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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:

Using machine learning models, remote sensing, and GIS to investigate the effects of changing climates and land uses on flood probability
Mohammadtaghi Avand, Hamidreza Moradi, Mehdi Ramazanzadeh lasboyee
Journal of Hydrology (2020) Vol. 595, pp. 125663-125663
Closed Access | Times Cited: 130

Showing 1-25 of 130 citing articles:

U-FLOOD – Topographic deep learning for predicting urban pluvial flood water depth
Roland Löwe, J. Böhm, David G. Jensen, et al.
Journal of Hydrology (2021) Vol. 603, pp. 126898-126898
Open Access | Times Cited: 142
Climate change: Strategies for mitigation and adaptation
Fang Wang, Jean Damascene Harindintwali, Ke Wei, et al.
The Innovation Geoscience (2023) Vol. 1, Iss. 1, pp. 100015-100015
Open Access | Times Cited: 119
Comprehensive Overview of Flood Modeling Approaches: A Review of Recent Advances
Vijendra Kumar, Kul Vaibhav Sharma, Tommaso Caloiero, et al.
Hydrology (2023) Vol. 10, Iss. 7, pp. 141-141
Open Access | Times Cited: 110
Modelling and quantifying tomorrow's risks from natural hazards
Gemma Cremen, Carmine Galasso, John McCloskey
The Science of The Total Environment (2021) Vol. 817, pp. 152552-152552
Open Access | Times Cited: 106
Land use and land cover classification with hyperspectral data: A comprehensive review of methods, challenges and future directions
Mohammed Abdulmajeed Moharram, Divya Meena Sundaram
Neurocomputing (2023) Vol. 536, pp. 90-113
Closed Access | Times Cited: 81
Flood susceptible prediction through the use of geospatial variables and machine learning methods
Navid Mahdizadeh Gharakhanlou, Liliana Pérez
Journal of Hydrology (2023) Vol. 617, pp. 129121-129121
Closed Access | Times Cited: 54
Adapting cities to the surge: A comprehensive review of climate-induced urban flooding
Gangani Dharmarathne, Anushka Osadhi Waduge, Madhusha Bogahawaththa, et al.
Results in Engineering (2024) Vol. 22, pp. 102123-102123
Open Access | Times Cited: 53
GIS-based machine learning algorithm for flood susceptibility analysis in the Pagla river basin, Eastern India
Nur Islam Saikh, Prolay Mondal
Natural Hazards Research (2023) Vol. 3, Iss. 3, pp. 420-436
Open Access | Times Cited: 47
A novel flood risk management approach based on future climate and land use change scenarios
Huu Duy Nguyen, Quoc‐Huy Nguyen, Dinh Kha Dang, et al.
The Science of The Total Environment (2024) Vol. 921, pp. 171204-171204
Closed Access | Times Cited: 26
DEM resolution effects on machine learning performance for flood probability mapping
Mohammadtaghi Avand, Alban Kuriqi, Majid Khazaei, et al.
Journal of Hydro-environment Research (2021) Vol. 40, pp. 1-16
Open Access | Times Cited: 104
Flood Risk Mapping by Remote Sensing Data and Random Forest Technique
Hadi Farhadi, Mohammad Najafzadeh
Water (2021) Vol. 13, Iss. 21, pp. 3115-3115
Open Access | Times Cited: 100
A systematic review of prediction methods for emergency management
Di Huang, Shuaian Wang, Zhiyuan Liu
International Journal of Disaster Risk Reduction (2021) Vol. 62, pp. 102412-102412
Open Access | Times Cited: 92
Evaluation of the effect of geographical parameters on the formation of the land surface temperature by applying OLS and GWR, A case study Shiraz City, Iran
Abdolreza Kashki, Mokhtar Karami, Rahman Zandi, et al.
Urban Climate (2021) Vol. 37, pp. 100832-100832
Closed Access | Times Cited: 75
Spatial Prediction of Future Flood Risk: An Approach to the Effects of Climate Change
Mohammadtaghi Avand, Hamid Reza Moradi, Mehdi Ramazanzadeh lasboyee
Geosciences (2021) Vol. 11, Iss. 1, pp. 25-25
Open Access | Times Cited: 65
Spatiotemporal mapping of Land Use/Land Cover dynamics using Remote Sensing and GIS approach: a case study of Prayagraj City, India (1988–2018)
Md. Omar Sarif, R. D. Gupta
Environment Development and Sustainability (2021) Vol. 24, Iss. 1, pp. 888-920
Closed Access | Times Cited: 57
Coupling machine learning and weather forecast to predict farmland flood disaster: A case study in Yangtze River basin
Zewei Jiang, Shihong Yang, Zhenyang Liu, et al.
Environmental Modelling & Software (2022) Vol. 155, pp. 105436-105436
Closed Access | Times Cited: 47
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: 43
LULC changes to riverine flooding: A case study on the Jamuna River, Bangladesh using the multilayer perceptron model
Md Mehedi Hasan, Md Sahjalal Mondol Nilay, Nahid Hossain Jibon, et al.
Results in Engineering (2023) Vol. 18, pp. 101079-101079
Open Access | Times Cited: 26
An integrated model chain for future flood risk prediction under land-use changes
Jun Liu, Junnan Xiong, Yangbo Chen, et al.
Journal of Environmental Management (2023) Vol. 342, pp. 118125-118125
Closed Access | Times Cited: 26
The Widespread Use of Remote Sensing in Asbestos, Vegetation, Oil and Gas, and Geology Applications
Leydy K. Torres Gil, David Valdelamar Martínez, Manuel Saba
Atmosphere (2023) Vol. 14, Iss. 1, pp. 172-172
Open Access | Times Cited: 23
Implication of novel hybrid machine learning model for flood subsidence susceptibility mapping: A representative case study in Saudi Arabia
Ahmed M. Al‐Areeq, Radhwan A. A. Saleh, Mustafa Ghaleb, et al.
Journal of Hydrology (2024) Vol. 630, pp. 130692-130692
Closed Access | Times Cited: 10
Recently emerging trends in big data analytic methods for modeling and combating climate change effects
Anayo Chukwu Ikegwu, Henry Friday Nweke, Emmanuel O.C. Mkpojiogu, et al.
Energy Informatics (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 10
Spatial modeling of flood probability using geo-environmental variables and machine learning models, case study: Tajan watershed, Iran
Mohammadtaghi Avand, Hamidreza Moradi, Mehdi Ramazanzadeh lasboyee
Advances in Space Research (2021) Vol. 67, Iss. 10, pp. 3169-3186
Closed Access | Times Cited: 55
Determination of flood probability and prioritization of sub-watersheds: A comparison of game theory to machine learning
Mohammadtaghi Avand, Ali Nasiri Khiavi, Majid Khazaei, et al.
Journal of Environmental Management (2021) Vol. 295, pp. 113040-113040
Closed Access | Times Cited: 52
Urban flood vulnerability assessment in a densely urbanized city using multi-factor analysis and machine learning algorithms
Farhana Parvin, Sk Ajim Ali, Beata Całka, et al.
Theoretical and Applied Climatology (2022) Vol. 149, Iss. 1-2, pp. 639-659
Closed Access | Times Cited: 36
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