Landscape-scale characterization of cropland in China using Vegetation and Landsat TM images

In this landscape-scale study we explored the potential for multi-temporal 10-day composite data from the Vegetation sensor to characterize land cover types, in combination with Landsat TM image and agricultural census data. The study area (175 km by 165 km) is located in eastern Jiangsu Province, China. The Normalized DiVerence Vegetation Index (NDVI) and the Normalized DiVerence Water Index (NDWI) were calculated for seven 10-day composite (VGT-S10) data from 11 March to 20 May 1999. Multi-temporal NDVI and NDWI were visually examined and used for unsupervised classi cation. The resultant VGT classi cation map at 1km resolution was compared to the TM classi cation map derived from unsupervised classi cation of a Landsat 5 TM image acquired on 26 April 1996 at 30m resolution to quantify percent fraction of cropland within a 1 km VGT pixel; resulting in a mean of 60 % for pixels classi ed as cropland, and 47 % for pixels classi ed as cropland/natural vegetation mosaic. The estimates of cropland area from VGT data and TM image were also aggregated to county-level, using an administrative county map, and then com-pared to the 1995 county-level agricultural census data. This landscape-scale analysis incorporated image classi cation (e.g. coarse-resolution VGT data, ne-resolution TM data), statistical census data (e.g. county-level agricultural census data) and a geographical information system (e.g. an administrative county map), and demonstrated the potential of multi-temporal VGT data for mapping of croplands across various spatial scales from landscape to region. This analysis also illustrated some of the limitations of per-pixel classi cation at the 1 km resolution for a heterogeneous landscape. 1.