Web-enabled Landsat Data (WELD): Demonstration of MODIS-Landsat Data Fusion to Provide a Consistent, Long-term, Large-area Data Record for the Terrestrial User Community
Abstract
Consistent long-term and large-area Landsat data records are needed to monitor land cover change and study Earth system functioning. The objective of NASA’s Making Earth Science Data Records for Use in Research Environments (MEaSUREs) program is to provide Earth science data products and services driven by NASA’s Earth science goals and to advance NASA’s “missions to measurements” concept. This MEaSUREs WELD project contributes to the Land measurement theme by systematically generating radiometrically consistent Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the conterminous USA (CONUS) and Alaska. The U.S. Department of Interior / U.S. Geological Survey (USGS) has been providing terrain-corrected Landsat ETM+ data at no cost since January 2008. In the WELD project every USGS Landsat ETM+ acquisition with cloud cover less than 60% is used to generate monthly, seasonal and annual composited mosaics. The consistency and quality of the ETM+ data is improved through a fusion with standard MODIS land products, including the MODIS BRDF reflectance anisotropy product to radiometrically normalize and fill missing (cloudy and SLC-off) Landsat pixels, the MODIS atmospheric characterization data to systematically atmospherically correct the Landsat data, and the MODIS vegetation continuous field product to provide training for Landsat scale land cover characterization. The WELD mosaics are defined at 30 m and include spectral reflectance, brightness temperature, normalized difference vegetation index, the date each composited pixel was acquired on, per-band radiometric saturation status, cloud mask values, and land cover characterization information. Results for the CONUS, algorithm insights, and information on how to access the WELD data products via the internet from the USGS Landsat project are presented.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2009
- Bibcode:
- 2009AGUFMIN43C1166R
- Keywords:
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- 0434 BIOGEOSCIENCES / Data sets;
- 0480 BIOGEOSCIENCES / Remote sensing;
- 1910 INFORMATICS / Data assimilation;
- integration and fusion