Predictive Soil Modeling
Predictive Soil Modeling is a geostatistical methodology that employs environmental covariates and machine learning algorithms to infer and map soil properties or classes across spatial domains based on sparse observational data.
716
Publications
45.5K
Citations
2.3K
Authors
1K
Institutions
Publications per year
2017–2026
499
Variants
Digital Soil Modeling
Parents
716
Spatial prediction of soil properties using environmental correlation
N. J. McKenzie, Philip J. Ryan · Geoderma · 1999 · 665 citations
1–5 of 716
2.3K
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11
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1–5 of 2.3K
1K

Chinese Academy of Sciences
Beijing, China
26 h-index
139 publications
10.1K citations

The University of Sydney
Sydney, Australia
21 h-index
42 publications
7.3K citations
University of Chinese Academy of Sciences
Beijing, China
17 h-index
55 publications
4.1K citations

Zhejiang University
Hangzhou, China
16 h-index
54 publications
4K citations

University of Tübingen
Tübingen, Germany
15 h-index
34 publications
2.8K citations
ISRIC - World Soil Information
Wageningen, Netherlands
14 h-index
28 publications
6.9K citations
Institute of Geographic Sciences and Natural Resources Research
Beijing, China
13 h-index
25 publications
2.1K citations

University of Tehran
Tehran, Iran
12 h-index
26 publications
782 citations
1–8 of 1K
84 publications · 9.8K citations
56
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24 publications · 2.2K citations
21
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22 publications · 1.3K citations
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SSSAJ · 20 publications · 1.7K citations
19
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17 publications · 1.3K citations
14
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1–5