New Digital Field of Drawing and Survey for the Automatic Identification of Debris Accumulation in Flooded Areas

Carmine Gambardella, Rosaria Parente, Anna Scotto di Santolo and Giuseppe Ciaburro ()
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Carmine Gambardella: UNESCO Chair on Landscape, Cultural Heritage, and Territorial Governance, Benecon Universities Consortium, 80100 Napoli, Italy
Rosaria Parente: UNESCO Chair on Landscape, Cultural Heritage, and Territorial Governance, Benecon Universities Consortium, 80100 Napoli, Italy
Anna Scotto di Santolo: Department of Economic and Legal Sciences, Telematic University Pegaso, 80100 Napoli, Italy
Giuseppe Ciaburro: Department of Architecture and Industrial Design, Università degli Studi della Campania Luigi Vanvitelli, 81031 Aversa, Italy

Sustainability, 2022, vol. 15, issue 1, 1-23

Abstract: Floods are among the most devastating natural hazards in the world, causing the largest percentage of deaths and property damage. The impact of floods can be mitigated with an adequate knowledge of the territory, which makes it possible to better organize prevention plans with an appropriate analysis of the risk areas, which allows the management of relief efforts quickly and adequately. This work presents a methodology for mapping and monitoring the areas affected by floods and landslides by remote sensing: the correct representation and full interpretation of the territory matrix are essential for quality and sustainability design. In this paper, we used tools and technology that allow us to analyze and visualize the landscape evolution. The calibration of the method was performed on the events that took place in Calabria, in Southern Italy, on 12 August 2015. The proposed methodology concerned the planning of acquisition flights, the selection and setting of the sensors used, and the processing and post-processing of the data collected through the application of algorithms used for data manipulation and interpretation. The process of recognizing the areas with deposits of debris through the spectral signature was carried out using similarity criteria relating to hyperspectral data. The results obtained recommend the adoption of this methodology to deal with emergencies due to flood events.

Keywords: remote sensing; hyperspectral data; flood risk; spectral angle mapper (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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