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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:

Machine learning in space and time for modelling soil organic carbon change
G.B.M. Heuvelink, Marcos E. Angelini, Laura Poggio, et al.
European Journal of Soil Science (2020) Vol. 72, Iss. 4, pp. 1607-1623
Open Access | Times Cited: 141

Showing 1-25 of 141 citing articles:

SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty
Laura Poggio, Luís Moreira de Sousa, N.H. Batjes, et al.
SOIL (2021) Vol. 7, Iss. 1, pp. 217-240
Open Access | Times Cited: 1266
Machine learning for digital soil mapping: Applications, challenges and suggested solutions
Alexandre M.J.‐C. Wadoux, Budiman Minasny, Alex B. McBratney
Earth-Science Reviews (2020) Vol. 210, pp. 103359-103359
Open Access | Times Cited: 407
Soil organic carbon stocks in European croplands and grasslands: How much have we lost in the past decade?
Daniele De Rosa, Cristiano Ballabio, Emanuele Lugato, et al.
Global Change Biology (2023) Vol. 30, Iss. 1
Open Access | Times Cited: 59
Mapping soil organic carbon stocks and trends with satellite-driven high resolution maps over South Africa
Zander S. Venter, Heidi‐Jayne Hawkins, Michael D. Cramer, et al.
The Science of The Total Environment (2021) Vol. 771, pp. 145384-145384
Open Access | Times Cited: 80
Estimating soil organic carbon stock change at multiple scales using machine learning and multivariate geostatistics
Gábor Szatmári, László Pásztor, G.B.M. Heuvelink
Geoderma (2021) Vol. 403, pp. 115356-115356
Open Access | Times Cited: 69
A CNN-LSTM Model for Soil Organic Carbon Content Prediction with Long Time Series of MODIS-Based Phenological Variables
Lei Zhang, Yanyan Cai, Haili Huang, et al.
Remote Sensing (2022) Vol. 14, Iss. 18, pp. 4441-4441
Open Access | Times Cited: 67
Digital mapping of soil pH and carbonates at the European scale using environmental variables and machine learning
Qikai Lu, Shuang Tian, Lifei Wei
The Science of The Total Environment (2022) Vol. 856, pp. 159171-159171
Closed Access | Times Cited: 67
Spatial statistics and soil mapping: A blossoming partnership under pressure
G.B.M. Heuvelink, R. Webster
Spatial Statistics (2022) Vol. 50, pp. 100639-100639
Open Access | Times Cited: 65
Assessing Machine Learning-Based Prediction under Different Agricultural Practices for Digital Mapping of Soil Organic Carbon and Available Phosphorus
Fuat Kaya, Ali Keshavarzi, Rosa Francaviglia, et al.
Agriculture (2022) Vol. 12, Iss. 7, pp. 1062-1062
Open Access | Times Cited: 46
Beyond prediction: methods for interpreting complex models of soil variation
Alexandre M.J.‐C. Wadoux, Christoph Molnar
Geoderma (2022) Vol. 422, pp. 115953-115953
Open Access | Times Cited: 44
Machine learning for sustainable development and applications of biomass and biomass-derived carbonaceous materials in water and agricultural systems: A review
Szu-Han Wang, Yuan Yao
Resources Conservation and Recycling (2023) Vol. 190, pp. 106847-106847
Open Access | Times Cited: 38
Mapping Brazilian soil mineralogy using proximal and remote sensing data
Nícolas Augusto Rosin, José Alexandre Melo Demattê, Raúl Roberto Poppiel, et al.
Geoderma (2023) Vol. 432, pp. 116413-116413
Open Access | Times Cited: 29
Incorporating machine learning models and remote sensing to assess the spatial distribution of saturated hydraulic conductivity in a light-textured soil
Meisam Rezaei, Seyed Roohollah Mousavi, Asghar Rahmani, et al.
Computers and Electronics in Agriculture (2023) Vol. 209, pp. 107821-107821
Closed Access | Times Cited: 28
Spatial prediction of soil properties using random forest, k-nearest neighbors and cubist approaches in the foothills of the Ural Mountains, Russia
Azamat Suleymanov, И. Ф. Туктарова, Larisa Belan, et al.
Modeling Earth Systems and Environment (2023) Vol. 9, Iss. 3, pp. 3461-3471
Closed Access | Times Cited: 25
Space-time mapping of soil organic carbon stock and its local drivers: Potential for use in carbon accounting
Sabastine Ugbemuna Ugbaje, Senani Karunaratne, Thomas F. A. Bishop, et al.
Geoderma (2024) Vol. 441, pp. 116771-116771
Open Access | Times Cited: 17
Using process-oriented model output to enhance machine learning-based soil organic carbon prediction in space and time
Lei Zhang, G.B.M. Heuvelink, Vera Leatitia Mulder, et al.
The Science of The Total Environment (2024) Vol. 922, pp. 170778-170778
Closed Access | Times Cited: 12
Learning vs. understanding: When does artificial intelligence outperform process-based modeling in soil organic carbon prediction?
Luca Giuliano Bernardini, Christoph Rosinger, Gernot Bodner, et al.
New Biotechnology (2024) Vol. 81, pp. 20-31
Open Access | Times Cited: 12
Providing quality-assessed and standardised soil data to support global mapping and modelling (WoSIS snapshot 2023)
N.H. Batjes, Luis Calisto, Luís Moreira de Sousa
Earth system science data (2024) Vol. 16, Iss. 10, pp. 4735-4765
Open Access | Times Cited: 12
Towards an improved prediction of soil-freezing characteristic curve based on extreme gradient boosting model
K.K. Li, Hailong He
Geoscience Frontiers (2024) Vol. 15, Iss. 6, pp. 101898-101898
Open Access | Times Cited: 10
A novel hybrid group method of data handling and Levenberg Marquardt model for estimating total organic carbon in source rocks with explainable artificial intelligence
Christopher N. Mkono, Chuanbo Shen, Alvin K. Mulashani, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 144, pp. 110137-110137
Closed Access | Times Cited: 1
Spatial and temporal evolution of soil organic matter and its response to dynamic factors in the Southern part of Black Soil Region of Northeast China
Xingnan Liu, Mingchang Wang, Ziwei Liu, et al.
Soil and Tillage Research (2025) Vol. 248, pp. 106475-106475
Closed Access | Times Cited: 1
Temporal adjustment approach for high-resolution continental scale modeling of soil organic carbon
Laxman Bokati, Anil Somenahally, Saurav Kumar, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Data-driven modeling indicates projected increase in plant production confines warming-induced topsoil organic carbon change in China within a small range in the 21st Century
Huiwen Li, Yue Cao, Yiping Wu, et al.
Sustainable Horizons (2025) Vol. 15, pp. 100138-100138
Open Access | Times Cited: 1
Artificial intelligence in soil science
Alexandre M.J.‐C. Wadoux
European Journal of Soil Science (2025) Vol. 76, Iss. 2
Open Access | Times Cited: 1
Machine Learning and Artificial Intelligence Applications in Soil Science
Budiman Minasny, Alex B. McBratney
European Journal of Soil Science (2025) Vol. 76, Iss. 2
Closed Access | Times Cited: 1
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