articleTop 1% cited
A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape
Ecological Indicators · 2015 · Vol. 52 · pp. 394–403
Kennedy Were✉(Norwegian University of Life Sciences)Dieu Tien Bui(Telemark Research Institute)Øystein B. Dick(Norwegian University of Life Sciences)Bal Ram Singh(Norwegian University of Life Sciences)
Soil Geostatistics and MappingSoil erosion and sediment transportSoil Carbon and Nitrogen DynamicsRandom forestMean squared errorSupport vector machineEnvironmental scienceSoil carbonArtificial neural networkRegressionClimate changeCalibrationRegression analysis
Funding
- Norges Forskningsråd
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796
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References
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On digital soil mapping
Geoderma · 2003 · 3,478 citations
Mapping continuous depth functions of soil carbon storage and available water capacity
Geoderma · 2009 · 487 citations
Soil organic carbon concentrations and stocks on Barro Colorado Island — Digital soil mapping using Random Forests analysis
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Does conversion of forest to agricultural land change soil carbon and nitrogen? a review of the literature
Global Change Biology · 2002 · 976 citations
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Geoderma · 2004 · 3,768 citations
Factors of Soil Formation, a System of Quantitative Pedology
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