Remotely sensed estimation of cropland in China: a comparison of the maps derived from four global land cover datasets

Four satellite-derived global land cover datasets with 1 km(2) pixel resolution are currently freely available: the University of Maryland Dataset (UMD), the International Geosphere-Biosphere Programme Data and Information System Cover (IGBP-DISCover), the Moderate Resolution Imaging Spectrometer (MODIS) dataset, and the Global Land Cover 2000 (GLC2000). Although produced primarily for global applications, these global land cover datasets are often used for national or regional applications. The objective of this study was to examine the similarities and differences between these datasets in mapping Chinese cropland and to highlight their strengths and weaknesses when used at the national and regional scales. First, the total areas (in ha) of the cropland mapped by the four datasets were compared at the Chinese national, regional, and provincial levels. Second, we performed a pixel-by-pixel comparison of the spatial locations of cropland mapped by the four datasets. These datasets were then separately compared with the Chinese 1996 National Land Survey Dataset (NLSD-1996) to assess their accuracy in cropland mapping. The results show that, despite some agreement, there are discrepancies between the datasets, and the type and extent varies between regions. There are many reasons for the discrepancies, the main ones being the diverse land cover classification schemes, coarse spatial resolution, per-pixel classification approach, and landscape heterogeneity.