Background
  5. MODIS Terra image taken on a relatively cloud free day just off the coast of New Orleans capturing the oil slick as it is being transported to the south via a loop current. The thicker oil slick appears brighter than surrounding water.
  6. Do we have a more recent example from LANCE The maps they generate are available to governments and relief organizations. For flood detection, the Flood Observatory has defined at least 710 sections of rivers worldwide. Each section is 20 to 30 kilometers in length and 20 to 30 kilometers in width. MODIS monitors the sections, called reaches, to determine the status of each. When water levels rise to flood status, the river can be targeted by higher-resolution sensors.
  7. The Canadian Ice Service uses MODIS images to chart out the daily ice conditions in the lakes, bays, and ocean around Canada.
  8. Dust events over Iraq can be quite nerve-wracking. Using MODIS data, Dr. Miller from our group developed and published a technique that applied a multi-spectral approach to distinguish dust from both clouds and the very complex desert terrain. In this example, the true color image reveals a complicated terrain pattern over the region within NW Persian Gulf. The dust product revealed a mesoscale frontal pattern of dust. Adding model winds depicts the circulation pattern within the dust plume along with a hint of the projected movement within the plume. In this example, dust over the Red Sea is clearly visible, but the extent of the plume isn’t clearly evident until the dust product is observed. In this example over the desert and mountainous terrain of Afghanistan, the dust pattern is visible, however, the dust product exposes the thickness of the plume, the sources of dust production, and hidden pockets of dust as shown here. This final example depicts the envelope of dust. Throughout the Middle East campaign, the NRL dust product has been an invaluable resource for military planners. Although there are a number of dust products available, the true test of dust detection comes in this type of terrain. Miller, S. D., 2003: A consolidated technique for enhancing desert dust storms with MODIS. Geophys. Res. Lett., 30, No. 20, 2071. Courtesy: NRL Satellite FOCUS web team, Naval Research Laboratory, Marine Meteorology Division, Monterey, CA 93943