In order to maximize ecosystem services (ES), a proper planning of urban green areas is needed. In this study, the urban greenery of two Italian cities (Milan and Bologna) exposed to high levels of atmospheric pollutants was examined. Vegetation maps were developed through a supervised classification algorithm, trained over remote sensing images, integrated by local trees inventory, and used as input for the AIRTREE multi-layer canopy model. In both cities, a large presence of deciduous broadleaves was found, which showed a higher capacity to sequestrate CO₂ (3,953,280 g m² y⁻¹), O₃ (5677.76 g m² y⁻¹), and NO₂ (2358.30 g m² y⁻¹) when compared to evergreen needle leaves that, on the other hand, showed higher performances in particulate matter removal (14,711.29 g m² y⁻¹ and 1964.91 g m² y⁻¹ for PM₁₀ and PM_2,5, respectively). We identified tree species with the highest carbon uptake capacity with values up to 1025.47 g CO₂ m² y⁻¹ for Celtis australis, Platanus x acerifolia, Ulmus pumila, and Quercus rubra. In light of forthcoming and unprecedent policy measures to plant millions of trees in the urban areas, our study highlights the importance of developing an integrated approach that combines modelling and satellite data to link air quality and the functionality of green plants as key elements in improving the delivery of ES in cities.

Mediterranean coastal areas are among the most threated forest ecosystems in the northern hemisphere due to concurrent biotic and abiotic stresses. These may affect plants functionality and, consequently, their capacity to provide ecosystem services. In this study, we integrated ground-level and satellite-level measurements to estimate the capacity of a 46.3 km² Estate to sequestrate air pollutants from the atmosphere, transported to the study site from the city of Rome. By means of a multi-layer canopy model, we also evaluated forest capacity to provide regulatory ecosystem services. Due to a significant loss in forest cover, estimated by satellite data as −6.8% between 2014 and 2020, we found that the carbon sink capacity decreased by 34% during the considered period. Furthermore, pollutant deposition on tree crowns has reduced by 39%, 46% and 35% for PM, NO₂ and O₃, respectively. Our results highlight the importance of developing an integrated approach combining ground measurements, modelling and satellite data to link air quality and plant functionality as key elements to improve the effectiveness of estimate of ecosystem services.

Digitalization has transformed various sectors, including forestry, by introducing specialized digital tools and ICTs. This study explores the impact of digitalization on the Italian forestry sector, focusing on socio-economic indicators. Data on these indicators were gathered from the “National Forest Information System” (SINFor), while the digitalization level in Italian regions came from previous studies. The methods used included correlation analysis between digitalization and socio-economic indicators, along with linear regression models. The study also presents three digital progress scenarios, predicting significant socio-economic improvements with increased digitalization. The results show a strong correlation between digitalization and forestry indicators such as employment, value creation, and certification. These findings highlight the transformative potential of digitalization for sustainable forest management, emphasizing the need for further investment in digital infrastructure to boost productivity, inclusivity, and environmental conservation. The study also discusses challenges in fully understanding the effects of digitalization and suggests future research directions to examine specific technological features and broader industry impacts.

The digitalization of processes is a priority objective on the agenda of the Italian National Government. The forestry system could benefit from its introduction, both for the purposes of administration, management, monitoring and governance of the national forest heritage. The authors, through questionnaires and interviews, defined the degree of digitalization of the forestry sector. While the computerisation phase has been completed, at the beginning of 2021, forest digitalization is still in the early stages, except for some realities that represent excellence.

This study presents an automatic methodology based on airborne laser scanner (ALS) data, which allows the mapping of forests, using quantitative criteria typical of forest definitions, i.e. minimum threshold for the height of trees, canopy cover, forest area size, and width. Interactions between forest and other land uses are explored by the methodology for the definition of forest borderlines using an additional criterion; this criterion is the distance-discontinuity (DD), which establishes a minimum width (MW) for portions of territory categorized by land uses different from the forest. The proposed forest mapping approach introduces also a fuzzy algorithm to assess the canopy cover, thereby enhancing the positional accuracy in the delineation of the forest borderline. This methodology has a very flexible mapping approach with the potential to address the many forest definitions existing worldwide. The evaluation and the improvement of the methodology are particularly encouraged by its release as an open source tool.