The rising environmental issues on contemporary cities urgently calls for sustainable planning policies. Implementation of nature-based solutions, ecosystem services, and green infrastructures associated to green spaces management is at present of paramount importance. In contrast to policies mainly focused on public greenery, the inclusion of private green in planning strategies might be a promising pathway. The general aim is mapping and classifying urban green spaces in Padua, a city of 93.3 km² (Northeast Italy). Specific aims are (i) testing an NDVI-derived extraction from very high-resolution orthophotos; (ii) classifying property status; (iii) highlighting multilevel relationships and strategies for urban green spaces implementation and management; (iv) assessing greenery in relation to per capita population. By performing remote sensing and GIS analyses, a first detailed global map of urban green spaces in Padua was created; then, binary classification and thematic maps for rural/non-rural, public/private, municipal/non-municipal greenery were produced for all urban units. Results show that, among total green spaces (52.23 km²), more than half are rural. Moreover, private green spaces represent 80%, while within public areas (20%) less than 10% are municipal (5 km²). We therefore highlight scenarios for planning policies in Padua by providing tools to policymakers for an integrated management of green spaces, where private greenery might also contribute to ecosystem services implementation for common urban well-being.

Weed management is a crucial issue in agriculture, resulting in environmental in-field and off-field impacts. Within Agriculture 4.0, adoption of UASs combined with spatially explicit approaches may drastically reduce doses of herbicides, increasing sustainability in weed management. However, Agriculture 4.0 technologies are barely adopted in small-medium size farms. Recently, small and low-cost UASs, together with open-source software packages, may represent a low-cost spatially explicit system to map weed distribution in crop fields. The general aim is to map weed distribution by a low-cost UASs and a replicable workflow, completely based on open GIS software and algorithms: OpenDroneMap, QGIS, SAGA and OpenCV classification algorithms. Specific objectives are: (i) testing a low-cost UAS for weed mapping; (ii) assessing open-source packages for semi-automatic weed classification; (iii) performing a sustainable management scenario by prescription maps. Results showed high performances along the whole process: in orthomosaic generation at very high spatial resolution (0.01 m/pixel), in testing weed detection (Matthews Correlation Coefficient: 0.67–0.74), and in the production of prescription maps, reducing herbicide treatment to only 3.47% of the entire field. This study reveals the feasibility of low-cost UASs combined with open-source software, enabling a spatially explicit approach for weed management in small-medium size farmlands.

The Tagaeri Taromenane People are two indigenous groups belonging to the Waorani first nation living in voluntary isolation within the Napo region of the western Amazon rainforest. To protect their territory the Ecuadorean State has declared and geographically defined, by Decrees, the Zona Intangible Tagaeri Taromenane (ZITT). This zone is located within the UNESCO Yasuní Biosphere Reserve (1989), one of the most biodiverse areas in the world. Due to several hydrocarbon reserve exploitation projects running in the area and the advancing of a large-scale deforestation front, the survival of these groups is presently at risk. The general aim was to validate the ZITT boundary using the geographical references included in the Decree 2187 (2007) by analyzing the geomorphological characteristics of the area. Remote sensing data such as Digital Elevation Models (DEM), Landsat imagery, topographic cartography of IGM-Ecuador, and fieldwork geographical data have been integrated and processed by Geographical Information System (GIS). The ZITT presents two levels of geographic inconsistencies. The first dimension is about the serious cartographical weaknesses in the perimeter delimitation related to the impossibility of linking two rivers belonging to different basins while the second deals with the perimeter line not respecting the hydrographic network. The GIS analysis results clearly show that ZITT boundary is cartographically nonsense due to the impossibility of mapping out the perimeter. Furthermore, GIS analysis of anthropological data shows presence of Tagaeri Taromenane clans outside the ZITT perimeter, within oil production areas and in nearby farmer settlements, reflecting the limits of protection policies for non-contacted indigenous territory. The delimitation of the ZITT followed a traditional pattern of geometric boundary not taking into account the nomadic characteristic of Tagaeri Taromenane: it is necessary to adopt geographical approaches to recognize the indigenous right to their liveable territories in the complex territorialities enacted by different stakeholders.

The mitigation of urban heat islands (UHIs) is crucial for promoting the sustainable development of urban areas. Geographic information systems (GISs) together with satellite-derived data are powerful tools for investigating the spatiotemporal distribution of UHIs. Depending on the availability of data and the geographic scale of the analysis, different methodologies can be adopted. Here, we show a complete open source GIS-based methodology based on satellite-driven data for investigating and mapping the impact of the UHI on the heat-related elderly risk (HERI) in the Functional Urban Area of Padua. Thermal anomalies in the territory were mapped by modelling satellite data from Sentinel-3. After a socio-demographic analysis, the HERI was mapped according to five levels of risk. The highest vulnerability levels were localised within the urban area and in three municipalities near Padua, which represent about 20% of the entire territory investigated. In these municipalities, a percentage of elderly people over 20%, a thermal anomaly over 2.4 °C, and a HERI over 0.65 were found. Based on these outputs, it is possible to define nature-based solutions for reducing the UHI phenomenon and promote a sustainable development of cities. Stakeholders can use the results of these investigations to define climate and environmental policies.

Focusing on a sustainable and strategic urban development, local governments and public administrations, such as the Veneto Region in Italy, are increasingly addressing their urban and territorial planning to meet national and European policies, along with the principles and goals of the 2030 Agenda for the Sustainable Development. In this regard, we aim at testing a methodology based on a semi-automatic approach able to extract the spatial extent of urban areas, referred to as “urban footprint”, from satellite data. In particular, we exploited Sentinel-1 radar imagery through multitemporal analysis of interferometric coherence as well as supervised and non-supervised classification algorithms. Lastly, we compared the results with the land cover map of the Veneto Region for accuracy assessments. Once properly processed and classified, the radar images resulted in high accuracy values, with an overall accuracy ranging between 85% and 90% and percentages of urban footprint differing by less than 1%–2% with respect to the values extracted from the reference land cover map. These results provide not only a reliable and useful support for strategic urban planning and monitoring, but also potentially identify a solid organizational dataflow process to prepare geographic indicators that will help answering the needs of the 2030 Agenda (in particular the goal 11 “Sustainable Cities and Communities”).