Improvement of flood susceptibility mapping by introducing hybrid ensemble learning algorithms and high-resolution satellite imageries-Reference-Cited by-同舟云学术

Improvement of flood susceptibility mapping by introducing hybrid ensemble learning algorithms and high-resolution satellite imageries

Published:2023-08-05 Issue:1 Volume:119 Page:1-37
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Islam Abu Reza Md. Towfiqul,Bappi Md. Mijanur Rahman,Alqadhi Saeed,Bindajam Ahmed Ali,Mallick Javed^ORCID,Talukdar Swapan

Funder

King Khalid University

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/s11069-023-06106-7.pdf

Reference119 articles.

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3. Ahmadisharaf E, Kalyanapu AJ, Chung ES (2016) Spatial probabilistic multi-criteria decision making for assessment of flood management alternatives. J Hydrol 533:365–378

4. Akhter S, Eibek KU, Islam S, Islam ARMT, Shen S, Chu R (2019) Predicting spatiotemporal changes of channel morphology in the reach of Teesta River Bangladesh Using GIS and ARIMA Modeling. Quatern Int 513:80–94. https://doi.org/10.1016/j.quaint.2019.01.022

5. Al-Juaidi AE (2018) A simplified GIS-based SCS-CN method for the assessment of land-use change on runoff. Arab J Geosci 11(11):269

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