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OpenAlex Citation Counts

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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:

A GIS-Based Artificial Neural Network Model for Flood Susceptibility Assessment
Nanda Khoirunisa, Cheng‐Yu Ku, Chih‐Yu Liu
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 3, pp. 1072-1072
Open Access | Times Cited: 77

Showing 1-25 of 77 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: 192
Flood susceptibility mapping using machine learning boosting algorithms techniques in Idukki district of Kerala India
Subbarayan Saravanan, Devanantham Abijith, Nagireddy Masthan Reddy, et al.
Urban Climate (2023) Vol. 49, pp. 101503-101503
Closed Access | Times Cited: 57
Flood Susceptibility Assessment with Random Sampling Strategy in Ensemble Learning (RF and XGBoost)
Hancheng Ren, Bo Pang, Ping Bai, et al.
Remote Sensing (2024) Vol. 16, Iss. 2, pp. 320-320
Open Access | Times Cited: 24
Comparative study of convolutional neural network (CNN) and support vector machine (SVM) for flood susceptibility mapping: a case study at Ras Gharib, Red Sea, Egypt
Ahmed M. Youssef, Biswajeet Pradhan, Abhirup Dikshit, et al.
Geocarto International (2022) Vol. 37, Iss. 26, pp. 11088-11115
Closed Access | Times Cited: 49
Application of GIS and Machine Learning to Predict Flood Areas in Nigeria
Eseosa Halima Ighile, Hiroaki Shirakawa, Hiroki Tanikawa
Sustainability (2022) Vol. 14, Iss. 9, pp. 5039-5039
Open Access | Times Cited: 44
Computational Machine Learning Approach for Flood Susceptibility Assessment Integrated with Remote Sensing and GIS Techniques from Jeddah, Saudi Arabia
Ahmed M. Al‐Areeq, Sani I. Abba, Mohamed A. Yassin, et al.
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5515-5515
Open Access | Times Cited: 42
GIS-based flood susceptibility mapping using bivariate statistical model in Swat River Basin, Eastern Hindukush region, Pakistan
Zahid Ur Rahman, Waheed Ullah, Shibiao Bai, et al.
Frontiers in Environmental Science (2023) Vol. 11
Open Access | Times Cited: 30
Artificial neural network for flood susceptibility mapping in Bangladesh
Rhyme Rubayet Rudra, Showmitra Kumar Sarkar
Heliyon (2023) Vol. 9, Iss. 6, pp. e16459-e16459
Open Access | Times Cited: 25
Improving the model robustness of flood hazard mapping based on hyperparameter optimization of random forest
Mingyong Liao, Haijia Wen, Ling Yang, et al.
Expert Systems with Applications (2023) Vol. 241, pp. 122682-122682
Closed Access | Times Cited: 25
Solving the spatial extrapolation problem in flood susceptibility using hybrid machine learning, remote sensing, and GIS
Huu Duy Nguyen, Quoc‐Huy Nguyen, Quang‐Thanh Bui
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 12, pp. 18701-18722
Closed Access | Times Cited: 8
Artificial neural networks for flood susceptibility analysis in Gangarampur sub-division of Dakshin Dinajpur, West Bengal, India
Ankeli Paul
Frontiers in Engineering and Built Environment (2025) Vol. 5, Iss. 1, pp. 1-21
Open Access | Times Cited: 1
Using Artificial Neural Networks to Assess Earthquake Vulnerability in Urban Blocks of Tehran
Rasoul Afsari, Saman Nadizadeh Shorabeh, Amir Reza Bakhshi Lomer, et al.
Remote Sensing (2023) Vol. 15, Iss. 5, pp. 1248-1248
Open Access | Times Cited: 17
A comparative spatial analysis of flood susceptibility mapping using boosting machine learning algorithms in Rathnapura, Sri Lanka
Kumudu Madhawa Kurugama, So Kazama, Yusuke Hiraga, et al.
Journal of Flood Risk Management (2024) Vol. 17, Iss. 2
Open Access | Times Cited: 7
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
Efficiency exploration of frequency ratio, entropy and weights of evidence-information value models in flood vulnerabilityassessment: a study of raiganj subdivision, Eastern India
Sunil Saha, Debabrata Sarkar, Prolay Mondal
Stochastic Environmental Research and Risk Assessment (2021) Vol. 36, Iss. 6, pp. 1721-1742
Closed Access | Times Cited: 35
GIS-based hybrid machine learning for flood susceptibility prediction in the Nhat Le–Kien Giang watershed, Vietnam
Huu Duy Nguyen
Earth Science Informatics (2022) Vol. 15, Iss. 4, pp. 2369-2386
Closed Access | Times Cited: 27
Flood susceptibility evaluation through deep learning optimizer ensembles and GIS techniques
Romulus Costache, Alireza Arabameri, Iulia Costache, et al.
Journal of Environmental Management (2022) Vol. 316, pp. 115316-115316
Open Access | Times Cited: 23
Predicting land use effects on flood susceptibility using machine learning and remote sensing in coastal Vietnam
Van Tich Vu, Huu Duy Nguyen, Phương Lan Vu, et al.
Water Practice & Technology (2023) Vol. 18, Iss. 6, pp. 1543-1555
Open Access | Times Cited: 13
Integration of machine learning and hydrodynamic modeling to solve the extrapolation problem in flood depth estimation
Huu Duy Nguyen, Dinh Kha Dang, Nhu Y Nguyen, et al.
Journal of Water and Climate Change (2023) Vol. 15, Iss. 1, pp. 284-304
Open Access | Times Cited: 13
Navigating Cyclone Threats: A Forecast Approach Using Water Streams’ Physical Characteristics as an Indicator to Predict High Risk Potential Areas in the Sultanate of Oman
Talal Al‐Awadhi, Meshal M. Abdullah, Zahraa M. Al‐Ali, et al.
Earth Systems and Environment (2024) Vol. 8, Iss. 4, pp. 937-949
Closed Access | Times Cited: 5
A Systematic Review of Urban Flood Susceptibility Mapping: Remote Sensing, Machine Learning, and Other Modeling Approaches
Tania Islam, Ethiopia Bisrat Zeleke, Mahmud Afroz, et al.
Remote Sensing (2025) Vol. 17, Iss. 3, pp. 524-524
Open Access
Flood Susceptibility Zonation Using Geospatial Frequency Ratio and Artificial Neural Network Techniques within Himalayan Terai Region: A Comparative Exploration
Deepanjan Sen, Swarup Das, Sumon Dey, et al.
Communications in computer and information science (2025), pp. 136-148
Closed Access
Application of frequency ratio model for flood hazard zonation in the Dikhow River basin, Northeast India
Anannya Panging, Srinivasa Rao Koduru, A. Simhachalam, et al.
Natural Hazards (2025)
Closed Access
Assessing Flood Susceptibility Using GIS and AHP Method: Case of Mandovi River Basin, Goa
Raj Rajeev, Subrat Naik, N. Nivedha
Springer geography (2025), pp. 71-97
Closed Access
Remote-Sensing-Based Prioritization of Post-Fire Restoration Actions in Mediterranean Ecosystems: A Case Study in Cyprus
Μαρία Προδρόμου, Ioannis Z. Gitas, Christodoulos Mettas, et al.
Remote Sensing (2025) Vol. 17, Iss. 7, pp. 1269-1269
Open Access
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