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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Flash-flood hazard susceptibility mapping in Kangsabati River Basin, India
Rabin Chakrabortty, Subodh Chandra Pal, Fatemeh Rezaie, et al.
Geocarto International (2021) Vol. 37, Iss. 23, pp. 6713-6735
Closed Access | Times Cited: 78

Showing 1-25 of 78 citing articles:

Deep learning methods for flood mapping: a review of existing applications and future research directions
Roberto Bentivoglio, Elvin Isufi, Sebastiaan N. Jonkman, et al.
Hydrology and earth system sciences (2022) Vol. 26, Iss. 16, pp. 4345-4378
Open Access | Times Cited: 203
Predicting future urban waterlogging-prone areas by coupling the maximum entropy and FLUS model
Jinyao Lin, Peiting He, Liu Yang, et al.
Sustainable Cities and Society (2022) Vol. 80, pp. 103812-103812
Closed Access | Times Cited: 148
A comparative assessment of flood susceptibility modelling of GIS-based TOPSIS, VIKOR, and EDAS techniques in the Sub-Himalayan foothills region of Eastern India
Rajib Mitra, Jayanta Das
Environmental Science and Pollution Research (2022) Vol. 30, Iss. 6, pp. 16036-16067
Closed Access | Times Cited: 77
Flash-flood hazard using deep learning based on H2O R package and fuzzy-multicriteria decision-making analysis
Romulus Costache, Tran Trung Tin, Alireza Arabameri, et al.
Journal of Hydrology (2022) Vol. 609, pp. 127747-127747
Closed Access | Times Cited: 75
Evaluating the association between morphological characteristics of urban land and pluvial floods using machine learning methods
Jinyao Lin, Wenli Zhang, Youyue Wen, et al.
Sustainable Cities and Society (2023) Vol. 99, pp. 104891-104891
Closed Access | Times Cited: 50
Threats of climate change and land use patterns enhance the susceptibility of future floods in India
Subodh Chandra Pal, Indrajit Chowdhuri, Biswajit Das, et al.
Journal of Environmental Management (2021) Vol. 305, pp. 114317-114317
Closed Access | Times Cited: 78
A GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level
Laxmi Gupta, Jagabandhu Dixit
Geocarto International (2022) Vol. 37, Iss. 26, pp. 11867-11899
Open Access | Times Cited: 54
A practical approach to flood hazard, vulnerability, and risk assessing and mapping for Quang Binh province, Vietnam
Hang Ha, Quynh Duy Bui, Huy Nguyen, et al.
Environment Development and Sustainability (2022) Vol. 25, Iss. 2, pp. 1101-1130
Closed Access | Times Cited: 52
Flood susceptibility mapping of Northeast coastal districts of Tamil Nadu India using Multi-source Geospatial data and Machine Learning techniques
Subbarayan Saravanan, Devanantham Abijith
Geocarto International (2022) Vol. 37, Iss. 27, pp. 15252-15281
Closed Access | Times Cited: 46
A comparative assessment of multi-criteria decision-making analysis and machine learning methods for flood susceptibility mapping and socio-economic impacts on flood risk in Abela-Abaya floodplain of Ethiopia
Muluneh Legesse Edamo, Tigistu Yisihak Ukumo, Tarun Kumar Lohani, et al.
Environmental Challenges (2022) Vol. 9, pp. 100629-100629
Open Access | Times Cited: 39
Development of a new integrated flood resilience model using machine learning with GIS-based multi-criteria decision analysis
Muhammad Hussain, Muhammad Tayyab, Kashif Ullah, et al.
Urban Climate (2023) Vol. 50, pp. 101589-101589
Closed Access | Times Cited: 34
Living with Floods Using State-of-the-Art and Geospatial Techniques: Flood Mitigation Alternatives, Management Measures, and Policy Recommendations
Rabin Chakrabortty, Subodh Chandra Pal, Dipankar Ruidas, et al.
