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In Situ VIS-NIR Spectroscopy for a Basic and Rapid Soil Investigation

Guillaume Debaene, Piotr Bartmiński, Marcin Siłuch

2023Sensors14 citationsDOIOpen Access PDF

Abstract

Visible and near-infrared (VIS-NIR) spectroscopy is extensively used in the field of soil science to predict several soil properties, mostly in laboratory conditions. When measured in situ, contact probes are used, and, very often, time-consuming methods are applied to generate better spectra. Unfortunately, spectra obtained by these methods differ greatly from spectra remotely acquired. This study tried to address this issue by measuring reflectance spectra directly with a fibre optic or a 4° lens on bare untouched soils. C, N content and soil texture (sand, silt, and clay) prediction models were established using partial least-square (PLS) and support vector machine (SVM) regression. With spectral pre-processing, some satisfactory models were obtained, i.e., for C content (R2 = 0.57; RMSE = 0.09%) and for N content (R2 = 0.53; RMSE = 0.02%). Some models were improved when using moisture and temperature as auxiliary data for the modelling. Maps of C, N and clay content generated with laboratory and predicted values were presented. Based on this study, VIS-NIR spectra acquired with bare fibre optic and/or a 4° lens could be used to build prediction models in order to obtain basic preliminary information on soil composition at the field scale. The predicting maps seem suitable for a fast but rough field screening.

Topics & Concepts

SiltWater contentIn situMean squared errorSoil textureSoil waterSpectroscopySupport vector machineSoil sciencePartial least squares regressionContent (measure theory)Spectral lineRemote sensingEnvironmental scienceMathematicsChemistryComputer scienceGeologyArtificial intelligenceStatisticsPhysicsAstronomyGeotechnical engineeringOrganic chemistryQuantum mechanicsPaleontologyMathematical analysisSoil Geostatistics and MappingSpectroscopy and Chemometric AnalysesMineral Processing and Grinding
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