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1 Landsat Data Gap Study Team Briefing to USGEO Study Team Chairs: Ed Grigsby, NASAGarik Gutman, NASARay Byrnes, USGS Team Lead: Vicki Zanoni, NASA 26.

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Presentation on theme: "1 Landsat Data Gap Study Team Briefing to USGEO Study Team Chairs: Ed Grigsby, NASAGarik Gutman, NASARay Byrnes, USGS Team Lead: Vicki Zanoni, NASA 26."— Presentation transcript:

1 1 Landsat Data Gap Study Team Briefing to USGEO Study Team Chairs: Ed Grigsby, NASAGarik Gutman, NASARay Byrnes, USGS Team Lead: Vicki Zanoni, NASA 26 May 05

2 2 Outline Introduction Key Findings Background Data Gap Study Team Assumptions Requirements Capabilities Comparison of Capabilities with Requirements Conclusions Recommendations

3 3 Introduction The Landsat Program provides for and updates a national archive of land remote sensing data for distribution to the U.S. Government, international community, and the general public –Public Law 102-555, the Land Remote Sensing Policy Act of 1992 –Presidential Decision Directive/NSTC-3 (5/5/94; amended 10/16/00) –Management Plan for the Landsat Program

4 4 Introduction The Earth observation community is facing a probable and pending gap in Landsat data continuity before OLI data arrive –Landsat 5 limited lifetime/coverage –Degraded Landsat 7 operations; potential failure in 2007 –Either or both satellites could fail at any time: both beyond design life Urgently need strategy to reduce the impact of a Landsat data gap –Landsat data are used extensively by a broad and diverse community –A data gap will interrupt a 33-yr time series of land observations during a critical time period Landsat Program Management must determine utility of alternate data sources to lessen the impact of the gap and feasibility of acquiring data from those sources in the event of a gap A Landsat Data Gap Study Team, chaired by NASA and the USGS, has been formed to analyze potential solutions

5 5 Key Findings The Landsat Program is unique –Single source of systematic, global land observations –Alternate sources may reduce the impact of a Landsat data gap Data quality of potential candidate systems is unverified; however, based on preliminary analysis –India’s ResourceSat and China/Brazil’s Earth Resources Satellite (CBERS) are the leading candidates for reducing the impact of a Landsat data gap Potentially acceptable global acquisition capability, availability, spatial and spectral coverage Landsat data gap mitigation efforts could serve as GEOSS prototype –Implementation plan correlates with the GEOSS Global Land Observing System – Land Use/Land Cover Change Initiative Several systems could meet special regional acquisition needs during some or all of the data gap period –ASTER (U.S. and Japan) –U.S. Commercial Satellites –SPOT (France) –EO-1/ALI (U.S.)

6 6 Landsat Importance to Science Change is occurring at rates unprecedented in human historyChange is occurring at rates unprecedented in human history The Landsat program provides the only inventory of the global land surface over timeThe Landsat program provides the only inventory of the global land surface over time –at a scale where human vs. natural causes of change can be differentiated –on a seasonal basis No other satellite system is capable/committed to even annual global coverage at this scaleNo other satellite system is capable/committed to even annual global coverage at this scale 1986 1997 Amazonian Deforestation 100 km Courtesy TRFIC–MSU, Houghton et al, 2000.

7 7 Landsat Impacts all GEOSS Societal Benefit Areas Natural & Human Induced Disasters Human Health & Well-Being Energy Resources Climate Variability & Change Water Resources Weather Information, Forecasting & Warning Terrestrial, Coastal & Marine Ecosystems Sustainable Agriculture & Desertification Biodiversity

8 8 Landsat 7 ETM + U.S. Global Archive and Distribution Interest in Landsat data is truly global Landsat 7 International Ground Station Network - November 2004 Number of Scenes Distributed

9 9 Landsat Data Gap Study Team Objective Recommend options, using existing and near-term capabilities, to store, maintain, and upgrade science-quality data in the National Satellite Land Remote Sensing Data Archive –Consistent with the Land Remote Sensing Policy Act of 1992 Approach Identify data “sufficiently consistent in terms of acquisition geometry, spatial resolution, calibration, coverage characteristics, and spatial characteristics with previous Landsat data…” –Consistent with Management Plan for the Landsat Program Process Identify acceptable gap-mitigation specifications Identify existing and near-term capabilities Compare capabilities to acceptable specifications Synthesize findings and make recommendations

10 10 Team Membership Edward Grigsby, NASA HQ, Co- Chair Ray Byrnes, USGS HQ, Co- Chair Garik Gutman, NASA HQ, Co- Chair Jim Irons, NASA GSFC, Community Needs Working Group Lead Bruce Quirk, USGS EDC, System Capabilities Working Group Lead Bill Stoney, Mitretek Systems, Needs-to-Capabilities Working Group Lead Vicki Zanoni, NASA HQ Detail, Team Coordinator and Synthesis Working Group Lead Mike Abrams, JPL Bruce Davis, DHS (NASA detailee) Brad Doorn, USDA FAS Fernando Echavarria, Dept. of State Stuart Frye, Mitretek Systems Mike Goldberg, Mitretek Systems Sam Goward, U. of Maryland Ted Hammer, NASA HQ Chris Justice, U. of Maryland Jim Lacasse, USGS EDC Martha Maiden, NASA HQ Dan Mandl, NASA GSFC Jeff Masek, NASA GSFC Gran Paules, NASA HQ John Pereira, NOAA/NESDIS Ed Sheffner, NASA HQ Tom Stanley, NASA SSC Woody Turner, NASA HQ Sandra Webster, NGA Diane Wickland, NASA HQ Darrel Williams, NASA GSFC

