Austrian NIR soil spectral library for soil health assessments

Abstract

Abstract. The rise in demand for soil data and information calls for quick and cost-effective methodologies to quantify soil properties. This is particularly important in the realm of restoring soil health in Europe. Near-infrared (NIR) spectroscopy has demonstrated the ability to predict specific soil properties with high accuracy whilst being less costly and time-consuming than traditional methods. To fill gaps in national spectroscopic soil data, we compiled the first Austrian NIR soil spectral library (680–2500 nm) based on legacy samples (n=2129), covering all environmental zones of Austria. We then employed partial least square regression (PLSR) modelling to test the usability of the dataset for soil health assessments at its current stage. Our analysis revealed that the application of the PLSR is not suitable for accurately estimating soil health indicators compared to routine laboratory analysis. Nevertheless, among the 14 soil properties tested, total nitrogen, CaCO3, soil organic carbon and clay exhibited moderate predictive accuracy (R2>0.7). Most importantly, the dataset containing sample meta-data (e.g., land use type, environmental zone or zip code), laboratory reference values and NIR spectra with 1 nm resolution can be used as a foundation for further spectral analysis and modelling. We make this work openly accessible to actively contribute to closing soil data gaps and promote the expansion of soil spectral libraries as a basis for soil health assessments (https://doi.org/10.5281/zenodo.15772618, Fohrafellner et al., 2025).