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Soil Geostatistics and Mapping

TopicLeading institutions, researchers & key papers

This cluster of papers represents advances in digital soil mapping techniques, including the use of geostatistics, remote sensing, spectroscopy, and machine learning for mapping and predicting soil properties. The focus is on spatial interpolation, global soil information, and the application of these techniques for soil security and terrain analysis.

35
Works

How has Soil Geostatistics and Mapping's publication output changed over time?

ScholarIQpublication output · 2009–2026

Output grew0% over the shown period — from 1 works in 2009 to 1 in 2026.

1
1
1
2
1
2
1
2
1
1
2009201120132014201520162021202420252026

What are the most-cited papers on Soil Geostatistics and Mapping?

ScholarIQmost cited works
An overview and comparison of machine-learning techniques for classification purposes in digital soil mapping
Brandon Heung, Hung Chak Ho, Jin Zhang, Anders Knudby, Chuck Bulmer, Margaret Schmidt
S201473135. 2015528 Citations
Predictive soil parent material mapping at a regional-scale: A Random Forest approach
Brandon Heung, Chuck Bulmer, Margaret Schmidt
S201473135. 2013281 Citations
Early season monitoring of corn and soybeans with TerraSAR-X and RADARSAT-2
Heather McNairn, Angela Kross, David R. Lapen, R. Caves, Jiali Shang
S4210179989. 2014166 Citations
Quantile regression as a generic approach for estimating uncertainty of digital soil maps produced from machine-learning
Babak Kasraei, Brandon Heung, Daniel D. Saurette, Margaret Schmidt, Chuck Bulmer, William Bethel
S113611870. 2021101 Citations
A framework for optimizing environmental covariates to support model interpretability in digital soil mapping
Babak Kasraei, Margaret Schmidt, Jin Zhang, Chuck Bulmer, Deepa S. Filatow, Adrienne Arbor, Travis Pennell, Brandon Heung
S201473135. 202470 CitationsOPEN ACCESS

Where is Soil Geostatistics and Mapping research published, and who funds it?

ScholarIQvenues & funding sources

TOP JOURNALS

S201473135982
S4210179989166
S113611870101
S11975763558

TOP FUNDERS

National Science Foundation
NIH
Wellcome Trust
European Research Council
Funder breakdown is a member featureSign up free to unlock

How much of the research on Soil Geostatistics and Mapping is open access?

ScholarIQopen access share
38%OPEN ACCESS
Gold
15%
Green
8%
Hybrid
8%
Bronze
8%
Closed
62%

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Predictive soil parent material mapping at a regional-scale: A Random Forest approach
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Early season monitoring of corn and soybeans with TerraSAR-X and RADARSAT-2
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470M+ articles · free account