Application of LISS III and MODIS-derived vegetation indices for assessment of micro-level agricultural drought

Drought in recent years has crippled the livelihoods of millions of people living in India and has also been the cause of many deaths. Puruliya district, India with more than one-third of its population belonging to the backward community has no proper agricultural drought management system. In this study, spatial and temporal characteristics of agricultural drought were examined using indices derived from Indian Remote Sensing (IRS) Linear Imaging Self Scanning (LISS III) sensor and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensor satellite images. MODIS Normalized Difference Vegetation Index (NDVI) results almost match with the results obtained from LISS III NDVI analysis. Vegetation Condition Index (VCI) was prepared from MODIS for a period of 16 years (2000-2016) and subsequently blockwise drought severity maps were generated from MODIS-derived VCI for Kharif and Rabi season. MODIS VCI analysis shows that nearly 34.1% and 76.5% of the study area for Kharif and Rabi season respectively faces drought conditions during the recent year 2015-16. It also shows severe and extreme drought situations for the years 2010-11 and 2005-06 respectively. Blockwise drought severity analysis reveals that Jaipur, Purulia I, Purulia II and Para blocks were chronically drought prone areas. The results indicate significant agreement between NDVI anomaly obtained from MODIS sensor and foodgrain anomaly obtained from crop yield statistics. The outcome of the research may be used for the district's drought preparedness programme so that proper crop planning and management can be carried out to help in agricultural production. (C) 2019 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V.