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Global surface reflectance products from Landsat, with validation against coincident MODIS measurements

Joseph Owen Sexton, University of Maryland - GLCF, jsexton@umd.edu (Presenter)
Min Feng, University of Maryland - GLCF, feng.tank@gmail.com
Chengquan Huang, University of Maryland, cqhuang@umd.edu
Jeffrey Masek, NASA GSFC, jeffrey.g.masek@nasa.gov
Eric Vermote, University of Maryland, eric@ltdri.org
Feng Gao, NASA GSFC/ERT Inc., fgao@ltpmail.gsfc.nasa.gov
Raghuram Narasimhan, University of Maryland - GLCF, raghu28@umd.edu
Saurabh Channan, UMD / GLCF, schannan@umiacs.umd.edu
John R. Townshend, University of Maryland, jtownshe@umd.edu

Global, long-term monitoring of changes in Earth’s land surface requires quantitative comparisons of satellite images acquired under widely varying atmospheric conditions. Although physically based estimates of surface reflectance (SR) ultimately provide the most accurate representation of Earth’s surface properties, there has never been a globally consistent SR dataset at the scale of Landsat. To increase the consistency and robustness of Landsat-based land cover monitoring, we atmospherically corrected the USGS Global Land Survey (GLS) dataset using the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) implementation of the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model and validated the data for GLS 2000 and 2005 epochs relative to coincident Moderate Resolution Imaging Spectroradiometer (MODIS) daily SR and Normalized Bidirectional Distribution Function-Adjusted Reflectance (NBAR) measurements. Accuracy with respect to MODIS SR and NBAR data is very high, with overall discrepancies (Root-Mean-Squared Deviation (RMSD)) between 1.2 and 2.3 percent reflectance for Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and between 1.5-3.0 percent reflectance for Landsat-5 Thematic Mapper (TM). SR datasets for 1975 and 1990 epochs are now in production as well, and this new repository of surface measurements will provide consistent, calibrated, multi-decadal image data for robust land cover change detection and monitoring across the Earth sciences.

Presentation: 2011_Poster_Sexton_80_197.pdf (30417k)

Presentation Type:  Poster

Session:  Coupled Processes at Land-Atmosphere-Ocean Interfaces   (Mon 4:00 PM)

Associated Project(s): 

  • Related Activity

Poster Location ID: 80

 


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