Assessing the influence of floods over selected states of Eastern India with cloud-based geo-computing platforms

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Abstract
Satellite-based remote sensing datasets are suitable for various applications including real-time flood intensity, progression, and deterioration monitoring. Google Earth Engine (GEE) has emerged as a leading cloud-based geo-computing platform for large-scale geoprocessing tools to offer higher computational speed through Google’s servers. It offers a unique platform for processing a variety of datasets without downloading raw imagery through the code editor. The cloud-based computing platforms offer a capability of real-time data for processing with space-based inputs. This platform facilitates customized algorithms with customized codes to perform the analysis on multiple datasets to generate the results. The study elucidates the geo-processing of large-scale remote sensing datasets in a cloud-based computing platform with the adapted algorithms and codes. It assesses and analyses the impact of floods over settlements, agricultural fields, vegetation cover, and other features in the selected parts of eastern India containing West Bengal, Bihar, and Jharkhand. The effect on vegetation cover is evaluated with satellite-derived indices containing normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) with proper validation. The outcomes are available with the area statistics and flood maps to visualize the damages across the settlements, agricultural fields, and vegetation cover. These will help policymakers to undertake precautionary measures for disaster management. Furthermore, analogous work can be replicated to quantity the flood-inundated areas with precise scale to offer quicker responses with optimal utilization of resources.

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