Borgo et al. (2026) Applying the IOTA2 Chain for Automated 10 m Crop Map Production in a Mediterranean Environment

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-09-11
• Authors: Andrea Borgo, Vincent Thiérion, Gabriele Giuseppe Antonio Satta, Antonio Trabucco, Flavio Lupia, Serena Marras, Marta Debolini
• DOI: 10.3390/rs18183118

Research Groups

• University of Sardinia (Italy)
• IOTA2 consortium

Short Summary

This study develops an automated chain to create 10 m crop distribution maps in Mediterranean regions using open-source satellite imagery and supervised machine learning, achieving high performance for specific crops.

Objective

• Develop a reliable and scalable framework for annual crop monitoring in complex, data-scarce Mediterranean environments.

Study Configuration

• Spatial Scale: 10 m spatial resolution.
• Temporal Scale: Annual crop monitoring.

Methodology and Data

• Models used: Supervised machine learning with open-source satellite imagery.
• Data sources: Land Parcel Identification System (LPIS), Corine Land Cover (CLC), Urban Atlas dataset, and 2018 reference data.

Main Results

• The simplified nomenclature (N25) achieved an overall accuracy of 0.77 with full sampling, compared to 0.61 for the detailed version.
• High performance was observed for specific crops like rice, citrus, and grapevine.
• Classification challenges were encountered for classes such as cereals and fruit trees due to landscape fragmentation.

Contributions

• This study delivers a reproducible framework that enhances thematic details of current European datasets.
• The automated chain offers a scalable solution for rapid crop monitoring in complex environments.

Funding

• Not specified in the paper.

Citation

@article{Borgo2026Applying,
  author = {Borgo, Andrea and Thiérion, Vincent and Satta, Gabriele Giuseppe Antonio and Trabucco, Antonio and Lupia, Flavio and Marras, Serena and Debolini, Marta},
  title = {Applying the IOTA2 Chain for Automated 10 m Crop Map Production in a Mediterranean Environment},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18183118},
  url = {https://doi.org/10.3390/rs18183118}
}