Natural Disasters Detection in Social Media and Satellite imagery: a survey

January 14, 2019 ยท The Cartographer ยท ๐Ÿ› Multimedia tools and applications

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: Natural Disasters Detection in Social Media and Satellite imagery: a survey"

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Authors Naina Said, Kashif Ahmad, Michael Regular, Konstantin Pogorelov, Laiq Hassan, Nasir Ahmad, Nicola Conci arXiv ID 1901.04277 Category cs.IR: Information Retrieval Cross-listed cs.SI Citations 123 Venue Multimedia tools and applications Last Checked 1 day ago
Abstract
The analysis of natural disaster-related multimedia content got great attention in recent years. Being one of the most important sources of information, social media have been crawled over the years to collect and analyze disaster-related multimedia content. Satellite imagery has also been widely explored for disasters analysis. In this paper, we survey the existing literature on disaster detection and analysis of the retrieved information from social media and satellites. Literature on disaster detection and analysis of related multimedia content on the basis of the nature of the content can be categorized into three groups, namely (i) disaster detection in text; (ii) analysis of disaster-related visual content from social media; and (iii) disaster detection in satellite imagery. We extensively review different approaches proposed in these three domains. Furthermore, we also review benchmarking datasets available for the evaluation of disaster detection frameworks. Moreover, we provide a detailed discussion on the insights obtained from the literature review, and identify future trends and challenges, which will provide an important starting point for the researchers in the field.
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