Mapping hailstorm damaged crop area using multispectral satellite data

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Hailstorms cause enormous physical damage in agriculture, often result in disasters leading to widespread, sudden loss in harvestable produce, and at times entire loss to grownup orchards. Accurate area-wide crop damage assessment is a challenging task to provide timely relief to farmers. This study demonstrates the feasibility of using multispectral satellite data for mapping crop-damaged area, identification of hailstreaks, their ground track attributes using NDVI difference of pre and post-hailstorm events. Crop classification within hailstreak was performed using a multispectral, high resolution LISS-IV satellite data from IRS-Resourcesat-2. Six hailstorm-damaged streaks were examined in the study area, varying in width ranging from 3 to 8 km, and length ranging from 6 to 33 km. Maximum area damaged was in grapes, followed by sugarcane and papaya. Changes in NDVI profile of different crops in the study area was recorded, and a model was developed for estimating changes in NDVI due to hail damage. The crop classification error matrix indicated Kappa Coefficient (0.55) with an overall classification accuracy of 69.6%. This study discusses the potential of high spectral, spatial and temporal resolution remote sensing data for crop damage assessment in the aftermath of the hailstorms.