63 citations as recorded by crossref.

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21. Soil parent material prediction through satellite multispectral analysis on a regional scale at the Western Paulista Plateau, Brazil F. Mello et al. 10.1016/j.geodrs.2021.e00412
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30. Comparison of Machine Learning-Based Prediction of Qualitative and Quantitative Digital Soil-Mapping Approaches for Eastern Districts of Tamil Nadu, India R. Kumaraperumal et al. 10.3390/land11122279
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48. Machine Learning With GA Optimization to Model the Agricultural Soil-Landscape of Germany: An Approach Involving Soil Functional Types With Their Multivariate Parameter Distributions Along the Depth Profile M. Ließ et al. 10.3389/fenvs.2021.692959
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50. Mapping Brazilian soil mineralogy using proximal and remote sensing data N. Rosin et al. 10.1016/j.geoderma.2023.116413
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55. High resolution middle eastern soil attributes mapping via open data and cloud computing R. Poppiel et al. 10.1016/j.geoderma.2020.114890
56. Geomorphometry today I. Florinsky 10.35595/2414-9179-2021-2-27-394-448
57. Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran M. Emadi et al. 10.3390/rs12142234
58. Spatiotemporal modelling of soil organic matter changes in Jiangsu, China between 1980 and 2006 using INLA-SPDE X. Sun et al. 10.1016/j.geoderma.2020.114808
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60. Visual Evaluation of Urban Streetscape Design Supported by Multisource Data and Deep Learning G. Feng et al. 10.1155/2022/3287117
61. Digital soil mapping algorithms and covariates for soil organic carbon mapping and their implications: A review S. Lamichhane et al. 10.1016/j.geoderma.2019.05.031
62. Multi-task convolutional neural networks outperformed random forest for mapping soil particle size fractions in central Iran R. Taghizadeh-Mehrjardi et al. 10.1016/j.geoderma.2020.114552
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