High-Resolution prediction of soil pH in European temperate forests using Sentinel-2 and ancillary environmental data.

ABSTRACT: Soil pH is a key indicator for understanding soil health status in forested ecosystems, yet high-resolution mapping of this variable, especially at a 30-m spatial resolution, remains limited. This study uses Sentinel-2 spectral data, in-situ soil pH measurements, topsoil physical properties from the Land Use/Cover Area Frame Survey (LUCAS) database, and elevation data to estimate soil pH across temperate forests in Europe using a Random Forest model. Despite challenges in signal penetration due to forest canopy cover, the model achieved high prediction accuracy (R² = 0.62) at 30 m resolution. Bulk density, available water capacity, and clay content were the most influential physical predictors, while Sentinel-2 bands, particularly SWIR (1.610 and 2.190 μm), NIR (0.842 μm), and red-edge (0.

SUBMITTER: Abdullah H 

PROVIDER: S-EPMC12325972 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature