Conference Agenda

The increasing frequency of extreme weather events requires cities to adopt effective climate adaptation strategies, the urban heat island (UHI) effect, environmental degradation, and limited access to natural spaces are among the most relevant urban challenges. Urban green infrastructure is widely recognized as a nature-based solution capable of mitigating thermal stress while improving environmental conditions and supporting healthier lifestyles.

This study presents a GIS-based methodological framework aimed at assessing the quality, spatial distribution, and functional potential of urban green spaces (UGS) to support climate adaptation and health-oriented urban planning. The approach integrates multiple spatial datasets within a geodatabase and applies an indicator-based multi-criteria analysis to evaluate structural, functional, and accessibility characteristics of UGS.

The methodology was applied to an Italian case study, a spatial database including 526 UGS was developed and integrated with territorial datasets such as transport networks, settlement patterns, public services, and population distribution.

The spatial analysis enabled the identification of priority intervention areas and the selection of UGS most suitable for physical activity and health-promotion initiatives. Results demonstrate that the proposed GIS-based framework represents an effective decision-support tool for environmental planning, facilitating targeted strategies to enhance urban resilience and mitigate thermal stress through improved green infrastructure management.

Urban areas play a central role in the energy transition, yet renewable energy planning often conflicts with land availability, environmental protection, and social acceptance. Building rooftops represent a strategic resource for the decarbonization of urban energy systems, enabling solar deployment without additional land consumption and integration with existing infrastructures. In Mediterranean regions such as Lazio (central Italy), characterized by high solar radiation and heterogeneous building stock, estimating rooftop photovoltaic (PV) potential is essential to support sustainable and equitable energy policies.

This paper presents a preliminary regional assessment of photovoltaic rooftop potential in Lazio, based on open cartographic and climatic data. The methodology integrates the regional geospatial database, roof utilization factors from international literature, and solar yield indicators from European climate tools. A GIS-based framework translates built areas into photovoltaic potential, ensuring transparency, replicability, and spatial consistency.

The analysis is conceived as a strategic planning support tool rather than a detailed feasibility study, providing a policy-oriented overview of the role of rooftop photovoltaics in regional energy strategies. By prioritizing built environments, the approach aligns renewable energy deployment with land conservation, cost-effectiveness, and environmental justice, while offering a transferable framework for planners and supporting future refinements with higher-resolution data and regulatory constraints.

Quantifying multisensory landscape perception along rural walking trails is increasingly relevant for the planning of sustainable rural infrastructures. This study develops and tests a GIS-based methodological framework integrating land-use data with visual and acoustic perception indicators to assess landscape quality along rural routes. The approach was applied to a representative section of the Way of St. Francis in Tuscany (Italy), characterised by a transition from peri-urban to agricultural and forested landscapes. Land use was analysed using Corine Land Cover data within a 40 m buffer along the trail, enabling calculation of ecotope frequency, Shannon diversity and evenness indices, a land-use sustainability index, and a Use and Coverage GIS Perception Index. Multisensory field surveys documented visual perception through panoramic photography and measurements of visual openness, while acoustic perception was assessed using AudioMoth devices to distinguish bio-, geo- and anthropogenic sound components. Data were integrated into composite GIS-based indices of visual and soundscape quality. Results indicate medium to high perceptual quality, driven by forest–agricultural mosaics despite localized anthropogenic pressures. The framework demonstrates how multisensory perception can be translated into spatial indicators supporting rural trail planning and sustainable landscape management.

The need to enhance the adaptation of cities to climate change has prompted integrated approaches to urban green (UG) planning that increase climate mitigation and urban resilience. Among UG infrastructures, green roofs (GR) represent an effective solution to improve the environmental sustainability of the built environment. Research has highlighted the ecosystem services provided by UG systems and the importance of plant selection and substrate management for optimizing GR performances, including urban heat reduction, air quality improvement, stormwater management, and building insulation. In this context, it is essential to study alternative plant species management on specific substrates.

