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US Remote Sensing Capabilities

US Remote Sensing Capabilities. Chris Justice and John Townshend. NASA’s Earth Observing System & Related Satellites. Next Generation Missions. Relevance to Land of US assets. In fact relatively small number of assets directly relevant to land MODIS VIIRS Landsat

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US Remote Sensing Capabilities

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  1. US Remote Sensing Capabilities Chris Justice and John Townshend

  2. NASA’s Earth Observing System & Related Satellites

  3. Next Generation Missions

  4. Relevance to Land of US assets • In fact relatively small number of assets directly relevant to land • MODIS • VIIRS • Landsat • Also we need a “VCL” type instrument for the vertical dimension in vegetation • Just possibly may be revived. • Plus we need regular very high resolution data for scaling and validation which potentially could be provided by US commercial satellites

  5. VIIRS EDR Priorities & Performance Imagery (with four ARRs ) IA Sea Surface Temp Aerosol Optical Thickness Aerosol Particle Size Suspended Matter Cloud Cover/Layers Cloud Effective Particle Size Cloud Optical Thickness Cloud Top Height Cloud Top Pressure Cloud Top Temperature IIA Albedo Land Surface Temperature Vegetation Index Snow Cover/Depth Surface Type (ST)l Fresh Water Ice(Sea Ice ARR) Visible/IR Imager Radiometer Suite Ice Surface Temperature Ocean Color/Chlorophyll Sea Ice Characterization Active Fires (ST ARR) IIB Precipitable Water Cloud Base Height IIIB Net Heat Flux Soil Moisture

  6. M N 16 C2 N’ 10-Year Mission Life for NPOESS EOS-Aqua AVHRR-VIIRS Transition Schedule CY 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 NPOESS C1 VIIRS 0930 - 1030 AVHRR METOP-AVHRR 1030 EOS-Terra NPP 1330 VIIRS AVHRR Local Equatorial Crossing Time S/C Deliveries S/C delivery interval driven by 15 month IAT schedule 6 Last Modified: Dec 1, 2001

  7. Landsat data • Landsat class data with the Landsat 7 acquisition strategy (LTAP) has been highly successful in satisfying multiple user needs • GLCF has regular downloads of 25,000 + scenes per month. • But Landsat now has major problems.

  8. Scan Line Corrector failure means that only the central 28 kms has no missing data. In fact this still means that 78% of the data is collected. But the 22% not collected is NOT the same 22% on each image and hence change detection is significantly compromised. Landsat 7 has significant problems for change detection.

  9. Landsat 7 fixes 1. Enhanced SLC-off Browse Image • The Landsat 7 browse image displayed on all data ordering interfaces has been modified to allow users to estimate the width of potential SLC-off scan gaps over their area of interest. 2. User-Selected Interpolation • Users will have the ability to select the number of pixels that are interpolated across the data gaps during Level 1G processing. This will allow potential production of a fully populated image when specified by the user. 3. SLC-off Data Available through NLAPS • Users will have the option to purchase National Landsat Archive Production System (NLAPS) processing if desired. 4. Gap-filled product - Phase 1 (SLC-off / SLC-on Merge) • An initial (Phase 1) gap-filled image product will be generated by replacing the missing data of an SLC-off scene with pixel values derived from a coregistered, histogram-matched SLC-on scene. product. 5. Gap-Filled Product - Phase 2 (SLC-off / SLC-off Merge) • A second (Phase 2) gap-filled image product will be generated from the merge of two or more SLC-off scenes to produce a single image product. 6. Inclusion of band-specific Gap Mask

  10. Can Landsat be replaced with existing assets? • SPOT HRV and IRS can provide data with ground receiving capability. • Some efforts already to do this, though very slow response from the US. • Unclear if resultant products are truly interoperable, but probably acceptable. • But far from global coverage and the quality of acquisition strategy will be below that of Landsat.

