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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:

The Use of Deep Machine Learning for the Automated Selection of Remote Sensing Data for the Determination of Areas of Arable Land Degradation Processes Distribution
Д. И. Рухович, П. В. Королева, Д. И. Рухович, et al.
Remote Sensing (2021) Vol. 13, Iss. 1, pp. 155-155
Open Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities
Wei Han, Xiaohan Zhang, Yi Wang, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2023) Vol. 202, pp. 87-113
Closed Access | Times Cited: 122
Forecasting vegetation indices from spatio-temporal remotely sensed data using deep learning-based approaches: A systematic literature review
Aya Ferchichi, Ali Ben Abbes, Vincent Barra, et al.
Ecological Informatics (2022) Vol. 68, pp. 101552-101552
Closed Access | Times Cited: 90
Bibliometric Analysis of Desertification in the Period from 1974 to 2024 Based on the Scopus Database
Arslan Berdyyev, Yousef A. Al-Masnay, Mukhiddin Juliev, et al.
Land (2025) Vol. 14, Iss. 3, pp. 496-496
Open Access | Times Cited: 1
Modelling and accessing land degradation vulnerability using remote sensing techniques and the analytical hierarchy process approach
Abebe Debele Tolche, Megersa Adugna Gurara, Quoc Bao Pham, et al.
Geocarto International (2021) Vol. 37, Iss. 24, pp. 7122-7142
Closed Access | Times Cited: 43
Digital soil mapping in the Russian Federation: A review
Azamat Suleymanov, Dominique Arrouays, I. Yu. Savin
Geoderma Regional (2024) Vol. 36, pp. e00763-e00763
Closed Access | Times Cited: 8
Rural Land Degradation Assessment through Remote Sensing: Current Technologies, Models, and Applications
Federica D’Acunto, Francesco Marinello, Andrea Pezzuolo
Remote Sensing (2024) Vol. 16, Iss. 16, pp. 3059-3059
Open Access | Times Cited: 6
Modeling and Assessment of Land Degradation Vulnerability in Arid Ecosystem of Rajasthan Using Analytical Hierarchy Process and Geospatial Techniques
Brijesh Kumar Yadav, Lal Chand Malav, Raimundo Jiménez Ballesta, et al.
Land (2022) Vol. 12, Iss. 1, pp. 106-106
Open Access | Times Cited: 20
A detailed mapping of soil organic matter content in arable land based on the multitemporal soil line coefficients and neural network filtering of big remote sensing data
Д. И. Рухович, П. В. Королева, Alexey Rukhovich, et al.
Geoderma (2024) Vol. 447, pp. 116941-116941
Open Access | Times Cited: 4
Mapping of Agate-like Soil Cover Structures Based on a Multitemporal Soil Line Using Neural Network Filtering of Remote Sensing Data
Д. И. Рухович, П. В. Королева, Alexey Rukhovich, et al.
Geosciences (2025) Vol. 15, Iss. 1, pp. 32-32
Open Access
Investigate the Factors of Land Degradation in Chinese Provinces: An Application of Index Formation and Random Forest
Z. P. Tu, Qing‐An Huang, Xin Zhao, et al.
Land Degradation and Development (2025)
Closed Access
Soil Conservation and Information Technologies: A Literature Review
Jô Vinícius Barrozo Chaves, Claudia Liliana Gutierrez Rosas, Camila Porfirio Albuquerque Ferraz, et al.
Smart Agricultural Technology (2025), pp. 100935-100935
Open Access
Recognition of the Bare Soil Using Deep Machine Learning Methods to Create Maps of Arable Soil Degradation Based on the Analysis of Multi-Temporal Remote Sensing Data
Д. И. Рухович, П. В. Королева, Д. И. Рухович, et al.
