13 citations as recorded by crossref.

1. Combining Digital Covariates and Machine Learning Models to Predict the Spatial Variation of Soil Cation Exchange Capacity F. Kaya et al. 10.3390/land12040819
2. Soil organic carbon stock prediction using multi-spatial resolutions of environmental variables: How well does the prediction match local references? M. Zeraatpisheh et al. 10.1016/j.catena.2023.107197
3. Estimating natural soil drainage classes in the Wisconsin till plain of the Midwestern U.S.A. based on lidar derived terrain indices: Evaluating prediction accuracy of multinomial logistic regression and machine learning algorithms S. Rahmani et al. 10.1016/j.geodrs.2023.e00728
4. Digital soil mapping in the Russian Federation: A review A. Suleymanov et al. 10.1016/j.geodrs.2024.e00763
5. Uncovering the effects of Urmia Lake desiccation on soil chemical ripening using advanced mapping techniques F. Shahbazi et al. 10.1016/j.catena.2023.107440
6. Evaluating the quality of soil legacy data used as input of digital soil mapping models P. Lagacherie et al. 10.1111/ejss.13463
7. Reference soil groups map of Ethiopia based on legacy data and machine learning-technique: EthioSoilGrids 1.0 A. Ali et al. 10.5194/soil-10-189-2024
8. Multiple soil map comparison highlights challenges for predicting topsoil organic carbon concentration at national scale C. Feeney et al. 10.1038/s41598-022-05476-5
9. Multiscale evaluations of global, national and regional digital soil mapping products in France B. Lemercier et al. 10.1016/j.geoderma.2022.116052
10. How well does digital soil mapping represent soil geography? An investigation from the USA D. Rossiter et al. 10.5194/soil-8-559-2022
11. Locally enhanced digital soil mapping in support of a bottom-up approach is more accurate than conventional soil mapping and top-down digital soil mapping M. Bohn & B. Miller 10.1016/j.geoderma.2024.116781
12. High-resolution agriculture soil property maps from digital soil mapping methods, Czech Republic D. Žížala et al. 10.1016/j.catena.2022.106024
13. Influence of Land Use and Topographic Factors on Soil Organic Carbon Stocks and Their Spatial and Vertical Distribution K. Blackburn et al. 10.3390/rs14122846