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Assessment of the NASA-USGS Global Land Survey (GLS) Datasets

July 1, 2013

The Global Land Survey (GLS) datasets are a collection of orthorectified, cloud-minimized Landsat-type satellite images, providing near complete coverage of the global land area decadally since the early 1970s. The global mosaics are centered on 1975, 1990, 2000, 2005, and 2010, and consist of data acquired from four sensors: Enhanced Thematic Mapper Plus, Thematic Mapper, Multispectral Scanner, and Advanced Land Imager. The GLS datasets have been widely used in land-cover and land-use change studies at local, regional, and global scales. This study evaluates the GLS datasets with respect to their spatial coverage, temporal consistency, geodetic accuracy, radiometric calibration consistency, image completeness, extent of cloud contamination, and residual gaps. In general, the three latest GLS datasets are of a better quality than the GLS-1990 and GLS-1975 datasets, with most of the imagery (85%) having cloud cover of less than 10%, the acquisition years clustered much more tightly around their target years, better co-registration relative to GLS-2000, and better radiometric absolute calibration. Probably, the most significant impediment to scientific use of the datasets is the variability of image phenology (i.e., acquisition day of year). This paper provides end-users with an assessment of the quality of the GLS datasets for specific applications, and where possible, suggestions for mitigating their deficiencies.

Publication Year 2013
Title Assessment of the NASA-USGS Global Land Survey (GLS) Datasets
DOI 10.1016/j.rse.2013.02.026
Authors Garik Gutman, Chengquan Huang, Gyanesh Chander, Praveen Noojipady, Jeffery G. Masek
Publication Type Article
Publication Subtype Journal Article
Series Title Remote Sensing of Environment
Index ID 70041208
Record Source USGS Publications Warehouse
USGS Organization Earth Resources Observation and Science (EROS) Center