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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:

Evaluating the influence of geo-environmental factors on gully erosion in a semi-arid region of Iran: An integrated framework
Omid Rahmati, Naser Tahmasebipour, Ali Haghizadeh, et al.
The Science of The Total Environment (2016) Vol. 579, pp. 913-927
Closed Access | Times Cited: 181

Showing 1-25 of 181 citing articles:

Prediction of the landslide susceptibility: Which algorithm, which precision?
Hamid Reza Pourghasemi, Omid Rahmati
CATENA (2017) Vol. 162, pp. 177-192
Closed Access | Times Cited: 424
Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin, Asir Region, Saudi Arabia
Ahmed M. Youssef, Hamid Reza Pourghasemi
Geoscience Frontiers (2020) Vol. 12, Iss. 2, pp. 639-655
Open Access | Times Cited: 336
Gully erosion susceptibility assessment and management of hazard-prone areas in India using different machine learning algorithms
Amiya Gayen, Hamid Reza Pourghasemi, Sunil Saha, et al.
The Science of The Total Environment (2019) Vol. 668, pp. 124-138
Closed Access | Times Cited: 269
Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion
Omid Rahmati, N Tahmasebipour, Ali Haghizadeh, et al.
Geomorphology (2017) Vol. 298, pp. 118-137
Closed Access | Times Cited: 268
River suspended sediment modelling using the CART model: A comparative study of machine learning techniques
Bahram Choubin, Hamid Darabi, Omid Rahmati, et al.
The Science of The Total Environment (2017) Vol. 615, pp. 272-281
Closed Access | Times Cited: 265
Spatial modelling of gully erosion in Mazandaran Province, northern Iran
Mohsen Zabihi, Fahimeh Mirchooli, Alireza Motevalli, et al.
CATENA (2017) Vol. 161, pp. 1-13
Closed Access | Times Cited: 207
Measuring, modelling and managing gully erosion at large scales: A state of the art
Matthias Vanmaercke, Panos Panagos, Tom Vanwalleghem, et al.
Earth-Science Reviews (2021) Vol. 218, pp. 103637-103637
Open Access | Times Cited: 201
Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models
Ali Azareh, Omid Rahmati, Elham Rafiei-Sardooi, et al.
The Science of The Total Environment (2018) Vol. 655, pp. 684-696
Open Access | Times Cited: 190
Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion
Younes Garosi, Mohsen Sheklabadi, Christian Conoscenti, et al.
The Science of The Total Environment (2019) Vol. 664, pp. 1117-1132
Closed Access | Times Cited: 189
Improvement of Best First Decision Trees Using Bagging and Dagging Ensembles for Flood Probability Mapping
Peyman Yariyan, Saeid Janizadeh, Tran Van Phong, et al.
Water Resources Management (2020) Vol. 34, Iss. 9, pp. 3037-3053
Closed Access | Times Cited: 148
Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine
Bakhtiar Feizizadeh, Davoud Omarzadeh, Mohammad Kazemi Garajeh, et al.
Journal of Environmental Planning and Management (2021) Vol. 66, Iss. 3, pp. 665-697
Closed Access | Times Cited: 139
Interpretability of simple RNN and GRU deep learning models used to map land susceptibility to gully erosion
Hamid Gholami, Aliakbar Mohammadifar, Shahram Golzari, et al.
The Science of The Total Environment (2023) Vol. 904, pp. 166960-166960
Closed Access | Times Cited: 48
GIS-based gully erosion susceptibility mapping: a comparison among three data-driven models and AHP knowledge-based technique
Alireza Arabameri, Khalil Rezaei, Hamid Reza Pourghasemi, et al.
Environmental Earth Sciences (2018) Vol. 77, Iss. 17
Closed Access | Times Cited: 163
Spatial Modelling of Gully Erosion Using GIS and R Programing: A Comparison among Three Data Mining Algorithms
Alireza Arabameri, Biswajeet Pradhan, Hamid Reza Pourghasemi, et al.
Applied Sciences (2018) Vol. 8, Iss. 8, pp. 1369-1369
Open Access | Times Cited: 127
Gully erosion spatial modelling: Role of machine learning algorithms in selection of the best controlling factors and modelling process
Hamid Reza Pourghasemi, Nitheshnirmal Sãdhasivam, Narges Kariminejad, et al.
Geoscience Frontiers (2020) Vol. 11, Iss. 6, pp. 2207-2219
Open Access | Times Cited: 115
Novel ensembles of COPRAS multi-criteria decision-making with logistic regression, boosted regression tree, and random forest for spatial prediction of gully erosion susceptibility
Alireza Arabameri, M Yamani, Biswajeet Pradhan, et al.
The Science of The Total Environment (2019) Vol. 688, pp. 903-916
Closed Access | Times Cited: 114
A machine learning framework for multi-hazards modeling and mapping in a mountainous area
Saleh Yousefi, Hamid Reza Pourghasemi, Sayed Naeim Emami, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 114
Application of the GIS-Based Probabilistic Models for Mapping the Flood Susceptibility in Bansloi Sub-basin of Ganga-Bhagirathi River and Their Comparison
Gopal Chandra Paul, Sunil Saha, Tusar Kanti Hembram
Remote Sensing in Earth Systems Sciences (2019) Vol. 2, Iss. 2-3, pp. 120-146
Closed Access | Times Cited: 113
A Novel Ensemble Artificial Intelligence Approach for Gully Erosion Mapping in a Semi-Arid Watershed (Iran)
Dieu Tien Bui, Ataollah Shirzadi, Himan Shahabi, et al.
Sensors (2019) Vol. 19, Iss. 11, pp. 2444-2444
Open Access | Times Cited: 110
A Comparative Assessment of Random Forest and k-Nearest Neighbor Classifiers for Gully Erosion Susceptibility Mapping
Mohammadtaghi Avand, Saeid Janizadeh, Seyed Amir Naghibi, et al.
Water (2019) Vol. 11, Iss. 10, pp. 2076-2076
Open Access | Times Cited: 103
Identification of soil erosion-susceptible areas using fuzzy logic and analytical hierarchy process modeling in an agricultural watershed of Burdwan district, India
Sunil Saha, Amiya Gayen, Hamid Reza Pourghasemi, et al.
Environmental Earth Sciences (2019) Vol. 78, Iss. 23
Closed Access | Times Cited: 100
Comparative assessment using boosted regression trees, binary logistic regression, frequency ratio and numerical risk factor for gully erosion susceptibility modelling
Alireza Arabameri, Biswajeet Pradhan, Luigi Lombardo
CATENA (2019) Vol. 183, pp. 104223-104223
Open Access | Times Cited: 93
Spatial prediction of soil erosion susceptibility using a fuzzy analytical network process: Application of the fuzzy decision making trial and evaluation laboratory approach
Farzaneh Sajedi Hosseini, Bahram Choubin, Karim Solaimani, et al.
Land Degradation and Development (2018) Vol. 29, Iss. 9, pp. 3092-3103
Closed Access | Times Cited: 88
Multi-Hazard Exposure Mapping Using Machine Learning Techniques: A Case Study from Iran
Omid Rahmati, Saleh Yousefi, Zahra Kalantari, et al.
Remote Sensing (2019) Vol. 11, Iss. 16, pp. 1943-1943
Open Access | Times Cited: 83
GIS-Based Site Selection for Check Dams in Watersheds: Considering Geomorphometric and Topo-Hydrological Factors
Omid Rahmati, Zahra Kalantari, Mahmood Samadi, et al.
Sustainability (2019) Vol. 11, Iss. 20, pp. 5639-5639
Open Access | Times Cited: 83
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