eupassarinho/soil-carbon-and-spectroscopy-with-PLS-and-LASSO
R scripts for predicting soil organic carbon using soil spectral library from visible, near-infrared and shortwave-infrared (VNIR) and middle-infrared (MIR) using LASSO and PLS regression methods and the target-oriented cross-validation strategy.
This project helps soil scientists and environmental researchers accurately predict soil organic carbon (SOC) content using soil spectral data. It takes in visible, near-infrared, shortwave-infrared, and mid-infrared spectral readings from soil samples and outputs robust, generalizable predictions of SOC, along with insights into which spectral bands are most indicative of carbon. The primary users are researchers focused on soil analysis and carbon sequestration.
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Use this if you need to predict soil organic carbon from spectral data and want to avoid model overfitting to develop more reliable and interpretable results.
Not ideal if you are looking for a pre-trained, ready-to-use model without any need to understand or reproduce the underlying methodology or train a new model from scratch.
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R
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GPL-3.0
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Last pushed
Aug 20, 2023
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