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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 GIS, Remote Sensing, and Machine Learning to Highlight the Correlation between the Land-Use/Land-Cover Changes and Flash-Flood Potential
Romulus Costache, Quoc Bao Pham, Ema Corodescu-Roșca, et al.
Remote Sensing (2020) Vol. 12, Iss. 9, pp. 1422-1422
Open Access | Times Cited: 65

Showing 1-25 of 65 citing articles:

GIS-based comparative assessment of flood susceptibility mapping using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and logistic regression: A case of Topľa basin, Slovakia
Sk Ajim Ali, Farhana Parvin, Quoc Bao Pham, et al.
Ecological Indicators (2020) Vol. 117, pp. 106620-106620
Open Access | Times Cited: 264
Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms
Swapan Talukdar, Bonosri Ghose, Shahfahad, et al.
Stochastic Environmental Research and Risk Assessment (2020) Vol. 34, Iss. 12, pp. 2277-2300
Closed Access | Times Cited: 184
Using artificial intelligence and data fusion for environmental monitoring: A review and future perspectives
Yassine Himeur, Bhagawat Rimal, Abhishek Tiwary, et al.
Information Fusion (2022) Vol. 86-87, pp. 44-75
Closed Access | Times Cited: 138
Application of genetic algorithm in optimization parallel ensemble-based machine learning algorithms to flood susceptibility mapping using radar satellite imagery
Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki, Myoung-Bae Seo, et al.
The Science of The Total Environment (2023) Vol. 873, pp. 162285-162285
Closed Access | Times Cited: 49
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
Flood susceptibility mapping through geoinformatics and ensemble learning methods, with an emphasis on the AdaBoost-Decision Tree algorithm, in Mazandaran, Iran
Maryam Jahanbani, Mohammad H. Vahidnia, Hossein Aghamohammadi, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 2, pp. 1433-1457
Closed Access | Times Cited: 18
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
Comparison of multi-criteria-analytical hierarchy process and machine learning-boosted tree models for regional flood susceptibility mapping: a case study from Slovakia
Matej Vojtek, Jana Vojteková, Romulus Costache, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 1153-1180
Open Access | Times Cited: 73
An Efficient Approach Based on Privacy-Preserving Deep Learning for Satellite Image Classification
Munirah Alkhelaiwi, Wadii Boulila, Jawad Ahmad, et al.
Remote Sensing (2021) Vol. 13, Iss. 11, pp. 2221-2221
Open Access | Times Cited: 72
High-Resolution Hydrological-Hydraulic Modeling of Urban Floods Using InfoWorks ICM
Lariyah Mohd Sidek, Aminah Shakirah Jaafar, Wan Hazdy Azad Wan Abdul Majid, et al.
Sustainability (2021) Vol. 13, Iss. 18, pp. 10259-10259
Open Access | Times Cited: 69
Spatiotemporal Monitoring of Urban Sprawl in a Coastal City Using GIS-Based Markov Chain and Artificial Neural Network (ANN)
Shawky Mansour, Eman Ghoneim, Asmaa El-Kersh, et al.
Remote Sensing (2023) Vol. 15, Iss. 3, pp. 601-601
Open Access | Times Cited: 30
New neural fuzzy-based machine learning ensemble for enhancing the prediction accuracy of flood susceptibility mapping
Romulus Costache, Roxana Ţîncu, Ismail Elkhrachy, et al.
Hydrological Sciences Journal (2020) Vol. 65, Iss. 16, pp. 2816-2837
Closed Access | Times Cited: 65
Rainfall induced landslide susceptibility mapping using novel hybrid soft computing methods based on multi-layer perceptron neural network classifier
Mehebub Sahana, Binh Thai Pham, Manas Shukla, et al.
Geocarto International (2020) Vol. 37, Iss. 10, pp. 2747-2771
Closed Access | Times Cited: 56
Predicting Future Urban Flood Risk Using Land Change and Hydraulic Modeling in a River Watershed in the Central Province of Vietnam
Huu Duy Nguyen, Dennis Fox, Dinh Kha Dang, et al.
Remote Sensing (2021) Vol. 13, Iss. 2, pp. 262-262
Open Access | Times Cited: 52
Development of a novel hybrid multi-boosting neural network model for spatial prediction of urban flood
Hamid Darabi, Omid Rahmati, Seyed Amir Naghibi, et al.
Geocarto International (2021) Vol. 37, Iss. 19, pp. 5716-5741
Open Access | Times Cited: 47
Investigating the spatial distribution of flood inundation and landforms using topographic position index (TPI) and geomorphon-based automated landform classification methods
Laxmi Gupta, Jagabandhu Dixit
Journal of Earth System Science (2024) Vol. 133, Iss. 3
Closed Access | Times Cited: 7
Flash-flood propagation susceptibility estimation using weights of evidence and their novel ensembles with multicriteria decision making and machine learning
Romulus Costache, Quoc Bao Pham, Alireza Arabameri, et al.
Geocarto International (2021) Vol. 37, Iss. 25, pp. 8361-8393
Closed Access | Times Cited: 40
Machine-learning and HEC-RAS integrated models for flood inundation mapping in Baro River Basin, Ethiopia
Habtamu Tamiru, Meseret Wagari
Modeling Earth Systems and Environment (2021) Vol. 8, Iss. 2, pp. 2291-2303
Open Access | Times Cited: 37
A Survey of Remote Sensing and Geographic Information System Applications for Flash Floods
Linxian Ding, Lei Ma, Longguo Li, et al.
Remote Sensing (2021) Vol. 13, Iss. 9, pp. 1818-1818
Open Access | Times Cited: 34
Sentinel‐1 remote sensing data and Hydrologic Engineering Centres River Analysis System two‐dimensional integration for flash flood detection and modelling in New Cairo City, Egypt
Ismail Elkhrachy, Quoc Bao Pham, Romulus Costache, et al.
Journal of Flood Risk Management (2021) Vol. 14, Iss. 2
Open Access | Times Cited: 33
Comparison of ANN model and GIS tools for delineation of groundwater potential zones, Fincha Catchment, Abay Basin, Ethiopia
Habtamu Tamiru, Meseret Wagari
Geocarto International (2021) Vol. 37, Iss. 23, pp. 6736-6754
Closed Access | Times Cited: 33
Developing flood mapping procedure through optimized machine learning techniques. Case study: Prahova river basin, Romania
Daniel Constantin Diaconu, Romulus Costache, Abu Reza Md. Towfiqul Islam, et al.
Journal of Hydrology Regional Studies (2024) Vol. 54, pp. 101892-101892
Open Access | Times Cited: 5
Evaluating the effects of climate and land use change on the future flood susceptibility in the central region of Vietnam by integrating land change modeler, machine learning methods
Huu Duy Nguyen, Dinh Kha Dang, Quoc‐Huy Nguyen, et al.
Geocarto International (2022) Vol. 37, Iss. 26, pp. 12810-12845
Closed Access | Times Cited: 22
Artificial Intelligence for Flood Risk Management: A Comprehensive State-of-the-Art Review and Future Directions
Zhewei Liu, Natalie Coleman, Flavia Ioana Patrascu, et al.
International Journal of Disaster Risk Reduction (2024) Vol. 117, pp. 105110-105110
Closed Access | Times Cited: 4
Analysing frequent extreme flood incidences in Brahmaputra basin, South Asia
Amit Kumar, Subhasree Mondal, Preet Lal
PLoS ONE (2022) Vol. 17, Iss. 8, pp. e0273384-e0273384
Open Access | Times Cited: 18
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