Abstract
Flood is the major cause of fatalities associated with natural disasters in the world. In India especially in the state of Bihar, where about half of the area (North Bihar) gets flooded every year due to the overflow of major rivers during the rainy season. Which severely affects human lives, properties, agricultural production, farmers and their livelihood. Usually, the basins of the Kosi and Gandak rivers are known for their worst affects in Bihar. Synthetic aperture radar (SAR) is widely used for robust monitoring of flood events due to its ability to image the surface of the earth in all weather conditions. However, limited studies are available on flood patterns of Bihar and their impact on agriculture. Here, we investigated the flood extents and affected paddy rice fields for Bihar during the months of June–October (2020) using all accessible Sentinel-1 SAR and Sentinel-2 MSI images with additional supporting datasets available on the Google Earth Engine. The study showed that a large portion of Bihar (7019 km2) was submerged during monsoon season. The floodwater remains in the agricultural fields for 50 to 65 days causing severe damage to the Kharif crops, mainly rice. The extreme effect of flood was seen in agricultural lands (11.23% of the total area) and populations (15.56% of the total population) in Bihar. Satellite-based identification of flood progression and affected rice fields can be helpful for decision-makers at the time of disaster to prioritize relief and rescue operations.
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Acknowledgements
The authors would like to thank European Space Agency (ESA) for providing the SAR data in Google Earth Engine for hassle-free cloud data processing with the API code.
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Kumar, H., Karwariya, S.K. & Kumar, R. Google Earth Engine-Based Identification of Flood Extent and Flood-Affected Paddy Rice Fields Using Sentinel-2 MSI and Sentinel-1 SAR Data in Bihar State, India. J Indian Soc Remote Sens 50, 791–803 (2022). https://doi.org/10.1007/s12524-021-01487-3
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DOI: https://doi.org/10.1007/s12524-021-01487-3