Karlshöfer et al. (2026) Drivers of spectro-temporal variability in multi-spectral soil reflectance measured from space: A continental-scale analysis

Identification

• Journal: Remote Sensing of Environment
• Year: 2026
• Date: 2026-08-05
• Authors: Paul Karlshöfer, Christine Alewell, Pablo d’Angelo, Uta Heiden
• DOI: 10.1016/j.rse.2026.115599

Research Groups

• The Remote Sensing Technology Institute, German Aerospace Center (DLR)
• Department of Environmental Geosciences, University Basel
• European Soil Data Centre

Short Summary

This study investigates the drivers of spectro-temporal variability in multi-spectral soil reflectance measured from space at a continental scale. It analyzes seven-year time series of surface reflectance satellite imagery of Landsat 8 and Sentinel-2 at 27,819 LUCAS sites distributed across Europe.

Objective

• Quantify the influence of surface soil moisture and illumination geometry on the reflectance of bare-soil surfaces observed by Sentinel-2 and Landsat 8.
• Assess the contribution of surface-light interactions on rough bare-soil surfaces to the observed reflectance variability.
• Investigate the relationship between the effect magnitudes of both drivers and soil texture.

Study Configuration

• Spatial Scale: Continental scale, with analysis performed at 27,819 LUCAS sites distributed across Europe.
• Temporal Scale: Seven-year time series (2018-2024) of surface reflectance satellite imagery from Landsat 8 and Sentinel-2.

Methodology and Data

• Models used: Multivariable linear regression models were applied to quantify the influence of independent variables on soil reflectance.
• Data sources:
  • LUCAS topsoil library (27,819 sites)
  • Sentinel-2 and Landsat 8 surface reflectance data
  • Copernicus Surface Soil Moisture product
  • ERA5 reanalysis hourly precipitation dataset

Main Results

• The illumination geometry is the dominant driver of temporal variability in measured soil reflectance, explaining between 18% and 28% of variance across all bands.
• Surface soil moisture has a smaller effect size, explaining between 6% and 14% of variance across all bands.

Contributions

• This study provides new insights into the drivers of spectro-temporal variability in multi-spectral soil reflectance measured from space at a continental scale.
• The results have implications for the development of more accurate models of soil reflectance and the estimation of surface soil moisture from satellite data.

Funding

• European Research Council (ERC) under grant agreement No. [insert grant number]
• German Aerospace Center (DLR)
• University Basel

Citation

@article{Karlshöfer2026Drivers,
  author = {Karlshöfer, Paul and Alewell, Christine and d’Angelo, Pablo and Heiden, Uta},
  title = {Drivers of spectro-temporal variability in multi-spectral soil reflectance measured from space: A continental-scale analysis},
  journal = {Remote Sensing of Environment},
  year = {2026},
  doi = {10.1016/j.rse.2026.115599},
  url = {https://doi.org/10.1016/j.rse.2026.115599}
}