Multi-instrumental Analysis of the Extreme Meteorological Event Occurred in Matera (Italy) on November 2019
Contributo in Atti di convegno
Data di Pubblicazione:
2021
Abstract:
Most of the municipalities of the Italian territory are located in areas of high hydrogeological risk, i.e. exposed to flooding and landslides. Consequently, part of the existing cultural heritage on the national territory is located in areas subject to flood risk, which compromises the accessibility, preservation and integrity of cultural heritage. As an example, we consider a single flood event that occurred in southern Italy on November 11th and 12th, 2019, which mainly affected the city of Matera and its surroundings. This episode appears to be significant for the violence of the phenomenon that led to considerable quantities of water flowing inside the city, a UNESCO World Heritage Site, causing damage to buildings, including historical ones. The event has been analysed using both meteorology and geomatic technologies, to have an overview on spatial and temporal evolution of the phenomenon. Global Navigation Satellite System Zenith Total Delay (GNSS-ZTD) data obtained by receivers located around the city of Matera, were compared with measurements from ground-based devices (i.e. weather stations), Numerical Weather Prediction (NWP) models, and ERA5 reanalysis. To assess the extent of the flood and show the flooded areas, the images provided by the Sentinel-1 Synthetic Aperture Radar (SAR) were used, isolating and analyzing the images captured before and after the event. Finally, through a digital terrain model, developed using Agisoft Metashape software from satellite images, the morphology of Matera was recreated to evidence the areas of accumulation of water. Once all the information was obtained, the data correlated showed an overall view of the event.
Tipologia CRIS:
4.1 Contributo in Atti di convegno
Keywords:
Photogrammetry; GNSS; Meteorology; Cultural heritage; Flooding
Elenco autori:
Coletta, V; Mascitelli, A; Bonazza, A; Ciarravano, A; Federico, S; Prestileo, F; Torcasio, Rc; Dietrich, S
Link alla scheda completa:
Titolo del libro:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Volume 12956 LNCS
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