13° Workshop tematico di Telerilevamento

The study propose to investigate and represent the great environmental and urban heritage by acquiring spatial data with remote sensing techniques. In particular, we will start with the use of multispectral satellite images, taking advantage of the effective knowledge of automatic (or semi-automatic) extraction of land cover data and detailed information about the investigated areas in order to create a parametric model of the city for urban planning management. The case study is the city of L’Aquila (Abruzzo, Italy) and its hamlets, affected by the tragic 2009 earthquake event, as well as an area of continuous transformation. Several spectral indices and the presence of any heat islands from the multispectral images were extracted, useful for further analysis. About the indices, the NDVI (Normalized Difference Vegetation Index) was obtained from the World-View 2 image to analyse the split between built-up area and vegetation and the vigour status of public parks and gardens (1). In addition, some other spectral indices related to the built-up area are investigated, such as the NDYG (Normalized Difference Yellow Green) and the NDNB (Normalized Difference NIR1 and Blue) to identify respectively the presence of tiles (2) and the presence of asbestos in the roofs (3) in the existing buildings. Finally, additional indices were extracted such as NDWI, Normalized Difference Water Index, for the water-body related to lakes, rivers or anthropogenic features such as swimming pools (1) and WV-II, WorldView New Iron Index, to identify elements with the presence of iron oxide (4). In addition, the topic focuses attention on describing the distribution of the Urban Heat Island (UHI) phenomenon through the potential investigation of surface temperature derived from the Thermal Infrared band (TIR) and NDVI. Landsat 8 images, considered over the summer period 2013-2018-2019, were used for obtaining an initial estimate of Top of Atmosphere (TOA) (5). Then, using the NDVI index, Proportion of Vegetation (Pv) was extracted and the ground emissivity was obtained (6). Finally, the LST (Land Surface Temperature) equation was applied to obtain the surface temperature map (6). This procedure is useful for identifying possible UHI in the territory, i.e., those urban areas that are significantly hotter than the surrounding rural areas due to anthropogenic activities. The new data obtained from the multispectral images were then added to the DBTR (Territorial Regional DataBase – the open database of the Regional Geoportal) through spatial analysis procedures in GIS (Geographic Information System), to update the information collected into the official regional sources. Then, the updated database was used by means Rhino’s Grasshopper plugin, to build an extended 3D urban model, called CIM (City Information Modeling), useful for urban planning management. Through the analysis of the area, it is possible to highlight the presence of critical issues, from which respective strategies can be outlined, fostering an environmentally sustainable policy. For example, in order to reduce the effects of UHI, it is possible to analyse and cross the data obtained by the multispectral images (LST, NDVI and other vegetation indices), increasing green areas in densely populated urban areas, thus reclaiming and redeveloping. Furthermore, thanks to the high frequency of satellite image acquisition, it is possible to have up-to-date urban planning databases and the possibility to monitor the corrective strategies/ actions implemented. In this paper, the potential of remote sensing by high-resolution multispectral satellite imagery is crucial both to deepen and learn more about the investigated area and to obtain updated information in a short time. In conclusion, the body of information, extracted by multispectral images, will allow for the future monitoring of different aspects of the in-depth areas using new digital technologies, e.g., CIM, proposing diversified solutions based on the source data and targeted to the precise and timely needs of the area.