Landslides affecting soil layers up to 1–2 m deep pose a significant hazard in mountainous and hilly regions, particularly in the Mediterranean, where intense precipitation is increasing. Identifying landslide-prone areas is crucial for risk assessment and mitigation, as landslides can severely impact land surfaces, infrastructure, and inhabited areas. Forest cover and management play a fundamental role in stabilizing soil and reducing landslide susceptibility. This study focuses on landslide forecasting models, which integrate geological, climatic, and topographic data to predict landslide probability and severity. Specifically, we compare the predictive accuracy of the 4SLIDE model with the established SHALSTAB model in a forested mountain catchment within Sila National Park, Southern Italy, using GIS-based analysis. The results demonstrate that both models effectively identify high-risk areas, with ROC analysis confirming the superior predictive capability of the 4SLIDE model. Our findings underscore the critical importance of early landslide identification, supporting timely interventions and the implementation of forest engineering and Civil Protection measures to mitigate the impact of landslides on communities and infrastructure.

Among the land use–land cover products, tree cover maps are essential tools for assessing forest functionality and ecosystem services, and implementing sustainable forest management. By combining open-source and ancillary high-resolution cartographic datasets, this study aims to map trees and forests in the Latium region in central Italy, highlighting their spatial configuration, function, and forest typology. The main findings show that trees cover 44.2% of the regional land area. Forests cover 508,056 ha, forming the core matrix of the Latium mountain landscape, providing significant ecological and socio-economic value for forest management and the regional wood supply chain. Although trees outside the forest represent only 3.1% of regional tree cover, they play a crucial role in enhancing ecological connectivity and landscape resilience. Approximately 2% of the tree and forest cover occurs in urban areas, contributing significantly to climate regulation and air quality in densely populated environments. The dominant forest types in Lazio include Turkey oak, temperate broadleaf, beech, downy oak, and Holm oak, which together account for 58.6% of the total tree cover. The accuracy tests confirm the feasibility of using open-source data for reliable, cost-effective forest mapping. Regular updates of these maps can support continuous monitoring and promote sustainable forest management practices.

Urban forests (UFs) play a crucial role in mitigating climate change, but their management presents complex trade-offs between environmental, economic, and social aspects. We developed a Decision Support Tool (DST) to simulate 27-year UF dynamics under six different management strategies, aiming to maximize socio-economic and environmental benefits while considering costs. Business as Usual (BaU), Yielding Scenario (YS), High Management (HM), Forest Development (FD), Social Boost (SB), and Cover Maximizing (CM) strategies were tested with the DST in the Vazzieri district of Campobasso, central Italy. The DST integrates CO₂ removal, management expenditures and revenues, and the social usability of UFs. The findings show that while all the strategies contribute to climate change mitigation, FD and SB offer the best balance between the environmental and social sides. FD demonstrates significant CO₂ removal with moderate expenditures, whereas SB maximizes CO₂ removal despite its high management expenditures. Otherwise, YS and BaU show limited environmental benefits with beneficial economic outcomes. While achieving the highest environmental and social benefits, CM incurs the greatest economic costs. This study highlights the need for long-term, integrated UF strategies to harmonize climate change mitigation with economic viability and social inclusivity. The DST provides a valuable framework for urban planners and policymakers to optimize sustainable UF management.

Among LULC products, tree cover maps are crucial tools to assess forest functionality and ecosystem services (ES), and implement sustainable forest management. Advances in remote sensing technologies continue improving maps’ accuracy, detail and proficiency. This study focuses on a novel high resolution tree cover mapping of Latium region, central Italy, emphasizing spatial configuration, function and typology. Regional forests and trees covers 44.2% of Latium. Forests in mountain areas represent 38.3% of the regional mountain surfaces. Covering 469,593 ha, trees in hilly and floodplain areas plays a crucial role for biodiversity, environmental risks and other ES. We distinguished between forests, which comprise 96.9% of tree cover, and TOF, which contribute to ecological connectivity and landscape resilience. Although representing 2% of the total tree cover, urban forests are vital for climate and urban air quality. Major forest categories of Latium include Turkey oak, Temperate broadleaf, Beech, Downy oak and Holm oak forests. Proposed methodology was found to be reliable for similar purposes. Study has successfully demonstrated the feasibility of producing reliable and cost-effective regional forest maps using open-source data. The regular release of such data should enable rapid map updates, promoting their use for monitoring purposes.