Water (2023) Vol. 15, Iss. 3, pp. 558-558
Open Access | Times Cited: 29
Flood susceptibility mapping using AutoML and a deep learning framework with evolutionary algorithms for hyperparameter optimization
Amala Mary Vincent, Parthasarathy Kulithalai Shiyam Sundar, P. Jidesh
Applied Soft Computing (2023) Vol. 148, pp. 110846-110846
Closed Access | Times Cited: 25
Flash Flood Susceptibility Modelling Using Soft Computing-Based Approaches: From Bibliometric to Meta-Data Analysis and Future Research Directions
Gilbert Hinge, Mohamed A. Hamouda, Mohamed Mostafa Mohamed
Water (2024) Vol. 16, Iss. 1, pp. 173-173
Open Access | Times Cited: 12
Improving flood hazard susceptibility assessment by integrating hydrodynamic modeling with remote sensing and ensemble machine learning
Izhar Ahmad, Rashid Farooq, Muhammad Ashraf, et al.
Natural Hazards (2025)
Open Access | Times Cited: 1
A Revolutionary Hybridised MCDM Approach on Geographic Information System for Evaluation of Flood Risk in Subarnarekha River Basin, India
Sipra Mophapatra, Dillip K. Ghose, Deba Prakash Satapathy
Geological Journal (2025)
Closed Access | Times Cited: 1
Development of geo-environmental factors controlled flash flood hazard map for emergency relief operation in complex hydro-geomorphic environment of tropical river, India
Dipankar Ruidas, Asish Saha, Abu Reza Md. Towfiqul Islam, et al.
Environmental Science and Pollution Research (2022) Vol. 30, Iss. 49, pp. 106951-106966
Closed Access | Times Cited: 35
Integration of RS-GIS with Frequency Ratio, Fuzzy Logic, Logistic Regression and Decision Tree Models for Flood Susceptibility Prediction in Lower Gangetic Plain: A Study on Malda District of West Bengal, India
Abhishek Ghosh, Priyanka Dey, Tirthankar Ghosh
Journal of the Indian Society of Remote Sensing (2022) Vol. 50, Iss. 9, pp. 1725-1745
Closed Access | Times Cited: 32
A hybrid integration of analytical hierarchy process (AHP) and the multiobjective optimization on the basis of ratio analysis (MOORA) for landslide susceptibility zonation of Aizawl, India
Jonmenjoy Barman, Brototi Biswas, K. Srinivasa Rao
Natural Hazards (2024) Vol. 120, Iss. 9, pp. 8571-8596
Closed Access | Times Cited: 8
Flood hazard forecasting and management systems: A review of state-of-the-art modelling, management strategies and policy-practice gap
Dipankar Ruidas, Subodh Chandra Pal, Asish Saha, et al.
International Journal of Disaster Risk Reduction (2024) Vol. 108, pp. 104539-104539
Closed Access | Times Cited: 7
A novel hybrid GIS ‐based multi‐criteria decision‐making approach for flood susceptibility analysis in large ungauged watersheds
Roya Sahraei, Yousef Kanani‐Sadat, Saeid Homayouni, et al.
Journal of Flood Risk Management (2022) Vol. 16, Iss. 2
Open Access | Times Cited: 27
Deep Learning Methods for Flood Mapping: A Review of Existing Applications and Future Research Directions
Roberto Bentivoglio, Elvin Isufi, Sebastiaan N. Jonkman, et al.
(2022)
Open Access | Times Cited: 24
Estimating potential illegal land development in conservation areas based on a presence-only model
Jinyao Lin, Hua Li, Yijuan Zeng, et al.
Journal of Environmental Management (2022) Vol. 321, pp. 115994-115994
Closed Access | Times Cited: 23
Spatial Mapping of Flood Susceptibility Using Decision Tree–Based Machine Learning Models for the Vembanad Lake System in Kerala, India
Parthasarathy Kulithalai Shiyam Sundar, Subrahmanya Kundapura
Journal of Water Resources Planning and Management (2023) Vol. 149, Iss. 10
Closed Access | Times Cited: 15
Flood susceptibility mapping with ensemble machine learning: a case of Eastern Mediterranean basin, Türkiye
Hüseyin Baran Özdemir, Müsteyde Baduna Koçyiğit, Diyar Akay
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 11, pp. 4273-4290
Closed Access | Times Cited: 14
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