Year: 2025
Type: article
Abstract: Land degradation is a complex and context-specific phenomenon with significant implications for rural areas, where agricultural and livestock activities intersect with natural ecosystem processes. Despite growing efforts to monitor land degradation, the absence of standardized methodologies limits the comparability of results and the implementation of coherent mitigation strategies. This study introduces RURALIS, a multi-model framework, based on remote sensing, specifically designed to assess land degradation in the rural areas of Italy. Drawing on the structure and outputs of three existing models, RURALIS adopts a model-learning approach. A Random Forest classifier is then employed to compare outputs from all models and identify areas of severe degradation across all models. The analysis reveals that approximately 2.34 million hectares (13.6%) of Italy’s rural lands are severely degraded, with hotspots in northern Puglia, Sicilia, and parts of northern Italy. The model demonstrates strong classification performance and provides a flexible, high-resolution tool that leverages the shared foundation of remote sensing to deliver spatially detailed, decision-ready outputs for rural land management.
Source: Remote Sensing
DOI: 10.3390/rs17193276
Institutions: University of Padua, Universität Hamburg
Language: English
Subfield: Soil Science
Domain: Life Sciences
SDG: Life on land
Open Access status: gold
Estimated APC paid: $3,258
Funder: European Commission
OpenAlex ID: W4414451813