Dynamic maps of human exposure to floods based on mobile phone data
<p>Floods are acknowledged as one of the most serious threats to people's lives and properties worldwide. To mitigate the flood risk, it is possible to act separately on its components: hazard, vulnerability, exposure. Emergency management plans can actually provide effective non-structur...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-12-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | https://nhess.copernicus.org/articles/20/3485/2020/nhess-20-3485-2020.pdf |
| Summary: | <p>Floods are acknowledged as one of the most serious
threats to people's lives and properties worldwide. To mitigate the flood
risk, it is possible to act separately on its components: hazard,
vulnerability, exposure. Emergency management plans can actually provide
effective non-structural practices to decrease both human exposure and
vulnerability. Crowding maps depending on characteristic time patterns,
herein referred to as dynamic exposure maps, represent a valuable tool to
enhance the flood risk management plans. In this paper, the suitability of
mobile phone data to derive crowding maps is discussed. A test case is
provided by a strongly urbanized area subject to frequent flooding located
on the western outskirts of Brescia (northern Italy). Characteristic
exposure spatiotemporal patterns and their uncertainties were detected
with regard to land cover and calendar period. This novel methodology still
deserves verification during real-world flood episodes, even though it
appears to be more reliable than crowdsourcing strategies, and seems to have
potential to better address real-time rescues and relief supplies.</p> |
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| ISSN: | 1561-8633 1684-9981 |