  11. IRS-1C/1D LISS-3 data archive of R&D Center ScanEx (February, 2004)

  12. Availability of the historical record • Almost complete global coverage for the early 90’s and 2000 available through NASA/Earthsat’s Geocover initiative • Available on-line through the GLCF and through TRFIC • Made available to countries (though UNEP and FAO) • Very valuable data set but with significant limitations. • Timing of acquisition varies substantially • Varying phenology hinders change detection

  13. What is the quality of the data: analysis for southern Africa of the quality of FAO proposed 1 degree sample 10km squares

  14. Analysis of suitability of GeoCover images for 1990 for Southern Africa by GLCF • Total Number: 308 • Fully acceptable 180 • Restricted value due to cloud etc 89 • Unacceptable 39 • Hence historical record is less satisfactory than at first appears

  15. What can we learn from these issues? • We do not have the final solution. • We need an operational fine resolution (20-50m) land observing system • one that is guaranteed in the long-term • POLO Polar Orbiting Land Observer • Possible platform - NPOESS Lite • Having the assets in orbit is not sufficient: an excellent acquisition strategy is vital • Avoid moving parts if at all possible.

  16. Enhancements to ETM+ are needed. • LDCM Science Team for Resource 21made the following recommendations • Add bands especially a Cirrus band (1380nm – Goetz, Gao et al) • Alter bandwidths (lessons learnt from MODIS) • 10nm reduction (to 680 nm) in upper bound of red band • Narrow and reposition NIR band to avoid water vapor, • Narrowing and repositioning of SWIR2 to the 1560nm to 1660 nm region to avoid water vapor attenuation. • Shift the SWIR3 to the 2100 nm to 2300 nm region to reduce water vapor absorption impact. • Improve the MTF (e.g., average 9x10m bands) • Improve frequency of acquisition (e.g. to 2 days).

  17. Conciliating spatial and temporal resolutions: towards an operational concept for land environment: argues for more frequent observations at Landsat/SPOT resolutions Landsat SPOT 5 SPOT ERS Pléiades MERIS MODIS VGT POLDER MSG « Gap » 10-20 m spatial resolution 8-12 spectral bands2 days revisit Full and operational observation of continents Source: H. Jeanjean

  18. Recent developments • US has at last accepted that a Landsat class capability be regarded as an operational necessity. • Proposal in recent RFI is to place an ETM+ like instrument on NPOESS. • But this could be 2009 or later. Hence possibility of a major gap. • May be a earlier launch but resources may not be available. • International effort should be launched to use existing international assets to satisfy LTAP. • Frequency would drop to once every 17 days. • Suggested enhancements: • Significantly widen swath (2-3 times) • Additional low cost free-flyers (Surrey Satellite model?) with possibly simpler sensors to improve temporal resolution and as operational back-ups. • Need reflectance products not DNs. • Also orthorectified products.

  19. Extra slides • One on a new crop data set though coarse resolution • Two extra JAXA slides if you need them

  20. Global Data Set of 18 Major Crops Global Distribution of Wheat Derived by merging remotely-sensed global land cover data with crop census data. Leff, B., N. Ramankutty, and J. Foley, Geographic distribution of major crops across the world, Global Biogeochemical Cycles, 18, GB1009, 2004. Center for Sustainability and the Global Environment Nelson Institute for Environmental Studies University of Wisconsin-Madison

  21. GRFM/GBFM Data Sets AFR-1 (3 CD set) West & Central Africa and Madagascar Dual-season (Low water/high water) Mosaicking by JRC SAR processing by NASDA AM-1 (4 CD set) South America/Amazon Dual-season (Low water/high water) Mosaicking by JPL SAR processing by ASF & NASDA SEA-1 (2 CD set) Mainland South-East Asia Dual-season (Dry/rainy) Mosaicking & SAR processing by NASDA NA-1 (DVD) Boreal North America Dual-season (Summer/winter) Mosaicking by JPL SAR processing by ASF AM-3 (2 CD set) Central America/Pantanal Mosaicking by JPL SAR processing by ASF & NASDA

  22. New Data Sets in the pipeline SEA-3 Insular South-East Asia (Philippines, New Guinea) Single season Mosaicking & SAR processing by JAXA Target:June 2004 AU-1 Australia Single season Mosaicking & SAR processing by JAXA Target: JFY 2004 SEA-2 Insular South-East Asia (Kalimantan, Java, Sumatra, Sulawesi) Multi-annual (1994/1996/1998) Mosaicking & SAR processing: JAXA Target: April 2004 AFR-2 Southern Africa Single season Mosaicking by JPL SAR processing by JAXA China Single season Mosaicking & SAR processing by JAXA Target: JFY 2004 India Single season Mosaicking & SAR processing by JAXA Target: JFY 2004 AM-4 Southern South America Single season Mosaicking by JPL SAR processing by JAXA

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