Using laboratory Vis-NIR spectroscopy for monitoring some forest soil properties

Abstract

The development of rapid, accurate, and cost-effective methods to determine forest soil properties such as visible and near infrared (Vis-NIR) spectroscopy is important for sustainable land management. The main objective of this study was to assess the suitability of Vis-NIR spectroscopy coupled with partial least squares regression (PLSR) to determine some forest soil properties such as organic carbon (SOC), total nitrogen (TN), pH, and soil texture (sand, silt, and clay) for a representative forest area in southern Italy. Soil samples (0–20 cm depth) were collected at 267 locations, oven-dried and passed through a 2-mm sieve, and analyzed for some chemical and physical soil properties using conventional laboratory methods. Vis-NIR reflectance of each soil sample was measured in laboratory under artificial light using an ASD FieldSpec IV 350–2500 nm spectroradiometer. Partial least squares regression (PLSR) was used to develop a calibration model for SOC, TN, pH, sand, silt, and clay. Samples were split into a calibration set (187 samples) to develop the models and a validation set (80 samples) to assess the prediction accuracy of the calibration models. Results showed a good agreement between measured and predicted values with high R 2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil properties. Finally, findings confirmed that laboratory Vis–NIR spectroscopy has the potential to be a non-destructive and cost-effective tool for rapid determination of many soil properties. The spectral data collected in this study could contribute to build a regional soil spectral library to be used advantageously in support to soil survey in other areas of the Calabria region (southern Italy).