Suchergebnisse

Abstract. Understanding city residents' collective geotagged behaviors (CGTBs) in
response to hazards and emergency events is important in disaster
mitigation and emergency response. It is a challenge, if not impossible, to
directly observe CGTBs during a real-time matter. This study used the number
of location requests (NLR) data generated by smartphone users for a variety
of purposes such as map navigation, car hailing, and food delivery to
infer the dynamics of CGTBs in response to rainstorms in eight Chinese cities. We examined rainstorms, flooding, and NLR anomalies, as well as the
associations among them, in eight selected cities across mainland China.
The time series NLR clearly reflects cities' general diurnal rhythm, and the
total NLR is moderately correlated with the total city population. Anomalies
of the NLR were identified at both the city and grid scale using the Seasonal Hybrid Extreme Studentized Deviate (S-H-ESD) method. Analysis results demonstrated that the NLR anomalies at the city and
grid levels are well associated with rainstorms, indicating that city residents
request more location-based services (e.g., map navigation, car hailing, food delivery, etc.) when there is a rainstorm. However, the sensitivity of the city residents' collective geotagged behaviors in response to rainstorms varies in different cities as shown by different peak rainfall intensity
thresholds. Significant high peak rainfall intensity tends to trigger city
flooding, which leads to increased location-based requests as shown by
positive anomalies in the time series NLR.

Abstract. Disaster-relevant authorities could make uninformed decisions due to the lack of a clear picture of urban
resilience to adverse natural events. Previous studies have seldom examined the
near-real-time human dynamics, which are critical to disaster emergency
response and mitigation, in response to the development and evolution of
mild and frequent rainfall events. In this study, we used the aggregated
Tencent location request (TLR) data to examine the variations in collective
human activities in response to rainfall in 346 cities in China. Then two
resilience metrics, rainfall threshold and response sensitivity, were
introduced to report a comprehensive study of the urban resilience to
rainfall across mainland China. Our results show that, on average, a
1 mm increase in rainfall intensity is associated with a 0.49 % increase
in human activity anomalies. In the cities of northwestern and
southeastern China, human activity anomalies are affected more by rainfall
intensity and rainfall duration, respectively. Our results highlight the
unequal urban resilience to rainfall across China, showing current heavy-rain-warning standards underestimate the impacts of heavy rains on residents in the northwestern arid region and the central underdeveloped areas
and overestimate impacts on residents in the southeastern coastal
area. An overhaul of current heavy-rain-alert standards is therefore needed
to better serve the residents in our study area.