Title:
Assessment of tropical cyclone amphan affected inundation areas using sentinel-1 satellite data

dc.contributor.authorMukunda Dev Behera
dc.contributor.authorJaya Prakash
dc.contributor.authorSomnath Paramanik
dc.contributor.authorSujoy Mudi
dc.contributor.authorJadunandan Dash
dc.contributor.authorRoma Varghese
dc.contributor.authorPartha Sarathi Roy
dc.contributor.authorP.C. Abhilash
dc.contributor.authorAnil Kumar Gupta
dc.contributor.authorPrashant Kumar Srivastava
dc.date.accessioned2026-02-07T11:04:41Z
dc.date.issued2022
dc.description.abstractTropical cyclones as natural disturbances, influence ecosystem structure, function and dynamics at the global scale. This study assesses the inundation due to the super cyclone Amphan in coastal districts of eastern India by leveraging the computational power of Google Earth Engine (GEE) and the availability of high resolution Sentinel-1 Synthetic Aperture Radar (SAR) data. A cloud-based image processing framework was developed and implemented in GEE for classification using Random Forest algorithm. The inundation areas due to storm surge owing to cyclone Amphan, were mapped and further categorised to different land use and land cover classes based on an existing land cover map. Sentinel-1 images were useful in post-cyclone studies for the change detection analysis due to its higher temporal resolution and cloud penetration ability. The study found that the majority of agricultural and agricultural fallow lands were inundated in the coastal districts. The availability of open-source cloud-based data processing platforms provides cost effective way to rapidly gather accurate geospatial information. Such information could be useful for emergency response planning and post-event disaster management including relief, rescue and rehabilitation measures; and crop yield loss assessment. Cyclone and Land Use and Land Cover (LULC) change can have significant impacts on the human population and if both coexist, the consequences for people and the surrounding environment may be severe. © 2021, International Society for Tropical Ecology.
dc.identifier.doi10.1007/s42965-021-00187-w
dc.identifier.issn5643295
dc.identifier.urihttps://doi.org/10.1007/s42965-021-00187-w
dc.identifier.urihttps://dl.bhu.ac.in/bhuir/handle/123456789/41794
dc.publisherSpringer
dc.subjectCloud computing
dc.subjectEastern India
dc.subjectGray level co-occurrence matrix
dc.subjectLand use and land cover
dc.subjectRandom forest
dc.subjectRGB clustering
dc.titleAssessment of tropical cyclone amphan affected inundation areas using sentinel-1 satellite data
dc.typePublication
dspace.entity.typeArticle

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