Impact Of Cyclone Jawad On Potato Crops In Purba Bardhaman: Insights For Crop Insurance Using Optical And Microwave Remote Sensing

Cyclone Jawad, which struck in December 2021, caused significant damage to potato crops in Purba Bardhaman, West Bengal, leading to substantial economic losses for farmers. This study utilizes Sentinel-1 SAR and Sentinel-2 optical data to map the extent of inundation in potato fields during the 2021-2022 rabi season. A decision tree classification based on NDVI thresholds was used to delineate potato-growing areas, and the spatial extent of inundation was mapped using SAR data. High inundation levels were observed in blocks like Ausgram-I and II, Bhatar, and Mongolkote, where over $20 \%$ of potato areas were affected. This extensive inundation necessitated crop resowing and delayed the growth cycle, further increasing production costs and affecting harvest timings. The study highlights the importance of remote sensing in accurately assessing detailed block-wise (thirdlevel administrative unit) crop inundation, and that can be informed to insurance schemes, thereby enhancing agricultural resilience to cyclonic storms.

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Published
2024-12-02
DOI
https://doi.org/10.1109/ingarss61818.2024.10984010
Primary Topic
Potato Plant Research
Type
article
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article

Impact Of Cyclone Jawad On Potato Crops In Purba Bardhaman: Insights For Crop Insurance Using Optical And Microwave Remote Sensing

Dheeraj Mondal, Debolina Sarkar, Manoj Kumar Nanda, Momsona Mondal
Potato Plant Research
article

Impact Of Cyclone Jawad On Potato Crops In Purba Bardhaman: Insights For Crop Insurance Using Optical And Microwave Remote Sensing

Dheeraj Mondal, Debolina Sarkar, Manoj Kumar Nanda, Momsona Mondal
article en

Abstract

Cyclone Jawad, which struck in December 2021, caused significant damage to potato crops in Purba Bardhaman, West Bengal, leading to substantial economic losses for farmers. This study utilizes Sentinel-1 SAR and Sentinel-2 optical data to map the extent of inundation in potato fields during the 2021-2022 rabi season. A decision tree classification based on NDVI thresholds was used to delineate potato-growing areas, and the spatial extent of inundation was mapped using SAR data. High inundation levels were observed in blocks like Ausgram-I and II, Bhatar, and Mongolkote, where over $20 \%$ of potato areas were affected. This extensive inundation necessitated crop resowing and delayed the growth cycle, further increasing production costs and affecting harvest timings. The study highlights the importance of remote sensing in accurately assessing detailed block-wise (thirdlevel administrative unit) crop inundation, and that can be informed to insurance schemes, thereby enhancing agricultural resilience to cyclonic storms.

Bidhan Chandra Krishi Viswavidyalaya (IN)
Zero hunger
Openalex Percentile: Top 64%
Potato Plant Research
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