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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:

Application of remote sensing techniques and machine learning algorithms in dust source detection and dust source susceptibility mapping
Mahdi Boroughani, Sima Pourhashemi, Hossein Hashemi, et al.
Ecological Informatics (2020) Vol. 56, pp. 101059-101059
Closed Access | Times Cited: 98

Showing 1-25 of 98 citing articles:

A review of Earth Artificial Intelligence
Ziheng Sun, L. Sandoval, Robert Crystal‐Ornelas, et al.
Computers & Geosciences (2022) Vol. 159, pp. 105034-105034
Open Access | Times Cited: 173
Dust storms in Iran – Distribution, causes, frequencies and impacts
Alireza Rashki, Nick Middleton, Andrew Goudie
Aeolian Research (2020) Vol. 48, pp. 100655-100655
Closed Access | Times Cited: 157
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
An automated deep learning convolutional neural network algorithm applied for soil salinity distribution mapping in Lake Urmia, Iran
Mohammad Kazemi Garajeh, Farzad Malakyar, Qihao Weng, et al.
The Science of The Total Environment (2021) Vol. 778, pp. 146253-146253
Closed Access | Times Cited: 71
Atmospheric Dynamics and Numerical Simulations of Six Frontal Dust Storms in the Middle East Region
Nasim Hossein Hamzeh‎, Sara Karami, Dimitris G. Kaskaoutis, et al.
Atmosphere (2021) Vol. 12, Iss. 1, pp. 125-125
Open Access | Times Cited: 67
Predicting the number of dusty days around the desert wetlands in southeastern Iran using feature selection and machine learning techniques
Zohre Ebrahimi‐Khusfi, Ali Reza Nafarzadegan, Fatemeh Dargahian
Ecological Indicators (2021) Vol. 125, pp. 107499-107499
Open Access | Times Cited: 64
Mapping of the wind erodible fraction of soil by bidirectional gated recurrent unit (BiGRU) and bidirectional recurrent neural network (BiRNN) deep learning models
Mahrooz Rezaei, Aliakbar Mohammadifar, Hamid Gholami, et al.
CATENA (2023) Vol. 223, pp. 106953-106953
Open Access | Times Cited: 32
Evaluation of machine learning models for predicting the temporal variations of dust storm index in arid regions of Iran
Zohre Ebrahimi‐Khusfi, Ruhollah Taghizadeh–Mehrjardi, Maryam Mirakbari
Atmospheric Pollution Research (2020) Vol. 12, Iss. 1, pp. 134-147
Open Access | Times Cited: 58
Assessing vegetation restoration potential under different land uses and climatic classes in northeast Iran
Ahmad Emamian, Alireza Rashki, Dimitris G. Kaskaoutis, et al.
Ecological Indicators (2021) Vol. 122, pp. 107325-107325
Open Access | Times Cited: 56
Using the Boruta algorithm and deep learning models for mapping land susceptibility to atmospheric dust emissions in Iran
Hamid Gholami, Aliakbar Mohammadifar, Shahram Golzari, et al.
Aeolian Research (2021) Vol. 50, pp. 100682-100682
Closed Access | Times Cited: 50
Machine Learning Based Algorithms for Global Dust Aerosol Detection from Satellite Images: Inter-Comparisons and Evaluation
Jangho Lee, Yingxi Shi, Changjie Cai, et al.
Remote Sensing (2021) Vol. 13, Iss. 3, pp. 456-456
Open Access | Times Cited: 49
Water bodies changes in Tigris and Euphrates basin has impacted dust storms phenomena
Ali Darvishi Boloorani, Ramin Papi, Masoud Soleimani, et al.
Aeolian Research (2021) Vol. 50, pp. 100698-100698
Closed Access | Times Cited: 46
Integrated modelling for mapping spatial sources of dust in central Asia - An important dust source in the global atmospheric system
Hamid Gholami, Aliakbar Mohammadifar, Hossein Malakooti, et al.
