Satellite-based assessment of hailstorm-affected potato crop for insurance purpose

Abstract

Assessing the extent of hailstorm affected crop is one of the thrust areas for quantifying mid-season adversaries under crop insurance values chain. This study evaluated the preand post-hailstorm responses on spectral bands and vegetation indices derived from Sentinel-2 data for assessing the severity class of the affected potato crop. The potato crop was mapped using pre-event satellite data with overall accuracy of 88% (k=0.82).Pair-wise Games-Howell t-test showed significant differences among the post-hailstorm potato severity classes in Red, Near Infrared & Short-wave Infra-red (SWIR) bands and Normalized vegetation indices. Percentage change (from pre-to post-event) in band reflectance and vegetation indices showed a better sensitivity in differentiating damage severity. Differential behaviour of SWIR-1 (Band-11) and SWIR-2 (Band-12) were observed within severely affected potato crop under dry and wet soil conditions. Decision matrix based on percentage change in Normalized difference Vegetation Index (DNDVI)and Normalized difference Tillage Index (DNDVI) could able to capture the damage severity classes with an overall accuracy of 86.7%. Higher proportion of affected area were found to be associated with larger percentage of Potato yield reduction based on measured yield data at Insurance unit level. The proposed methodology could be adopted for operational assessment of the impact of hailstorm events on crops.