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Author  |
Haiyan Hao; Yan Wang |
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Title |
Hurricane Damage Assessment with Multi-, Crowd-Sourced Image Data: A Case Study of Hurricane Irma in the City of Miami |
Type |
Conference Article |
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Year |
2020 |
Publication |
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2020 |
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Pages |
825-837 |
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Keywords |
Computer Vision, Damage Assessment, Disaster Management, Insurance Claims, Social Networking Platforms. |
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Abstract |
The massive crowdsourced data generated on social networking platforms (e.g. Twitter and Flickr) provide free, real-time data for damage assessment (DA) even during catastrophes. Recent studies leveraging crowdsourced data for DA mainly focused on analyzing textual formats. Crowdsourced images can provide rich and objective information about damage conditions, however, are rarely researched for DA purposes. The highly-varied content and loosely-defined damage forms make it difficult to process and analyze the crowdsourced images. To address this problem, we propose a data-driven DA method based on multi-, crowd-sourced images, which includes five machine learning classifiers organized in a hierarchical structure. The method is validated with a case study investigating the damage condition of the City of Miami caused by Hurricane Irma. The outcome is then compared with a metric derived from NFIP insurance claims data. The proposed method offers a resource for rapid DA that supplements conventional DA methods. |
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Address |
University of Florida; University of Florida |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Abbreviated Series Title |
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Edition |
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ISSN |
978-1-949373-27-73 |
ISBN |
2411-3459 |
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Track |
Social Media for Disaster Response and Resilie |
Expedition |
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Conference |
17th International Conference on Information Systems for Crisis Response and Management |
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Notes |
hhao@ufl.edu |
Approved |
no |
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Call Number |
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Serial |
2274 |
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