Atmospheric Pollution Research (2021) Vol. 12, Iss. 9, pp. 101173-101173
Closed Access | Times Cited: 43
Hybrid Machine Learning Approach for Gully Erosion Mapping Susceptibility at a Watershed Scale
Sliman Hitouri, Antonietta Varasano, Meriame Mohajane, et al.
ISPRS International Journal of Geo-Information (2022) Vol. 11, Iss. 7, pp. 401-401
Open Access | Times Cited: 37
Land degradation risk dynamics assessment in red and lateritic zones of eastern plateau, India: A combine approach of K-fold CV, data mining and field validation
Asish Saha, Subodh Chandra Pal, Indrajit Chowdhuri, et al.
Ecological Informatics (2022) Vol. 69, pp. 101653-101653
Closed Access | Times Cited: 34
Identifying sand and dust storm sources using spatial-temporal analysis of remote sensing data in Central Iran
Ramin Papi, A.A. Kakroodi, Masoud Soleimani, et al.
Ecological Informatics (2022) Vol. 70, pp. 101724-101724
Closed Access | Times Cited: 34
Modeling land susceptibility to wind erosion hazards using LASSO regression and graph convolutional networks
Hamid Gholami, Aliakbar Mohammadifar, Kathryn E. Fitzsimmons, et al.
Frontiers in Environmental Science (2023) Vol. 11
Open Access | Times Cited: 17
A comprehensive investigation of the causes of drying and increasing saline dust in the Urmia Lake, northwest Iran, via ground and satellite observations, synoptic analysis and machine learning models
Nasim Hossein Hamzeh‎, Karim A. Shukurov, Kaveh Mohammadpour, et al.
Ecological Informatics (2023) Vol. 78, pp. 102355-102355
Closed Access | Times Cited: 17
Evaluating traditional versus ensemble machine learning methods for predicting missing data of daily PM10 concentration
Elham Kalantari, Hamid Gholami, Hossein Malakooti, et al.
Atmospheric Pollution Research (2024) Vol. 15, Iss. 5, pp. 102063-102063
Closed Access | Times Cited: 8
A new integrated data mining model to map spatial variation in the susceptibility of land to act as a source of aeolian dust
Hamid Gholami, Aliakbar Mohammadifar, Hamid Reza Pourghasemi, et al.
Environmental Science and Pollution Research (2020) Vol. 27, Iss. 33, pp. 42022-42039
Closed Access | Times Cited: 42
Dust source susceptibility mapping in Tigris and Euphrates basin using remotely sensed imagery
Ali Darvishi Boloorani, Najmeh Neysani Samany‬, Ramin Papi, et al.
CATENA (2021) Vol. 209, pp. 105795-105795
Closed Access | Times Cited: 41
Predicting of dust storm source by combining remote sensing, statistic-based predictive models and game theory in the Sistan watershed, southwestern Asia
Mahdi Boroughani, Sima Pourhashemi, Hamid Gholami, et al.
Journal of Arid Land (2021) Vol. 13, Iss. 11, pp. 1103-1121
Open Access | Times Cited: 35
Integration of a process-based model into the digital soil mapping improves the space-time soil organic carbon modelling in intensively human-impacted area
Enze Xie, Xiu Zhang, Fangyi Lu, et al.
Geoderma (2021) Vol. 409, pp. 115599-115599
Closed Access | Times Cited: 33
Long-term (2012–2020) PM10 concentrations and increasing trends in the Sistan Basin: The role of Levar wind and synoptic meteorology
Reza Dahmardeh Behrooz, Kaveh Mohammadpour, Parya Broomandi, et al.
Atmospheric Pollution Research (2022) Vol. 13, Iss. 7, pp. 101460-101460
Closed Access | Times Cited: 25
Characterization of Hydrologic Sand and Dust Storm Sources in the Middle East
Ramin Papi, Sara Attarchi, Ali Darvishi Boloorani, et al.
Sustainability (2022) Vol. 14, Iss. 22, pp. 15352-15352
Open Access | Times Cited: 24
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