11 11 Assumptions Focus on data acquisition solutions Address DoI (USGS) responsibility to store, maintain, and upgrade science-quality data in the National Satellite Land Remote Sensing Data Archive (NSLRSDA) Assume 2007 Landsat 7 failure for purposes of planning and budgeting Landsat 5 has limited lifetime and capability OLI data available no earlier than 2010 (first NPOESS mid-morning orbit satellite) LDCM data specification used to define data quality and quantity goals Landsat 7 unrestricted data policy will serve as the model for acquired data

12 12 Requirements Analysis LDCM Data Specification (“Goal”) has been vetted by science and applications communities, and supports the range of Landsat applications Obtaining data identical to LDCM from existing systems is not possible Acceptable specifications were derived to support basic global change research given available sources of Landsat-like data: – Global mapping of land-cover – Long-term analysis of land-cover change Analysis incorporated OSTP Landsat User Survey Responses –Users require Landsat-like data (global coverage, moderate resolution, spectral coverage) –Many users already considering alternate sources of data following Landsat-7 Scan Line Corrector anomaly

13 13 Capabilities Analysis Team focused on systems that can best meet acceptable specifications –Used publicly available information to make this determination –Low and high resolution systems were not the initial study focus High resolution systems cannot meet global coverage acceptable requirement; might be source for sub-global sampling sites Low resolution systems cannot meet spatial resolution acceptable requirement Informal inquiry of commercial and foreign data providers to identify global acquisition capabilities and associated data cost estimates

14 14 IRS ResourceSat – 1, 2 (India) CBERS – 2, 2A, 3, 4 (China & Brazil) RapidEye – 1, 2, 3, 4, 5 (Germany) DMC – Algeria, Nigeria, UK, China Terra/ASTER (METI & NASA) High-resolution U.S. commercial systems –IKONOS –QuickBrid –OrbView-3 SPOT – 4, 5 (France) ALOS (JAXA) EO-1/ALI (NASA & USGS) Systems Considered

15 15 Conclusions (1) The Landsat Program is unique –Single source of systematic, global land observations –Alternate sources can reduce the impact of a Landsat data gap Data quality of potential candidate systems is unverified, however, based on preliminary analysis –India’s ResourceSat and China/Brazil’s Earth Resources Satellite (CBERS) are the leading candidates for reducing the impact of a Landsat data gap This effort could serve as a GEOSS prototype for International cooperation: –Implementation plan correlates with the GEOSS/Global Land Observing System/Land Use/Land Cover Change initiative System of systems Building upon existing systems Continuity of observations Full and open exchange of Earth observations Data quality and cross-calibration Data management standards Interoperability

16 16 Conclusions (2) Several systems could meet special regional acquisition needs during some or all of the data gap period –ASTER (U.S. and Japan) –U.S. commercial systems (sampled) –SPOT (France) –EO-1/ALI (U.S.) (sampled) Key expectations may not be met during a data gap –Data continuity / consistency –Seasonal coverage –A reliable “gold standard” for sensor cross-calibration –Rapid data acquisition and access for emergency response –Acquisition and access to data for internationally sensitive areas for national/homeland security –Directly downlink to international ground stations –U.S. 16-day repeat coverage –Price of data

17 17 Conclusions (3) There will be programmatic challenges: –Data cost and licensing Commercial prices for global coverage and/or license restrictions could be prohibitive Preference is for government-to-government sharing of data or systems –Negotiations with foreign providers and U.S. commercial companies: ResourceSat: Indian Remote Sensing (IRS) and/or Space Imaging CBERS: China and Brazil ASTER, ALOS: Japan SPOT: Spot Image Corporation and Terra Image and/or ScanEx –Uncertainty in system lifetimes and operational concepts Terra/ASTER: continued Terra operations under consideration by NASA RapidEye: entire constellation to be launched on one vehicle EO-1/ALI: probable operations through FY06

18 18 Conclusions (4) There will be technical challenges: –Receiving and archiving data from new source(s) Different formats, storage media, metadata Cataloguing data acquired along different orbits with varying scene sizes and swath widths –Data characterization and cross-calibration –Analysis/Applications of data from new source(s) Mosaicing and co-registering data from multiple sources with different spatial resolutions, registration accuracy, and scene size Differentiating land cover change from data discrepancies Developing new methodologies and algorithms incorporating data from multiple sources

19 19 Immediate Action Plan U.S. civil agencies (led by NASA, NOAA, USGS) to: –Verify data quality of candidate data sources: Complete initial analysis of ResourceSat and CBERS data sets and system capabilities –If data quality and volume are found sufficient for Landsat-like data continuity, explore agreement (s) to acquire, archive, and distribute data Further investigate other global and regional coverage candidates to better define technical capabilities, costs of data, and accessibility (SPOT, Rapid Eye, U.S. commercial firms, etc.) –Estimate budget impact for FY07-10 –If funding is available, extend operations of Landsat-like Terra/ASTER, EO- 1/ALI systems to provide immediate data insurance if L7 fails early Data quality and usefulness, costs well documented USGS already ingests, archives, distributes data

20 20 Near-Term Action Plan U.S. civil agencies coordinate data gap mitigation efforts with U.S. Group on Earth Observations –Correlate with GEOSS-Global Land Observing System Land Use/Land Cover Change elements –Complete detailed planning for International Cooperative GEOSS/GLOS/LULCC Initiative –NASA, NOAA, USGS coordinate on agency-unique capabilities –Develop plan-of-action for the compilation, validation and sharing of global land data sets: 2-yr: complete plans, processes, procedures, models, international agreements, etc. 6-yr: produce 2010 GLOS GeoCover data set (positionally accurate images of the Earth’s land cover, as in 2000 GeoCover product) 10-yr: produce 2015 GLOS GeoCover data set (including OLI data)


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