Published in

Association for Computing Machinery (ACM), Proceedings of the ACM on Human-Computer Interaction, CSCW2(6), p. 1-16, 2022

DOI: 10.1145/3555107

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Venice Was Flooding ... One Tweet at a Time

Journal article published in 2022 by Valerio Lorini ORCID, Paola Rufolo, Carlos Castillo
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

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Data provided by SHERPA/RoMEO

Abstract

Before urban flooding actually happens, weather forecasts with varying degrees of precision are available to emergency managers. In the aftermath of the event, authoritative information including Earth Observation (EO) data can be used to estimate precisely the flood extent, possibly after several hours. This study aims to determine how social media information can reduce the inherent uncertainty of the information in the immediate aftermath of an urban flood event. Specifically, the study investigates how to collect relevant social media images and to interpolate such data in order to create a map. The premise of the study is that social media platforms, when combined with digital surface models, can provide control points for creating a reliable near real-time estimate of the flood extent. In the study, we compared a flood extent map derived from social media with that derived from authoritative altimetry data during one of the worst floods to hit Venice, which occurred in November 2019. The results of the experiments show a good overall accuracy using several digital surface models. Given the global coverage of such models and the low resources required, we think the methodology proposed could be beneficial for emergency managers. Specifically, we describe how a flood extent map can be made available within 24 h, or even less, after urban flooding strikes a densely inhabited area, where data generated by the public are available.