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Agricultural sector is exposed to the risks created by the weather variables including rainfall, surface temperature, and soil moisture in the form of disasters like cyclones, drought, flood, etc. and the production related to these type of risks affects the household by affecting their income. In order to develop the agriculture and to manage risk associated with it crop insurance has an important role to play. Earlier conventional insurance method was used where the indemnities were being paid off on the basis of the loss in the crop production whereas index based insurance pays off by reading the index value. The designing of insurance becomes very challenging and also unreliable when it comes to the payouts due to the primary constraints like limited availability, poor quality, accessibility and quantity of the ground data. This paper focuses on applying time series earth observation dataset for calculating crop insurance for the state of Rajasthan. The study was carried out using, MODIS Terra NDVI 1km monthly composite (2001 to 2018), MODIS Terra LST 1km 8 days composite (2001 to 2018) for monitoring agricultural drought through Vegetation Health Indices (VHI) in Rajasthan. The CHIRPS v2.0 5.5km monthly precipitation data (2001 to 2018) was used for monitoring meteorological drought using standard precipitation index (SPI) for the state. On the basis of frequency of multiple drought condition in district with large area under drought condition was chosen for the calculation of crop insurance. CHIRPS v2.0 5.5km daily precipitation data was used for daily payout calculation according to the HDFC ERGO term sheet for the year 2012 for the selected district for major crop Bajra for the state. The results suggests that although there has not been large area suffering from moderate or severe drought in the state, 90% of cropland of the state has faced at least 4-7 years agricultural drought. Almost 10% of cropland has faced 8 -10 years of drought. The crop insurance calculation was carried out on Dholpur district which had approximately 30% of the cropland facing agricultural drought. The results show that maximum payout is during plant growth period of Bajra crop. It was found that payout had strong correlation with cumulative rainfall in sowing and growth season. The correlation in third phase was found to be mostly insignificant which required further research to investigate the reason behind it. This study uses weather based scheme for crop insurance. The future research includes considering crop yield and its relationship with both weather variables and remotely sensed vegetation indices.
Keywords: Index insurance, VHI, SPI, term sheet, agricultural drought, meteorological drought
