Early season prevented and failed rice sowing detection using temporal Synthetic Aperture Radar data in coastal India for crop insurance applications
Deiveegan Murugesan | Renaud Mathieu
Droughts and floods are threats to rice production in coastal India. To mitigate these, India implements the Pradhan Mantri Fasal Bima Yojana (PMFBY) crop insurance. Adoption remains low due to disputes/delays in damage assessments and claim settlements. Thus, the government promotes remote sensing technology to expedite payouts. Here we conducted a study in Odisha, India, where early season flash floods that frequently submerge rice fields for over two weeks and result in losses through prevented/failed sowing (P/FS). We propose a systematic approach to analyse near real-time early season P/FS losses and provide objective and accurate evidence within the PMFBY timeline. We utilized radar Sentinel-1 time series to map prolonged flood conditions before the PMFBY cut-off date for claiming P/FS status. P/FS conditions were correctly detected at 92.3%, with a slight omission and small risk of misclassification of normal rice as P/FS. About 6,471 and 4,194 ha of rice area were detected under P/FS during the wet seasons of 2018 and 2019, while 37% and 4% of the insurance units were eligible for claims. The radar backscatter allowed discrimination of P/FS from normal rice-growing areas since flooding decreased the backscatter due to the absence of post-inundation crop growth. This approach can potentially improve the accuracy and speed of claim processing while minimizing costly field surveys. Leveraging open-source satellite data and fostering strategic partnerships, the claims process can be enhanced and benefiting both farmers and insurance stakeholders.
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