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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:

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

Showing 1-25 of 268 citing articles:

Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan
Jie Dou, Ali P. Yunus, Dieu Tien Bui, et al.
The Science of The Total Environment (2019) Vol. 662, pp. 332-346
Closed Access | Times Cited: 509
Assessment of the importance of gully erosion effective factors using Boruta algorithm and its spatial modeling and mapping using three machine learning algorithms
Mahdis Amiri, Hamid Reza Pourghasemi, Gholamabbas Ghanbarian, et al.
Geoderma (2019) Vol. 340, pp. 55-69
Closed Access | Times Cited: 222
Pedology and digital soil mapping (DSM)
Yuxin Ma, Budiman Minasny, Brendan Malone, et al.
European Journal of Soil Science (2019) Vol. 70, Iss. 2, pp. 216-235
Closed Access | Times Cited: 199
Testing a New Ensemble Model Based on SVM and Random Forest in Forest Fire Susceptibility Assessment and Its Mapping in Serbia’s Tara National Park
Ljubomir Gigović, Hamid Reza Pourghasemi, Siniša Drobnjak, et al.
Forests (2019) Vol. 10, Iss. 5, pp. 408-408
Open Access | Times Cited: 199
Assessing and mapping multi-hazard risk susceptibility using a machine learning technique
Hamid Reza Pourghasemi, Narges Kariminejad, Mahdis Amiri, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 198
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
Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland Australia
Omid Rahmati, Fatemeh Falah, Kavina Dayal, et al.
The Science of The Total Environment (2019) Vol. 699, pp. 134230-134230
Closed Access | Times Cited: 174
A comparative analysis of statistical and machine learning techniques for mapping the spatial distribution of groundwater salinity in a coastal aquifer
Hossein Sahour, Vahid Gholami, Mehdi Vazifedan
Journal of Hydrology (2020) Vol. 591, pp. 125321-125321
Closed Access | Times Cited: 158
Comparison of machine learning models for gully erosion susceptibility mapping
Alireza Arabameri, Wei Chen, Marco Loche, et al.
Geoscience Frontiers (2019) Vol. 11, Iss. 5, pp. 1609-1620
Open Access | Times Cited: 149
Susceptibility Mapping of Soil Water Erosion Using Machine Learning Models
Amirhosein Mosavi, Farzaneh Sajedi Hosseini, Bahram Choubin, et al.
Water (2020) Vol. 12, Iss. 7, pp. 1995-1995
Open Access | Times Cited: 144
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
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
Machine learning models for gully erosion susceptibility assessment in the Tensift catchment, Haouz Plain, Morocco for sustainable development
Youssef Bammou, Brahim Benzougagh, Abdessalam Ouallali, et al.
Journal of African Earth Sciences (2024) Vol. 213, pp. 105229-105229
Open Access | Times Cited: 24
Gully erosion zonation mapping using integrated geographically weighted regression with certainty factor and random forest models in GIS
Alireza Arabameri, Biswajeet Pradhan, Khalil Rezaei
Journal of Environmental Management (2018) Vol. 232, pp. 928-942
Open Access | Times Cited: 162
Comparison of differences in resolution and sources of controlling factors for gully erosion susceptibility mapping
Younes Garosi, Mohsen Sheklabadi, Hamid Reza Pourghasemi, et al.
Geoderma (2018) Vol. 330, pp. 65-78
Open Access | Times Cited: 154
Groundwater spring potential modelling: Comprising the capability and robustness of three different modeling approaches
Omid Rahmati, Seyed Amir Naghibi, Himan Shahabi, et al.
Journal of Hydrology (2018) Vol. 565, pp. 248-261
Closed Access | Times Cited: 151
Land subsidence modelling using tree-based machine learning algorithms
Omid Rahmati, Fatemeh Falah, Seyed Amir Naghibi, et al.
The Science of The Total Environment (2019) Vol. 672, pp. 239-252
Closed Access | Times Cited: 141
Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function–logistic regression algorithm
Alireza Arabameri, Biswajeet Pradhan, Khalil Rezaei, et al.
Land Degradation and Development (2018) Vol. 29, Iss. 11, pp. 4035-4049
Open Access | Times Cited: 121
GIS-Based Machine Learning Algorithms for Gully Erosion Susceptibility Mapping in a Semi-Arid Region of Iran
Xinxiang Lei, Wei Chen, Mohammadtaghi Avand, et al.
Remote Sensing (2020) Vol. 12, Iss. 15, pp. 2478-2478
Open Access | Times Cited: 121
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
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 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
Gully headcut susceptibility modeling using functional trees, naïve Bayes tree, and random forest models
Mohsen Hosseinalizadeh, Narges Kariminejad, Wei Chen, et al.
Geoderma (2019) Vol. 342, pp. 1-11
Closed Access | Times Cited: 101
Gully erosion susceptibility mapping using GIS-based multi-criteria decision analysis techniques
Alireza Arabameri, Biswajeet Pradhan, Khalil Rezaei, et al.
CATENA (2019) Vol. 180, pp. 282-297
Closed Access | Times Cited: 100
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