Using an ensemble model coupled with portable X-ray fluorescence and visible near-infrared spectroscopy to explore the viability of mapping and estimating arsenic in an agricultural soil
James Kobina Mensah Biney, Radim Vašát, Johanna Ruth Blöcher, Luboš Borůvka, Karel Němeček
Topics & Concepts
Random forestCalibrationEnvironmental scienceSoil testMean squared errorSupport vector machinePartial least squares regressionCoefficient of determinationSoil scienceSoil waterStatisticsMathematicsComputer scienceMachine learningSoil Geostatistics and MappingGeochemistry and Geologic MappingHeavy metals in environment