2025/11/03 by Simon Ian Futerman, Rachel Lugassi, Jonti Shepherd +5 · 1 voice
Environmental Science · #Soil Geostatistics and Mapping #Soil Moisture and Remote Sensing #Remote Sensing in Agriculture
paper · doi:10.1177/00037028251396975
openalex publication_date 2025/11/03 · openalex created_date 2025/11/03 · openalex updated_date 2026/07/22
Soil reflectance spectroscopy is a powerful tool for rapid, non-destructive assessment of soil properties and the foundation for data-driven soil science applications. However, systematic discrepancies during routine spectral measurement procedures, particularly those arising from contamination or deterioration of white reference (WR) calibration panels, may compromise spectral data stability and hinder harmonization practices across laboratories. This study investigates the impact of using a non-contaminated WR panel as a calibration target to measure soil reflectance across the visible (Vis), near-infrared (NIR), and short-wavelength infrared (SWIR) spectral regions. The study evaluates the effectiveness of an internal soil standard (ISS) Lucky Bay sand to correct discrepancies within a controlled laboratory setting. Twelve soils from the Israeli Legacy Soil Spectral Library were analyzed using a contact-probe setup that was calibrated with both a clean and a contaminated WR. The spectral correction method, based on IEEE P4005 protocols and the ISS calibration, significantly reduced spectral inconsistencies, especially in the Vis region where contamination effects were most pronounced. Results show that the ISS effectively harmonized spectra acquired under different WR conditions, reducing the modified average spectral difference stability (mASDS) measure across all samples. While ISS correction is commonly employed for cross-laboratory harmonization, our findings highlight its critical role in enhancing intra-laboratory consistency under routine operational variability. We recommend that every WR calibration process will be accompanied with ISS measurements. The continuous use of a well-maintained WR and ISS improves the reliability of soil spectral datasets and supports the long-term harmonization of soil spectral libraries.