摘要：Floods are acknowledged as one of the most seriousthreats to people's lives and properties worldwide. To mitigate the floodrisk, it is possible to act separately on its components: hazard,vulnerability, exposure. Emergency management plans can actually provideeffective non-structural practices to decrease both human exposure andvulnerability. Crowding maps depending on characteristic time patterns,herein referred to as dynamic exposure maps, represent a valuable tool toenhance the flood risk management plans. In this paper, the suitability ofmobile phone data to derive crowding maps is discussed. A test case isprovided by a strongly urbanized area subject to frequent flooding locatedon the western outskirts of Brescia (northern Italy). Characteristicexposure spatiotemporal patterns and their uncertainties were detectedwith regard to land cover and calendar period. This novel methodology stilldeserves verification during real-world flood episodes, even though itappears to be more reliable than crowdsourcing strategies, and seems to havepotential to better address real-time rescues and relief supplies.
