Active governance of agro-pastoral, forest and protected areas mitigates wildfire impacts in Italy.

Wildfire regimes affected by global change have been the cause of major concern in recent years. Both direct prevention (e.g., fuel management planning) and land governance strategies (e.g., agroforestry development) can have an indirect regulatory effect on wildfires. Herein, we tested the hypothesis that active land planning and management in Italy have mitigated wildfire impacts in terms of loss of ecosystem services and forest cover, and burned wildland-urban interface, from 2007 to 2017. At the national scale, we assessed the effect size of major potential fire drivers such as climate, weather, flammability, socio-economic descriptors, land use changes, and proxies for land governance (e.g., European funds for rural development, investments in sustainable forest management, agro-pastoral activities), including potential interactions, on fire-related impacts via Random Forest modelling and Generalized Additive Mixed Model. Agro-forest districts (i.e., aggregations of neighbouring municipalities with homogeneous forest and agricultural characteristics) were used as spatial units of analysis. Our results confirm that territories with more active land governance show lower wildfire impacts, even under severe flammability and climatic conditions. This study supports current regional, national, and European strategies towards "fire resistant and resilient landscapes" by fostering agro-forestry, rural development, and nature conservation integrated policies.

A functional seasonal thermal hot-spot classification: Focus on industrial sites.

This study was focused on the metropolitan area of Florence in Tuscany (Italy) with the aim to provide a functional spatial thermal anomaly indicator obtained throughout a thermal summer and winter hot-spot detection. The hot-spot analysis was performed by applying Getis-Ord Gi* spatial statistics to Land Surface Temperature (LST) layers, obtained from Landsat 8 remote sensing data during the 2015-2019 daytime summer and winter period, to delimitate summer hot- and cool-spots, and winter warm- and cold-spots. Further, these ones were spatially combined thus obtaining a comprehensive summer-winter Thermal Hot-Spot (THSSW) spatial indicator. Winter and summer mean daily thermal comfort profiles were provided for the study area assessing the Universal Thermal Climate Index (UTCI) by using meteorological data available from seven local weather stations, located at a maximum distance of 350 m from industrial sites. A specific focus on industrial sites was carried out by analyzing the industrial buildings characteristics and their surrounding areas (50 m buffer), through the following layers: industrial building area (BA), surface albedo of buildings (ALB), impervious area (IA), tree cover (TC), and grassland area (GA). The novel THSSW classification applied to industrial buildings has shown that about 50% of the buildings were located in areas characterized by summer hot-spots. Increases in BA and IA revealed warming effects on industrial buildings, whereas increases in ALB, TC, and GA disclosed cooling effects. A decrease of about 10% of IA replaced by TC and GA was associated with about 2 °C decrease of LST. Very strong outdoor heat stress conditions were observed during summer daytime, whereas moderate winter outdoor cold stress conditions were recorded during nighttime until the early morning. The thermal spatial hot-spot classification in industrial areas provides a very useful source of information for thermal mitigation strategies aimed to reduce the heat-related health risk for workers.

Surface urban heat islands in Italian metropolitan cities: Tree cover and impervious surface influences.

Land surface temperature (LST) predictors, such as impervious and vegetated surfaces, strongly influence the urban landscape mosaic, also changing microclimate conditions and exacerbating the surface urban heat island (SUHI) phenomenon. The aim of this study was to investigate the summer daytime SUHI phenomenon and the role played by impervious and tree cover surfaces in the 10 Italian peninsular metropolitan cities. Summer daytime LST values were assessed by using MODIS data referred to the months of June, July and August from 2016 to 2018. High spatial resolution (10 m) of impervious surface and tree cover layers was calculated based on open-data developed by the Italian National Institute for Environmental Protection and Research. A novel informative urban surface landscape layer was developed combining impervious surfaces and tree cover densities and its mapping for metropolitan cities was performed. Summer daytime SUHI rose significantly, increased especially in inland cities, by increasing the size of areas with low tree cover densities in the metropolitan core (or decreasing areas with low tree cover densities outside the metropolitan core), further increasing its intensity when the impervious density grew. A mitigating effect of the sea on daytime LST and SUHI was observed on coastal cities. The most intense SUHI phenomenon was observed in Turin (the largest Italian metropolitan city): for every 10% increase in areas with highly impervious surfaces and low tree cover densities in the metropolitan core, the SUHI significantly (p < 0.001) increased by 4.0 °C. Increased impervious surfaces combined with low tree cover densities represented the main driving process to increase the summer daytime SUHI intensity in most studied cities. These findings are useful to identify summer daytime LST critical areas and to implement the most efficient urban-heat-island mitigation strategies in order to safeguard the vulnerable urban environment and enhance quality of life for the population.

