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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:

Assessing urban flood disaster risk using Bayesian network model and GIS applications
Zening Wu, Yanxia Shen, Huiliang Wang, et al.
Geomatics Natural Hazards and Risk (2019) Vol. 10, Iss. 1, pp. 2163-2184
Open Access | Times Cited: 53

Showing 1-25 of 53 citing articles:

Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction
Binh Thai Pham, Abolfazl Jaafari, Mohammadtaghi Avand, et al.
Symmetry (2020) Vol. 12, Iss. 6, pp. 1022-1022
Open Access | Times Cited: 221
Assessing the scale effect of urban vertical patterns on urban waterlogging: An empirical study in Shenzhen
Yuqin Huang, Jinyao Lin, Xiaoyu He, et al.
Environmental Impact Assessment Review (2024) Vol. 106, pp. 107486-107486
Closed Access | Times Cited: 35
Urban flood disaster risk evaluation based on ontology and Bayesian Network
Zening Wu, Yanxia Shen, Huiliang Wang, et al.
Journal of Hydrology (2020) Vol. 583, pp. 124596-124596
Closed Access | Times Cited: 105
Identification of sensitivity indicators of urban rainstorm flood disasters: A case study in China
Meimei Wu, Zening Wu, Wei Ge, et al.
Journal of Hydrology (2021) Vol. 599, pp. 126393-126393
Closed Access | Times Cited: 100
Risk assessment of geohazards along Cheng-Kun railway using fuzzy AHP incorporated into GIS
Qian Zheng, Hai‐Min Lyu, Annan Zhou, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 1508-1531
Open Access | Times Cited: 63
Flood risk assessment by using an interpretative structural modeling based Bayesian network approach (ISM-BN): An urban-level analysis of Shenzhen, China
Guyuan Li, Xiaofeng Wu, Jing‐Cheng Han, et al.
Journal of Environmental Management (2022) Vol. 329, pp. 117040-117040
Closed Access | Times Cited: 37
Urban flood risk differentiation under land use scenario simulation
Hongbo Zhao, Tianshun Gu, Junqing Tang, et al.
iScience (2023) Vol. 26, Iss. 4, pp. 106479-106479
Open Access | Times Cited: 34
Know to Predict, Forecast to Warn: A Review of Flood Risk Prediction Tools
Kwesi Twum Antwi-Agyakwa, Mawuli Afenyo, Donatus Bapentire Angnuureng
Water (2023) Vol. 15, Iss. 3, pp. 427-427
Open Access | Times Cited: 22
Integrated GIS and analytic hierarchy process for flood risk assessment in the Dades Wadi watershed (Central High Atlas, Morocco)
Asmae Aichi, Mustapha Ikirri, Mohamed Ait Haddou, et al.
Results in Earth Sciences (2024) Vol. 2, pp. 100019-100019
Open Access | Times Cited: 9
Scalable and rapid building damage detection after hurricane Ian using causal Bayesian networks and InSAR imagery
Chenguang Wang, Yepeng Liu, Xiaojian Zhang, et al.
International Journal of Disaster Risk Reduction (2024) Vol. 104, pp. 104371-104371
Closed Access | Times Cited: 8
GIS-Based Comparative Study of the Bayesian Network, Decision Table, Radial Basis Function Network and Stochastic Gradient Descent for the Spatial Prediction of Landslide Susceptibility
Junpeng Huang, Sixiang Ling, Xiyong Wu, et al.
Land (2022) Vol. 11, Iss. 3, pp. 436-436
Open Access | Times Cited: 34
A Monte Carlo augmented Bayesian network approach for external flood PRAs
Joy Shen, Michelle Bensi, Mohammad Modarres
Nuclear Engineering and Design (2025) Vol. 433, pp. 113840-113840
Open Access
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
A probabilistic approach to estimating residential losses from different flood types
Dominik Paprotny, Heidi Kreibich, Oswaldo Morales‐Nápoles, et al.
Natural Hazards (2020) Vol. 105, Iss. 3, pp. 2569-2601
Open Access | Times Cited: 47
Flood Risk Assessment under Land Use and Climate Change in Wuhan City of the Yangtze River Basin, China
Zhihui Li, Keyu Song, Lu Peng
Land (2021) Vol. 10, Iss. 8, pp. 878-878
Open Access | Times Cited: 29
Key Disaster-Causing Factors Chains on Urban Flood Risk Based on Bayesian Network
Shanqing Huang, Huimin Wang, Yejun Xu, et al.
Land (2021) Vol. 10, Iss. 2, pp. 210-210
Open Access | Times Cited: 27
An integrated Bayesian networks and Geographic information system (BNs-GIS) approach for flood disaster risk assessment: A case study of Yinchuan, China
Yuwen Lu, Guofang Zhai, Shutian Zhou
Ecological Indicators (2024) Vol. 166, pp. 112322-112322
Open Access | Times Cited: 3
Built Environment Challenges Due to Climate Change
Zofia Zięba, Jolanta Dąbrowska, Marián Marschalko, et al.
IOP Conference Series Earth and Environmental Science (2020) Vol. 609, Iss. 1, pp. 012061-012061
Open Access | Times Cited: 25
Cross-sectoral preparedness and mitigation for networked typhoon disasters with cascading effects
Zhibin Hu, Guangdong Wu, Huanyu Wu, et al.
Urban Climate (2022) Vol. 42, pp. 101140-101140
Closed Access | Times Cited: 15
Emergency response inference mapping (ERIMap): A Bayesian Network-based method for dynamic observation processing
Moritz Schneider, Lukas Halekotte, Tina Comes, et al.
Reliability Engineering & System Safety (2024), pp. 110640-110640
Open Access | Times Cited: 2
Organizing Theories for Disasters into a Complex Adaptive System Framework
Annetta Burger, William G. Kennedy, Andrew Crooks
Urban Science (2021) Vol. 5, Iss. 3, pp. 61-61
Open Access | Times Cited: 15
Bayesian networks for assessment of disruption to school systems under combined hazards
Ahsana Parammal Vatteri, Dina D’Ayala, Pierre Gehl
International Journal of Disaster Risk Reduction (2022) Vol. 74, pp. 102924-102924
Open Access | Times Cited: 9
A Bayesian Network for Classifying and Predicting Ship Collision
Iis Dewi Ratih, Ketut Buda Artana, Heri Kuswanto, et al.
Lecture notes on data engineering and communications technologies (2024), pp. 403-414
Closed Access | Times Cited: 1
Unraveling the factors behind self-reported trapped incidents in the extraordinary urban flood disaster: a case study of Zhengzhou City, China
Hongbo Zhao, Yangyang Liu, Yue Li, et al.
Cities (2024) Vol. 155, pp. 105444-105444
Closed Access | Times Cited: 1
Urban risks due to climate change in the Andean municipality of Pasto, Colombia: A Bayesian network approach
Luis Carlos Ortega Chamorro, Julio Cañón
Risk Analysis (2023) Vol. 43, Iss. 10, pp. 2017-2032
Closed Access | Times Cited: 4
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