In this paper we study the problem of flood detection and quantification using online media and satellite data. We present a three approaches, two of them based on neural networks and a third one based on the combination of different bands of satellite images. This work aims to detect floods and also give relevant information about the flood situation such as the water level and the extension of the flooded regions, as specified in the three subtasks, for which of them we propose a specific solution.

AI-Based Flood Event Understanding and Quantifying Using Online Media and Satellite Data / Zaffaroni, Mirko; Lopez Fuentes, Laura; Farasin, Alessandro; Garza, Paolo; Skinnemoen, Harald. - ELETTRONICO. - 2670:(2019), pp. 1-3. ((Intervento presentato al convegno MediaEval 2019 Multimedia Benchmark Workshop tenutosi a EURECOM - Sophia Antipolis nel 27/10/2019.

AI-Based Flood Event Understanding and Quantifying Using Online Media and Satellite Data

Alessandro Farasin;Paolo Garza;
2019

Abstract

In this paper we study the problem of flood detection and quantification using online media and satellite data. We present a three approaches, two of them based on neural networks and a third one based on the combination of different bands of satellite images. This work aims to detect floods and also give relevant information about the flood situation such as the water level and the extension of the flooded regions, as specified in the three subtasks, for which of them we propose a specific solution.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2846167