This is the authors' abstract. We don't add key points for this paper.
Several indices both conventional and satellite based are used in drought monitoring and assessment. In this study, a satellite derived Drought Severity Index (DSI) was used to monitor and assess the agricultural drought over Andhra Pradesh state, India from 2002 to 2012. The components of DSI are the Normalize Difference Vegetation Index (NDVI) and Evapotranspiration. The NDVI and evapotranspiration products of MODIS were used in this study to derive the DSI. The DSI is expected to capture the drought event that has been reported in the state between 2002 and 2012 and provide a quantitative measure of severity. The analysis showed that the DSI was having a larger variance during June due to the large variation in the onset of monsoon. The DSI variance was low in the predominantly irrigated districts. The spatial cumulative seasonal DSI captured the drought affected districts during the reported drought years. When the seasonal cumulative DSI was correlated with seasonal rainfall, it showed a strong relation with the current month rainfall in the rainfed crop growing districts. The annual DSI showed strong positive correlation with the annual Net Primary Productivity. This study clearly shows that the DSI was able to discern the drought affected regions in the state of Andhra Pradesh, India during the study period.
No takes yet. Share an insight, caveat, or question.
Chandrasekar et al. (2017) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: