Using Spectroradiometry to Measure Organic Carbon in Carbonate-Containing Soils.

Autor: Bartmiński P; Department of Geology, Soil Science and Geoinformation, Institute of Earth and Environmental Sciences, Maria Curie-Skłodowska University, al. Kraśnicka 2cd, 20-718 Lublin, Poland., Siedliska A; Institute of Agrophysics Polish Academy of Sciences, ul. Doświadczalna 4, 20-290 Lublin, Poland., Siłuch M; Department of Geology, Soil Science and Geoinformation, Institute of Earth and Environmental Sciences, Maria Curie-Skłodowska University, al. Kraśnicka 2cd, 20-718 Lublin, Poland.
Jazyk: angličtina
Zdroj: Sensors (Basel, Switzerland) [Sensors (Basel)] 2024 Jun 02; Vol. 24 (11). Date of Electronic Publication: 2024 Jun 02.
DOI: 10.3390/s24113591
Abstrakt: This study explores the feasibility of analyzing soil organic carbon (SOC) in carbonate-rich soils using visible near-infrared spectroscopy (VIS-NIR). Employing a combination of datasets, feature groups, variable selection methods, and regression models, 22 modeling pipelines were developed. Spectral data and spectral data combined with carbonate contents were used as datasets, while raw reflectance, first-derivative (FD) reflectance, and second-derivative (SD) reflectance constituted the feature groups. The variable selection methods included Spearman correlation, Variable Importance in Projection (VIP), and Random Frog (Rfrog), while Partial Least Squares Regression (PLSR), Random Forest Regression (RFR), and Support Vector Regression (SVR) were the regression models. The obtained results indicated that the FD preprocessing method combined with RF, results in the model that is sufficiently robust and stable to be applied to soils rich in calcium carbonate.
Databáze: MEDLINE
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