Monitoring Global Land Surface Drought Severity by Multi-Sensors Remote Sensing Data

In the context of global warming, persistent droughts may cause adverse impacts on ecosystems and human societies. Although several multi-source satellite remote sensing records and types of drought indices exist, detection of droughts at regional to global scales remains a challenge. On the basis of precipitation data of the Tropical Rainfall Measuring Mission (TRMM) used to quantify rainfall anomalies and the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index and land surface data used to reflect vegetation growth anomalies, this study develops a Multi-sensor Drought Severity Index (MDSI) to accurately monitor meteorological drought events at almost the global scale (50°S-50°N, 0°-180°-0°). These events include the 2005 and 2010 droughts in the Amazon; the 2006 drought in Chongqing, China; the 2010 drought in Yunnan, China; the 2011 drought in the eastern Africa; and the 2012 drought in the central parts of America. The spatial distribution patterns of the drought and flood events of the MDSI are essentially the same as those of the Palmer Drought Severity Index (PDSI). Therefore, the MDSI is useful for detecting drought conditions in humid areas.