Flood susceptibility mapping in Brahmaputra floodplain of Bangladesh using deep boost, deep learning neural network, and artificial neural network-Reference-Cited by-同舟云学术

Flood susceptibility mapping in Brahmaputra floodplain of Bangladesh using deep boost, deep learning neural network, and artificial neural network

Published:2021-11-26 Issue: Volume: Page:1-22
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Ahmed Naser¹^ORCID,Hoque Muhammad Al-Amin¹²,Arabameri Alireza³^ORCID,Pal Subodh Chandra⁴^ORCID,Chakrabortty Rabin⁴^ORCID,Jui Jesmin¹

Affiliation:

1. Department of Geography and Environment, Jagannath University, Dhaka, Bangladesh

2. Centre for Advanced Modelling and Geospatial Information Systems, Faculty of Engineering and IT, The University of Technology Sydney, Ultimo, NSW, Australia

3. Department of Geomorphology, Tarbiat Modares University, Tehran, Iran

4. Department of Geography, The University of Burdwan, Bardhaman, West Bengal, India

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2021.2005698

Reference76 articles.

1. The use of watershed geomorphic data in flash flood susceptibility zoning: a case study of the Karnaphuli and Sangu river basins of Bangladesh

2. Coastal erosion vulnerability assessment along the eastern coast of Bangladesh using geospatial techniques

3. Flash flood susceptibility assessment using the parameters of drainage basin morphometry in SE Bangladesh

4. Integration of hard and soft supervised machine learning for flood susceptibility mapping

5. A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran

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