In recent decades, many mountain areas of the Mediterranean countries show spontaneous reforestation or densification due to depopulation and the consequent abandonment of traditional agricultural and pastoral activities, leading to the loss of open habitats. In this paper, dynamics of natural and semi-natural areas in the summit areas of the Abruzzo, Lazio e Molise National Park are investigated, highlighting changes that occurred from 1954 to present days. Historic Land cover maps have been produced by photo interpretation. A quantitative description of changes and habitats loss in relation to the socio-economic changes is provided. As expected, a forest surface expansion and an open areas decrease are observed similarly to many marginal mountains, where land abandonment and general forest/shrub recovery are the inevitable tendencies. An intense debate is still ongoing regarding the opportunity of rewilding, allowing the natural reforestation processes, versus the management of some areas, in order to preserve habitats and cultural traditional landscapes. For the EU biodiversity conservation policy to be effective, proper planning and management of interventions as well as public support and funding, become crucial when traditional activities are no longer profitable and viable for local inhabitants.

Winter resources are crucial for wildlife, and, at a local scale, some anthropogenic and environmental factors could affect their availability. In the case of wolves, it is known that vocalisations in response to unfamiliar howls are issued to defend their territory and the important resources within it. Then, we studied the characteristics of winter response sites (WRS) during the cold season, aiming to assess their eventual ability to provide insights into the distribution of valuable resources within their territories. Within this scope, we planned a wolf-howling survey following a standardised approach. The study covered an Apennine (Central Italy) area of 500 km². A hexagonal mesh was imposed on the area, in order to determine the values of different variables at the local scale. A logistic LASSO regression was performed. WRS were positively related to the presence of thermal refuges (odds = 114.485), to patch richness (odds = 1.153), wild boar drive hunting areas (odds = 1.015), and time elapsed since the last hunt (odds = 1.019). Among negative factors, stray dogs reply considerably affects wolves’ responsiveness (odds = 0.207), where odds are the exponentiated coefficients estimated by the logistic lasso regression. These results suggest that WRS are related to anthropogenic and environmental factors favouring the predation process.

Urbanization poses significant challenges to ecosystems, resources, and human well-being, necessitating sustainable planning. Urban vegetation, particularly trees, provides critical ecosystem services such as carbon sequestration, air quality improvement, and biodiversity conservation. Traditional tree assessments are resource-intensive and time-consuming. Recent advances in remote sensing, especially high-resolution multispectral imagery and object-based image analysis (OBIA), offer efficient alternatives for mapping urban vegetation. This study evaluates and compares the efficacy of Sentinel-2 and Pléiades satellite imagery in classifying tree species within historic urban parks in Rome—Villa Borghese, Villa Ada Savoia, and Villa Doria Pamphilj. Pléiades imagery demonstrated superior classification accuracy, achieving an overall accuracy (OA) of 89% and a Kappa index of 0.84 in Villa Ada Savoia, compared to Sentinel-2’s OA of 66% and Kappa index of 0.47. Specific tree species, such as Pinus pinea (Stone Pine), reached a user accuracy (UA) of 84% with Pléiades versus 53% with Sentinel-2. These insights underscore the potential of integrating high-resolution remote sensing data into urban forestry practices to support sustainable urban management and planning.

Small landscape features (i.e., trees outside forest, small woody features) and linear vegetation such as hedgerows, riparian vegetation, and green lanes are vital ecological structures in agroecosystems, enhancing the biodiversity, landscape diversity, and protecting water bodies. Therefore, their monitoring is fundamental to assessing a specific territory’s arrangement and verifying the effectiveness of strategies and financial measures activated at the local or European scale. The size of these elements and territorial distribution make their identification extremely complex without specific survey campaigns; in particular, remote monitoring requires data of considerable resolution and, therefore, is very costly. This paper proposes a methodology to map these features using a combination of open-source or low-cost high-resolution orthophotos (RGB), which are typically available to local administrators and are object-oriented classification methods. Additionally, multispectral satellite images from the Sentinel-2 platform were utilized to further characterize the identified elements. The produced map, compared with the other existing layers, provided better results than other maps at the European scale. Therefore, the developed method is highly effective for the remote and wide-scale assessment of SWFs, making it a crucial tool for defining and monitoring development policies in rural environments.