The aim of this study was to evaluate the performance of multipurpose, low-maintenance herbaceous plants grown on experimental GR modules under controlled conditions. The study compared modules treated with chemical fertilizers and modules treated with biomass from catch crops used as green manure. Plant performance was assessed through fresh and dry biomass, plant cover ratio, and chlorophyll content.

Results show that plants treated with green manure produced significantly higher biomass and vegetation cover than those treated with chemical fertilizers, and that the catch-crop species growth contributed to the biomass and vegetation cover, suggesting that they can represent a sustainable option for GR management.

Green Infrastructure (GI) is designed and managed to deliver a wide range of ecosystem services in both rural and urban settings. It is a fundamental resource for well-being and climate change mitigation. For these reasons, it should be well distributed and equally accessible to the entire population, close to where people live.

This study aims to assess the distribution and accessibility of GI in two European cities, Milan and Vienna. The methodology adopted the “3-30-300” rule as reference framework (Konijnendijk C.C., 2022) to evaluate both spatial and socioeconomic disparities, combining spatial and statistical analyses. Tree visibility (“3” rule) was quantified by identifying trees within 30 m of residential buildings windows. The percentage of green cover (“30” rule) was derived from land-use databases, while a network analysis was conducted to measure proximity and accessibility (“300” rule). Socioeconomic variables and their relationships with GI metrics were explored through cluster and statistical analyses.

Results revealed heterogeneous yet encouraging distribution of all parameters in both cities, with inequities in tree visibility and green cover in Vienna, and in accessibility in Milan.

The integrated GIS and statistical approach applied within the 3-30-300 framework helps to assess the equity of GI distribution across urban contexts.

Urban green spaces are critical for mitigating climate change and enhancing biodiversity, yet efficient management requires detailed tree inventories, often hindered by the high costs and labor intensity of manual data collection. This study evaluates the efficacy of low-cost geomatic techniques against professional-grade equipment for the census of "Ascolana Tenera" olive trees in Ascoli Piceno, Italy. Using 18 specimens as a case study, three 3D modeling methodologies were rigorously tested: professional mobile laser scanning (KAARTA-Stencil 2), consumer-grade LiDAR on an iPhone 14 Pro Max, and terrestrial photogrammetry processed with Structure from Motion (SfM) algorithms. Results indicate that while the professional scanner enables rapid data acquisition in large-scale environments, it often produces noisy point clouds during trunk measurements. In contrast, the iPhone 14 Pro Max provided highly precise measurements of trunk diameter and tree height, offering a superior cost-to-accuracy ratio for smaller urban plots. Photogrammetry yielded the highest point density but required significant computational processing time. Ultimately, the study concludes that integrated mobile LiDAR technology is a robust, accessible solution for municipalities to meet mandatory environmental criteria and quantify carbon sequestration, facilitating sustainable urban planning and the preservation of local agricultural heritage.

The rapid deployment of photovoltaic systems in agricultural landscapes calls for scalable monitoring approaches that support sustainable energy planning. This study evaluates the effectiveness of a Geographic Object-Based Image Analysis (GEOBIA) methodology in eCognition for detecting ground-mounted solar panels in agricultural fields in the Marche using Sentinel-2 multispectral imagery. Multiresolu-tion segmentation was used to generate homogeneous image objects, followed by rule-based classification that integrates spectral, spatial, and contextual features to differen-tiate photovoltaic arrays from cropland, bare soil, and built-up areas. Results indicate that, despite its 10–20 m spatial resolution, Sentinel-2 imagery can identify medium- to large-scale solar installations when coupled with object-based techniques. The ap-proach successfully captured the shape, texture, and spectral behavior of panel clusters embedded in agricultural matrices. An accuracy assessment is underway to quantify classification performance and validate model robustness. The proposed framework demonstrates strong potential as a cost-effective and transferable tool for regional-scale monitoring of renewable energy infrastructure, supporting integrated energy–agricul-ture planning and sustainable rural development strategies.