MODIS land cover and LAI Collection 4 product quality across nine sites in the western hemisphere
IEEE Transactions on Geoscience and Remote Sensing
Global maps of land cover and leaf area index (LAI) derived from the Moderate Resolution Imaging Spectrometer (MODIS) reflectance data are an important resource in studies of global change, but errors in these must be characterized and well understood. Product validation requires careful scaling from ground and related measurements to a grain commensurate with MODIS products. We present an updated BigFoot project protocol for developing 25-m validation data layers over 49-km2 study areas. Results from comparisons of MODIS and BigFoot land cover and LAI products at nine contrasting sites are reported. In terms of proportional coverage, MODIS and BigFoot land cover were in close agreement at six sites. The largest differences were at low tree cover evergreen needleleaf sites and at an Arctic tundra site where the MODIS product overestimated woody cover proportions. At low leaf biomass sites there was reasonable agreement between MODIS and BigFoot LAI products, but there was not a particular MODIS LAI algorithm pathway that consistently compared most favorably. At high leaf biomass sites, MODIS LAI was generally overpredicted by a significant amount. For evergreen needleleaf sites, LAI seasonality was exaggerated by MODIS. Our results suggest incremental improvement from Collection 3 to Collection 4 MODIS products, with some remaining problems that need to be addressed
LAI, land cover, Landsat, MODIS, scaling, validation
This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
Cohen, Warren B.; Maiersperger, Thomas K.; Turner, David P.; Ritts, William D.; Pflugmacher, Dirk; Kennedy, Robert E.; Kirschbaum, Alan; Running, Steven W.; Costa, Marcos; Gower, Stith T. 2006. MODIS land cover and LAI collection 4 product quality across nine states in the western hemisphere. IEEE Transactions on Geoscience and Remote Sensing. 44(7): 1843-1857, doi: 10.1109/TGRS.2006.876026