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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:

An XGBoost-SHAP approach to quantifying morphological impact on urban flooding susceptibility
Mo Wang, Yingxin Li, Haojun Yuan, et al.
Ecological Indicators (2023) Vol. 156, pp. 111137-111137
Open Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

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: 33
The Dynamic Monitoring and Driving Forces Analysis of Ecological Environment Quality in the Tibetan Plateau Based on the Google Earth Engine
Muhadaisi Airiken, Shuangcheng Li
Remote Sensing (2024) Vol. 16, Iss. 4, pp. 682-682
Open Access | Times Cited: 13
Flood risk in mountainous settlements: A new framework based on an interpretable NSGA-II-GB from a point-area duality perspective
Qihang Wu, Zhe Sun, Zhan Wang, et al.
Journal of Environmental Management (2025) Vol. 373, pp. 123842-123842
Closed Access
Interpretable flash flood susceptibility mapping in Yarlung Tsangpo River Basin using H2O Auto-ML
Fei He, Suxia Liu, Xingguo Mo, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Informing Risk Hotspots and Critical Mitigations for Rainstorms Using Machine Learning: Evidence from 268 Chinese Cities
Litiao Hu, Siqi Deng, Jixiang Ma, et al.
Environmental Science & Technology (2025)
Closed Access
Exploring sustainable consumer behaviour in retail: A teacher-student model framework for socio-economic insights
Sumit Tripathi, Roma Trigunait
Journal of Retailing and Consumer Services (2025) Vol. 84, pp. 104227-104227
Closed Access
Explainability of Machine Learning Models with XGBoost and SHAP Values in the Context of Coping with Disasters
Lucas Teixeira, Augusto de Matos, Gabriel Carvalho, et al.
Lecture notes in computer science (2025), pp. 152-166
Closed Access
Simulation and prediction of PM2.5 concentrations and analysis of driving factors using interpretable tree-based models in Shanghai, China
Wei Qing, Yongqi Chen, Huijin Zhang, et al.
Environmental Research (2025), pp. 121003-121003
Closed 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
Synergistic assessment of multi-scenario urban waterlogging through data-driven decoupling analysis in high-density urban areas: A case study in Shenzhen, China
Shiqi Zhou, Weiyi Jia, Mo Wang, et al.
Journal of Environmental Management (2024) Vol. 369, pp. 122330-122330
Closed Access | Times Cited: 4
Assessing the Impact of Urban Morphologies on Waterlogging Risk Using a Spatial Weight Naive Bayes Model and Local Climate Zones Classification
Binwei Zou, Yuanyue Nie, Rude Liu, et al.
Water (2024) Vol. 16, Iss. 17, pp. 2464-2464
Open Access | Times Cited: 3
Decoding China’s new-type industrialization: Insights from an XGBoost-SHAP analysis
Yawen Lai, Guochao Wan, Xiaoxia Qin
Journal of Cleaner Production (2024) Vol. 478, pp. 143927-143927
Open Access | Times Cited: 3
Evaluating the Utility of Selected Machine Learning Models for Predicting Stormwater Levels in Small Streams
Mariusz Starzec, Sabina Kordana
Sustainability (2024) Vol. 16, Iss. 2, pp. 783-783
Open Access | Times Cited: 2
Optical–SAR Data Fusion Based on Simple Layer Stacking and the XGBoost Algorithm to Extract Urban Impervious Surfaces in Global Alpha Cities
Muhammad Nasar Ahmad, Zhenfeng Shao, Akib Javed, et al.
Remote Sensing (2024) Vol. 16, Iss. 5, pp. 873-873
Open Access | Times Cited: 2
Exploring the impact of seasonal forest landscapes on tourist emotions using Machine learning
Zhengyan Chen, C. Ye, Honghui Yang, et al.
Ecological Indicators (2024) Vol. 163, pp. 112115-112115
Open Access | Times Cited: 2
Improving the explainability of CNN-LSTM-based flood prediction with integrating SHAP technique
Hao Huang, Zhaoli Wang, Yaoxing Liao, et al.
Ecological Informatics (2024) Vol. 84, pp. 102904-102904
Open Access | Times Cited: 2
Attribution analysis of urban social resilience differences under rainstorm disaster impact: Insights from interpretable spatial machine learning framework
Tianshun Gu, Hongbo Zhao, Yue Li, et al.
Sustainable Cities and Society (2024), pp. 106029-106029
Closed Access | Times Cited: 2
Prediction of Inland Excess Water Inundations Using Machine Learning Algorithms
Balázs Kajári, Zalán Tobak, Norbert Túri, et al.
Water (2024) Vol. 16, Iss. 9, pp. 1267-1267
Open Access | Times Cited: 1
Recognition of Longitudinal Cracks on Slab Surfaces Based on Particle Swarm Optimization and eXtreme Gradient Boosting Model
Yu Liu, Jiang Lai, Jing Shi, et al.
Processes (2024) Vol. 12, Iss. 6, pp. 1087-1087
Open Access | Times Cited: 1
Exploring Non-Linear and Synergistic Effects of Street Environment on the Spirit of Place in Historic Districts: Using Multi-Source Data and XGBoost
Shuxiao Ma, W. N. HUANG, Nana Cui, et al.
Sustainability (2024) Vol. 16, Iss. 12, pp. 5182-5182
Open Access | Times Cited: 1
Identification of Influencing Factors and Risk Assessment of Underground Space Flooding in the Mountain City
Ximin Yuan, Minrui Wu, Fuchang Tian, et al.
International Journal of Disaster Risk Reduction (2024) Vol. 113, pp. 104807-104807
Closed Access | Times Cited: 1
Investigating the influence of urban morphology on pluvial flooding: Insights from urban catchments in England (UK)
Yue Zhu, Paolo Burlando, Puay Yok Tan, et al.
The Science of The Total Environment (2024) Vol. 953, pp. 176139-176139
Open Access | Times Cited: 1
Enhancing transparency in data-driven urban pluvial flood prediction using an explainable CNN model
Weizhi Gao, Yaoxing Liao, Yuhong Chen, et al.
Journal of Hydrology (2024), pp. 132228-132228
Closed Access | Times Cited: 1
Investigating the influence of nonlinear spatial heterogeneity in urban flooding factors using geographic explainable artificial intelligence
Entong Ke, Juchao Zhao, Yaolong Zhao
Journal of Hydrology (2024), pp. 132398-132398
Closed Access | Times Cited: 1
Flood risk assessment of coastal cities based on GCW_ISODATA and explainable artificial intelligence methods
Yawen Zang, Huimin Wang, Zhenzhen Liu, et al.
International Journal of Disaster Risk Reduction (2024), pp. 105025-105025
Closed Access | Times Cited: 1
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