Modeling of impact assessment of super cyclone Amphan with machine learning algorithms in Sundarban Biosphere Reserve, India
Author:
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology
Link
https://link.springer.com/content/pdf/10.1007/s11069-023-05935-w.pdf
Reference83 articles.
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3. Akber M, Patwary MM, Islam M, Rahman MR (2018) Storm protection service of the Sundarbans mangrove forest, Bangladesh. Nat Hazards 94(1):405–418
4. Alam A, Bhat MS, Maheen M (2020) Using Landsat satellite data for assessing the land use and land cover change in Kashmir valley. GeoJournal 85:1529–1543
5. Ali SA, Khatun R, Ahmad A, Ahmad SN (2020) Assessment of cyclone vulnerability, hazard evaluation and mitigation capacity for analyzing cyclone risk using GIS technique: a study on Sundarban Biosphere Reserve, India. Earth Syst Environ 4:71–92
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