Lago et al. (2026) Optical, radar, and hybrid indices to detect farming practices in Europe

Identification

• Journal: Remote Sensing of Environment
• Year: 2026
• Date: 2026-06-30
• Authors: Paolo Dal Lago, Lammert Kooistra, Nandin‐Erdene Tsendbazar, Kirsten M. de Beurs
• DOI: 10.1016/j.rse.2026.115553

Research Groups

• Laboratory of Geo-Information Science and Remote Sensing (GRS), Wageningen University & Research, the Netherlands

Short Summary

This study investigates the strengths of radar and optical data to retrieve sowing, harvest, and tillage dates at the field level, proposing a novel Hybrid Bare Soil Radar Index (HyBRIS) that merges optical and radar data into a single index using a temporally weighted mean. The method was tested on 41 crops across 16 locations in 11 European countries over 8 years.

Objective

• Investigate the potential of optical and radar indices for detecting farming practices, including sowing, harvest, and tillage dates at the field level.
• Develop a remote sensing framework to calculate hybrid indices fusing optical and radar data.
• Propose a method to identify growing seasons, dormant periods, and detect key farming practices.

Study Configuration

• Spatial Scale: Field-level resolution in 11 European countries.
• Temporal Scale: 8-year interval from 2017 to 2025.

Methodology and Data

• Models used: Hybrid Bare Soil Radar Index (HyBRIS) based on Sentinel-1 and Sentinel-2 data.
• Data sources: Sentinel-1 and Sentinel-2 satellite images, ground truth data from two farms in the Netherlands and one in Italy, and a dataset of sowing, harvest, and tillage dates collected from various sources.

Main Results

• The proposed method based on HyBRIS time series improved sowing and harvest dates detection (MAE 26 and 23 days, respectively) compared to the Copernicus High Resolution Layer Croplands product (HRL-Cropland).
• The method enabled tillage dates estimation during dormant periods (MAE = 28 days), but tended to overestimate the number of tillage events.

Contributions

• This study provides a novel approach for detecting farming practices at the field level using hybrid indices that combine optical and radar data.
• The proposed method can be used to monitor agricultural management and support environmental stewardship.

Funding

• This research was funded by the European Union's Horizon 2020 program (project name not specified).
• Additional funding was provided by the Wageningen University & Research.

Citation

@article{Lago2026Optical,
  author = {Lago, Paolo Dal and Kooistra, Lammert and Tsendbazar, Nandin‐Erdene and Beurs, Kirsten M. de},
  title = {Optical, radar, and hybrid indices to detect farming practices in Europe},
  journal = {Remote Sensing of Environment},
  year = {2026},
  doi = {10.1016/j.rse.2026.115553},
  url = {https://doi.org/10.1016/j.rse.2026.115553}
}