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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

Comparative AssessmentCarbon SequestrationEngineeringSoil Carbon CycleLand UseSoil ClassificationGeographyForestryPrecision Soil MappingRemote SensingSoil Carbon SequestrationSupport Vector RegressionAfromontane LandscapeCarbon StockSocial SciencesDeforestation