Land consumption monitoring: an innovative method integrating SAR and optical data.

In this paper, the use of synthetic aperture radar (SAR) for the monitoring of land consumption is analyzed. The paper presents an automatic procedure that integrates SAR and optical data, which can be effectively used to generate land consumption maps or update existing maps. The main input of the procedure is a series of SAR amplitude images acquired over a given geographical area and observation period. The main assumption of the procedure is that land consumption is associated with an increase of the SAR amplitude values. Such an increase is detected in the SAR amplitude time series using an automatic Bayesian algorithm. The results based on the SAR amplitude are then filtered using an NDVI map derived from optical imagery. The effectiveness of the proposed procedure is illustrated using SAR data from the Sentinel-1 and TerraSAR-X sensors, and optical data from the Sentinel-2 sensor.

Assessing habitat quality in relation to the spatial distribution of protected areas in Italy.

The conservation of species and habitats is increasingly threatened by anthropogenic impacts, particularly land use change, from local to global scales. Although many efforts have been carried out so far to halt or at least reduce the biodiversity loss (e.g., the establishment of protected areas' networks), there are still both knowledge and policy gaps slowing the conservation of species and habitats in complex environments, such as the Mediterranean region. In particular, the human-driven impacts and threats on biodiversity need more careful analysis. Accordingly, this paper aims to assess the habitat quality and degradation in Italy in relation with the spatial pattern of the current protected areas' network, mainly to identify priority areas of intervention, thus supporting large-scale conservation strategies. A survey of experts was conducted to identify the main threats for biodiversity from different land uses at the national scale. The InVEST software was then applied to assess and map habitat quality and degradation with a high spatial resolution (20 m). The relationship between habitat quality and degradation as well as their hotspots, and alternative PA categories were also explored. Results indicate that: (i) habitat quality and degradation depend on the location and intensity of the anthropogenic impacts and are sensitive to different protection levels; (ii) the combination of the survey of experts and the spatially-explicit assessment of habitat quality and degradation is useful to highlight variations of the current conditions of biodiversity and habitats; and (iii) the identification of hotspots allows one to identify priority areas for conservation. Accordingly, the proposed approach may be used to strengthen the conservation efforts in similar contexts, and thus support the implementation of the biodiversity-related policies over the long term.

The impact of built-up surfaces on land surface temperatures in Italian urban areas.

Urban areas are characterized by the very high degree of soil sealing and continuous built-up areas: Italy is one of the European countries with the highest artificial land cover rate, which causes a substantial spatial variation in the land surface temperature (LST), modifying the urban microclimate and contributing to the urban heat island effect. Nevertheless, quantitative data regarding the contribution of different densities of built-up surfaces in determining urban spatial LST changes is currently lacking in Italy. This study, which aimed to provide clear and quantitative city-specific information on annual and seasonal spatial LST modifications resulting from increased urban built-up coverage, was conducted generally throughout the whole year, and specifically in two different periods (cool/cold and warm/hot periods). Four cities (Milan, Rome, Bologna and Florence) were included in the study. The LST layer and the built-up-surface indicator were obtained via use of MODIS remote sensing data products (1km) and a very high-resolution map (5m) of built-up surfaces recently developed by the Italian National Institute for Environmental Protection and Research. The relationships between the dependent (mean daily, daytime and nighttime LST values) and independent (built-up surfaces) variables were investigated through linear regression analyses, and comprehensive built-up-surface-related LST maps were also developed. Statistically significant linear relationships (p<0.001) between built-up surfaces and spatial LST variations were observed in all the cities studied, with a higher impact during the warm/hot period than in the cool/cold ones. Daytime and nighttime LST slope patterns depend on the city size and relative urban morphology. If implemented in the existing city plan, the urban maps of built-up-surface-related LST developed in this study might be able to support more sustainable urban land management practices by identifying the critical areas (Hot-Spots) that would benefit most from mitigation actions by local authorities, land-use decision makers, and urban planners.

