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.

Digital twin (DT) technology has expanded far beyond its industrial origins, increasingly finding application across environmental and territorial domains. This review provides a structured mapping of DT deployments at environmental and territorial scales over the period 2020–2025, examining 117 peer-reviewed publications (109 applied studies and 8 review articles) through a structured 16-parameter classification framework. The review traces three major conceptual shifts in the DT paradigm: from industrial assets to living entities, from discrete systems to Earth-scale representations, and from closed deterministic models to ecological and systemic frameworks, as reflected in the emergence of ecological digital twins (EcoDTs), environmental digital twins (EDTs), and territorial digital twin (TDT) definitions. The results reveal a clear growth trajectory in DT applications across themes, with urban systems as the most consolidated application domain, and progressive diversification into marine, coastal, forestry, river/lake, and Earth system applications from 2022 onward. Institutional actors dominate production in this space, aligned with European flagship initiatives such as Destination Earth (DestinE) and the European Digital Twin of the Ocean (EDITO). The findings position and expand the notion of territorial digital twins as an evolving paradigm, underscoring both the momentum generated by EU digital and environmental policy and the need for integrated tools to answer and respond to key environmental challenges.

Soil compaction is a widespread yet insufficiently monitored form of agricultural land degradation, affecting approximately 25% of global soils and nearly 33% of European subsoils, with consequential reductions in soil physical functionality, crop performance, and long-term sustainability; however, approaches for national-scale compaction risk mapping remain limited. A geospatial decision support framework was developed to quantify and map susceptibility to compaction risk across Italy by integrating Earth observation products with multi-criteria decision analysis within a GIS-based Analytic Hierarchy Process. The model combined four indicators: (i) Soil Moisture Index derived from Sentinel 1 C band SAR time series (2018 to 2024), (ii) the Sentinel 2 Normalized Difference Tillage Index, (iii) clay fraction from SoilGrids 2.0, and (iv) an Intensity of Agricultural Practice Index derived from national census statistics. The approach was applied to 74,156 km² of bare soil surfaces across all 20 regions to generate 100 m seasonal and multi-year mean risk maps. Extreme risk (high plus very high) exhibited a bimodal seasonal behavior, occupying 53.6% in winter and 55.5% in autumn, while declining to 24.8% in spring and 26.5% in summer; Southern Italy showed the largest seasonal amplitude (40.7%), and Friuli Venezia Giulia persisted as a hotspot exceeding 50% in all seasons. Comparison with the independent bulk density observations yielded 31.24% accuracy, largely constrained by the temporal mismatch between dynamic processes and static reference data, which represents a constraint of this research. The framework provides an initial screening tool for mapping susceptibility to soil compaction aligned with the EU Soil Strategy 2023 to 2030, supporting targeted interventions by prioritizing spring (March to May) as a low-risk remediation window; however, local conditions must be checked because cultivated crop types are highly diverse, and cropping cycles vary significantly from one species to another.

Coastal zones and their connected freshwater and marine systems are among the environments most acutely exposed to accelerating climate hazards. European policy has responded by placing Digital Twin (DT) infrastructures at the centre of its climate adaptation and ocean governance agenda: Destination Earth for the Earth system, and the European Digital Twin of the Ocean (EDITO) for the marine and coastal domain. This scoping review defines and evaluates Hydro Digital Twins (HDTs), encompassing Digital Twins of the Ocean (DTOs), coastal-zone DTs, and freshwater-system DTs, as instruments for coastal management, water territory governance, and climate adaptation decision support. Conducted in accordance with PRISMA-ScR, the review screened 231 records (January 2020 to September 2025) and retained 21 studies, each coded against a thirteen-parameter framework organised on a governance axis and a data-centric axis. Governance objectives consistently outweigh technical motivations: risk reduction dominates (7/21 studies, 33%), followed by environmental monitoring (5/21 studies, 24%) and coastal management (4/21 studies, 19%). Remote sensing is used in 19/21 studies (90%) as the near-universal data backbone; artificial intelligence, coded as an analytical method rather than a data source, appears in 10/21 studies (48%) and concentrates in the River/Lakes domain (6/7 studies, 86%), which also holds three of the four predictive outputs; citizen science data, though a stated European policy priority, appears operationally in only 2/21 studies (10%). The modal maturity category is TRL 4–5 (6/21 studies, 29%), only one study reaches TRL 6, and 6/21 studies (29%) report no formal validation. The review clarifies the architectural distinction between HDTs and Web GIS and situates these findings within the European coastal governance agendas of Destination Earth and EDITO. All proportions above are properties of the reviewed corpus and are not extrapolated to the HDT field as a whole.