Publications

Sulla-Menashe, D; Gray, JM; Abercrombie, SP; Friedl, MA (2019). Hierarchical mapping of annual global land cover 2001 to present: The MODIS Collection 6 Land Cover product. REMOTE SENSING OF ENVIRONMENT, 222, 183-194.

Abstract
Land cover and land use maps provide an important basis for characterizing the ecological state and biophysical properties of Earth's land areas. The Collection 5 MODIS Global Land Cover Type product, initially released in 2010, was produced at annual time steps and has been widely used in the land science community. In this paper we describe refinements and improvements, in both the algorithm and the resulting map data sets, that have been implemented in the MODIS Collection 6 Global land Cover Type product. Unlike the Collection 5 product, which was based on the 17-class International Geosphere-Biosphere Programme (IGBP) legend, the Collection 6 algorithm uses a hierarchical classification model where the classes included in each level of the hierarchy reflect structured distinctions between land cover properties. The resulting suite of nested classifications is combined to create eight distinct classification schemes including the five legacy schemes included in Collection 5, and three new legends based on the FAO-Land Cover Classification System (LEGS) that distinguish between land cover, land use, and surface hydrologic state. The Collection 6 algorithm also incorporates a state-space multitemporal modeling framework based on hidden Markov models that reduce spurious land cover changes introduced by classification uncertainty in individual years. Among other changes, relative to Collection 5, the Collection 6 product includes less area mapped as forests, open shrublands, and cropland/natural vegetation mosaics, and more area mapped as woodlands and grasslands. Accuracy assessment indicates that the Collection 6 product has an overall accuracy of 73.6% for the primary LCCS layer and that the amount of spurious land cover change has been substantially reduced in Collection 6 relative to Collection 5 (1.6% in C6 and 11.4% in C5).

DOI:
10.1016/j.rse.2018.12.013

ISSN:
0034-4257