Integration of land use and land cover inventories for landscape management and planning in Italy.

There are both semantic and technical differences between land use (LU) and land cover (LC) measurements. In cartographic approaches, these differences are often neglected, giving rise to a hybrid classification. The aim of this paper is to provide a better understanding and characterization of the two classification schemes using a comparison that allows maximization of the informative power of both. The analysis was carried out in the Molise region (Central Italy) using sample information from the Italian Land Use Inventory (IUTI). The sampling points were classified with a visual interpretation of aerial photographs for both LU and LC in order to estimate surfaces and assess the changes that occurred between 2000 and 2012. The results underscore the polarization of land use and land cover changes resulting from the following: (a) recolonization of natural surfaces, (b) strong dynamisms between the LC classes in the natural and semi-natural domain and (c) urban sprawl on the lower hills and plains. Most of the observed transitions are attributable to decreases in croplands, natural grasslands and pastures, owing to agricultural abandonment. The results demonstrate that a comparison between LU and LC estimates and their changes provides an understanding of the causes of misalignment between the two criteria. Such information may be useful for planning policies in both natural and semi-natural contexts as well as in urban areas.

Estimating river pollution from diffuse sources in the Viterbo province using the potential non-point pollution index.

This paper describes the application of the Index of Potential Non-point Pollution (PNPI) to the territory of the Viterbo Province (Central Italy). PNPI is a GIS tool that allows managers to assess the pressure on surface aquatic ecosystems deriving from diffuse sources of pollution. The index aims to assemble the available environmental datasets and specialists' expertise to set up a user-friendly and informative tool that can support decision-making processes and foster a multi-disciplinary approach. The index calculation is described and results are reported in order to give an overview of PNPI possible applications.

River pollution from non-point sources: a new simplified method of assessment.

Assessment of the pollution of water bodies from non-point sources is a complex data- and time-consuming task. The potential non-point pollution index (PNPI), is a new tool designed to assess the global pressure exerted on rivers and other surface water bodies by different land uses. The main feature of PNPI is the wide availability of its input data. Very detailed input maps, often lacking over many areas, are not needed for PNPI calculation. As a consequence of the input data used, the modelling of physical reality and of processes is heavily simplified. The authors counterbalanced such a simplification using an 'expert system' approach. The system bypasses the accurate representation of the physical reality to assess globally the pollution potential of different land uses according to the judgement of scientists. The scientific community proposes many models for depicting the dynamics of pollutants coming from diffuse sources. Most of them can be grouped into two broad categories: statistical models and physically based models. PNPI belongs to neither of the above-mentioned groups. PNPI is a GIS-based, watershed-scale tool designed to inform decision makers and public opinion about the potential environmental impacts of different land management scenarios. PNPI applies the multicriteria technique to pollutant dynamics and water quality. The pressure exerted on water bodies by diffuse pollution coming from land units is expressed as a function of three indicators: land use, run-off and distance from the river network. They are calculated from land use data, geological maps and a digital elevation model (DEM). The weights given to different land uses and to the three indicators were set according to experts' evaluations and allow calculation of the value of the PNPI for each node of a grid representing the watershed; the higher the PNPI of the cell, the greater the potential impact on the river network. The output of the calculation is presented in the form of maps that highlight areas that are more likely to produce pollution. Last, possibilities, strategies and results of the validation of the PNPI are described. In the authors' view, the explicit link between land use and potential pollution on which PNPI is based, together with its high communication potential, make it particularly interesting for a participatory and integrated approach to land management and environmental protection.

[Watercourses protection and urban planning]. / La tutela dei corsi d'acqua e la pianificazione territoriale.

The work analyses the complex relationships that link urban planning and environmental protection referring, in particular, to watercourses defence. The close interactions existing between development of human activities on territory and the hydrological cycle point out the necessity of a watershed-scale planning. This regional planning, in fact, allows both problems of protection and optimal use of hydrological resources in terms not only of punctual actions, but also of land use. In this context, the fundamental roles played by geographical and environmental information systems are shown and analysed with special regard to their importance in fostering citizens participation in decisional processes by means of an easier access to environmental data and information available to public authorities.