Assessing Agricultural Vulnerability in India using NDVI Data Products
Keywords: Agriculture, Climate, Vegetation, Impact Analysis, Multisensor, Multiresolution, Multitemporal, National
Abstract. Impact of climate change on Indian rainfed agriculture was assessed using temporal NDVI data products from AVHRR and MODIS. Agricultural vulnerability was analysed using CV of Max NDVI from NOAA-AVHRR (15-day, 8 km) and MODIS-TERRA (16-day, 250 m) NDVI data products from 1982–2012. AVHRR dataset was found suitable for estimating regional vulnerability at state and agro-eco-sub-region (AESR) level while MODIS dataset was suitable for drawing district-level strategy for adaptation and mitigation. Methodology was developed to analyse NDVI variations with spatial pattern of rainfall using 10 X 10 girded data and spatially interpolating it to estimate Standard Precipitation Index. Study indicated large variations in vegetation dynamics across India owing to bio-climate and natural resource base. IPCC framework of vulnerability and exposure was used to identify vulnerable region extending from arid western India to semi-arid and dry sub-humid regions in central India and southern peninsula. This is a major agricultural region in the country with sizable human and livestock population with millions of marginal and small farm holdings. Exposure to climatic variability at local and regional levels have national implications and study indicated that over 122 districts extending over 110 mha was vulnerable to climate change that spread across 26 typical AESR in 11 states in India. Of the 74 mha under agriculture in the region, MODIS dataset indicated 47 mha as agriculturally vulnerable while coarser resolution of AVHRR dataset indicated a conservative estimate of 29 mha. First ever estimates of agricultural vulnerability for India indicates 20.4 to 33.1 % agricultural land under risk from climate change.