Remote Sensing (2022) Vol. 14, Iss. 9, pp. 2224-2224
Open Access | Times Cited: 15
Survey on Machine Learning and Deep Learning Techniques for Agriculture Land
Gurwinder Singh, Ganesh Kumar Sethi, Sartajvir Singh
SN Computer Science (2021) Vol. 2, Iss. 6
Closed Access | Times Cited: 19
Analytic Hierarchy Process Based Land Suitability for Organic Farming in the Arid Region
Pandian Mangan, Dinagarapandi Pandi, Mohd Anul Haq, et al.
Sustainability (2022) Vol. 14, Iss. 8, pp. 4542-4542
Open Access | Times Cited: 14
Land degradation vulnerability mapping in a west coast river basin of India using analytical hierarchy process combined machine learning models
Bappa Das, Sujeet Desai, Amrita Daripa, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 35, pp. 83975-83990
Open Access | Times Cited: 8
Updating of the Archival Large-Scale Soil Map Based on the Multitemporal Spectral Characteristics of the Bare Soil Surface Landsat Scenes
Д. И. Рухович, П. В. Королева, Д. И. Рухович, et al.
Remote Sensing (2023) Vol. 15, Iss. 18, pp. 4491-4491
Open Access | Times Cited: 8
Informativeness of the Long-Term Average Spectral Characteristics of the Bare Soil Surface for the Detection of Soil Cover Degradation with the Neural Network Filtering of Remote Sensing Data
Д. И. Рухович, П. В. Королева, Д. И. Рухович, et al.
Remote Sensing (2022) Vol. 15, Iss. 1, pp. 124-124
Open Access | Times Cited: 12
Mapping tea plantation area using phenology algorithm, time-series Sentinel-2 and Landsat images
Haoming Xia, Xiqing Bian, Li Pan, et al.
International Journal of Remote Sensing (2023) Vol. 44, Iss. 9, pp. 2826-2846
Closed Access | Times Cited: 6
Artificial Intelligence including Machine Learning and Deep Learning algorithms
Mostafa Biglarfadafan
Elsevier eBooks (2024), pp. 323-336
Closed Access | Times Cited: 2
Prediction and mapping of land degradation in the Batanghari watershed, Sumatra, Indonesia: utilizing multi-source geospatial data and machine learning modeling techniques
Fajar Yulianto, Puguh Dwi Raharjo, Irfan Budi Pramono, et al.
Modeling Earth Systems and Environment (2023) Vol. 9, Iss. 4, pp. 4383-4404
Closed Access | Times Cited: 5
Land Cover and Landscape Structural Changes Using Extreme Gradient Boosting Random Forest and Fragmentation Analysis
Charles Matyukira, Paidamwoyo Mhangara
Remote Sensing (2023) Vol. 15, Iss. 23, pp. 5520-5520
Open Access | Times Cited: 4
Identification of Surface-Carbonate Soils and Soils with Variegated Underlying Rocks in the South of Volga Upland on Satellite Images
И. Н. Горохова, N. B. Khitrov, L. A. Tarnopolsky
Eurasian Soil Science (2024) Vol. 57, Iss. 8, pp. 1297-1307
Closed Access | Times Cited: 1
Erosion–Accumulative Soil Cover Patterns of Dry-Steppe Agrolandscape, Rostov Region
N. B. Khitrov, Е. И. Кравченко, Д. И. Рухович, et al.
Eurasian Soil Science (2024) Vol. 57, Iss. 9, pp. 1409-1432
Closed Access | Times Cited: 1
Analyzing the Trend of LULC Change Over Five Decades in Dhanbad District, Jharkhand (India) Using Geospatial Techniques
Gaurav Chakrabarty, Mahendra Singh Nathawat, Suman Sinha
(2024), pp. 363-392
Closed Access | Times Cited: 1
Evolutionary Overview and Prediction of Themes in the Field of Land Degradation
Xinhai Lu, Yanwei Zhang, Chaoran Lin, et al.
Land (2021) Vol. 10, Iss. 3, pp. 241-241
Open Access | Times Cited: 8
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