Application of MODIS time series data for drought assessment in the East China

Drought is one of the major environmental disasters in China, so it is very important to detect and monitor drought periodically at large scale for decision making. This study focuses on combining information from visible, near infrared, and short wave infrared channels of MODIS to improve sensitivity to drought severity. Significant correlations have been found between DVI/NMDI values and precipitation/soil moisture data in individual stations. It was confirmed that both NDVI and NMDI indices could be used to monitor drought in the study area at a regional scale. However, NMDI had a slightly higher correlation with soil moisture or precipitation than NDVI, which suggests that NMDI variations can be a good indicator of water changes and in turn, the drought conditions in individual stations in the study area. Results from analysis of time series NDVI and NDWI data over the study area also indicate that NMDI was more sensitive than NDVI to drought conditions. Future efforts are being need to more fully exploit the potential of NMDI as an active drought-monitoring tool for different geographic regions, climates, and multiple spatial scales.