This paper illustrates a land consumption map for Italy (year 2017) at a scale 1:1,300,000, and the assessment of its changes (2012–2017). We define land consumption as the replacement of a non-artificial land cover to an artificial land cover, both permanent and no-permanent. The maps are a 10 m spatial resolution raster, produced by photointerpretation of very high resolution images and semiautomatic classification of high resolution remote sensing images. An overall accuracy of 97.7% for the map of 2012 and of 99.66% for the map of 2017 was obtained. The results suggest that the method proposed is appropriate to detect land consumption, both for the urban densification and for the sprawling phenomena, from national to local level. Furthermore, because of the high spatial resolution and the classification scheme adopted, it is suitable for an effective monitoring system, compared to other existing classification systems or monitoring programs.

Urbanization and related land consumption are one of the main causes of ecosystem services loss. This is especially the case for soil-related services affecting ecosystem functions and limiting accessibility to natural resources. Satellite remote sensing and environmental databases enable in-depth analysis of urban expansion and land changes, which can be used to monitor trends in the provision of ecosystem services. This work aims to describe a multilayered approach to the assessment of biophysical loss of ecosystem services flows in Italy caused by an increase in land consumption in the period 2012–2020. The results show higher losses in wood production, carbon storage, hydrological regime regulation, and pollination in the northern regions of Italy, as well as in some southern regions, such as Campania and Apulia. Habitat quality loss is widespread throughout Italy, whereas crop production loss varies on the basis of the locations in which it occurs and the crop types involved. Loss of arable land and fodder production mainly occurs in northern regions, whereas southern regions have experienced a drop in permanent crop production. This study highlights the importance of using integrated data and methodologies for well-founded approaches, with a view to gaining a thorough understanding of ecosystem services-related processes and the changes connected therewith.

Land consumption is the increase in artificial land cover, which is a major issue for environmental sustainability. In Italy, the Italian Institute for Environmental Protection and Research (ISPRA) and National System for Environmental Protection (SNPA) have the institutional duty to monitor land consumption yearly, through the photointerpretation of high-resolution images. This study intends to develop a methodology in order to produce maps of land consumption, by the use of the semi-automatic classification of multitemporal images, to reduce the effort of photointerpretation in detecting real changes. The developed methodology uses vegetation indices calculated over time series of images and decision rules. Three variants of the methodology were applied to detect the changes that occurred in Italy between the years 2018 and 2019, and the results were validated using ISPRA official data. The results show that the produced maps include large commission errors, but thanks to the developed methodology, the area to be photointerpreted was reduced to 7300 km² (2.4% of Italian surface). The third variant of the methodology provided the highest detection of changes: 70.4% of the changes larger than 100 m² (the pixel size) and over 84.0% of changes above 500 m². Omissions are mainly related to single pixel changes, while larger changes are detected by at least one pixel in most of the cases. In conclusion, the developed methodology can improve the detection of land consumption, focusing photointerpretation work over selected areas detected automatically.

For the first time in human history, over half of the world’s population lives in urban areas. This rapid growth makes cities more vulnerable, increasing the need to monitor urban dynamics and its sustainability. The aim of this work is to examine the spatial extent of urban areas, to identify the urban–rural continuum, to understand urbanization processes, and to monitor Sustainable Development Goal 11. In this paper, we apply the methodology developed by the European Commission-Joint Research Center for the classification of the degree of urbanization of the Italian territory, using the ISPRA land consumption map and the ISTAT population data. The analysis shows that the availability of detailed and updated spatialized population data is essential to calculate SDG indicator 11.3.1, which assesses the ratio of land consumption rate to population growth rate. Three new indicators are also proposed to describe the main trends in urban sprawl, analyzing the spatial distribution of land consumption in terms of infill and settlement dispersion. The research shows good results in identifying class boundaries and describing the Italian urbanized landscape, highlighting the need for more detailed spatialized demographic data. The classification obtained lends itself to a variety of applications, such as monitoring land consumption, settlement dynamics, or the urban heat islands, and assessing the presence and state of green infrastructures in the urban context, driving the development of policies in urban areas toward sustainable choices focused on urban regeneration.

Nowadays, Land Degradation Neutrality (LDN) is on the political agenda as one of the main objectives in order to respond to the increasing degradation processes affecting soils and territories. Nevertheless, proper implementation of environmental policies is very difficult due to a lack of the operational, reliable and easily usable tools necessary to support political decisions when identifying problems, defining the causes of degradation and helping to find possible solutions. It is within this framework that this paper attempts to demonstrate a new valuable web-based operational LDN tool as a component of an already running Spatial Decision Support System (S-DSS) developed on a Geospatial Cyberinfrastructure (GCI). The tool could be offered to EU administrative units (e.g., municipalities) so that they may better evaluate the state and the impact of land degradation in their territories. The S-DSS supports the acquisition, management and processing of both static and dynamic data, together with data visualization and on-the-fly computing, in order to perform modelling, all of which is potentially accessible via the Web. The land degradation data utilized to develop the LDN tool refer to the SDG 15.3.1 indicator and were obtained from a platform named Trends.Earth, designed to monitor land change by using earth observations, and post-processed to correct some of the major artefacts relating to urban areas. The tool is designed to support land planning and management by producing data, statistics, reports and maps for any EU area of interest. The tool will be demonstrated through a short selection of practical case studies, where data, tables and stats are provided to challenge land degradation at different spatial extents. Currently, there are WEBGIS systems to visualize land degradation maps but—to our knowledge—this is the first S-DSS tool enabling customized LDN reporting at any NUTS (nomenclature of territorial units for statistics) level for the entire EU territory.