Preprints
https://doi.org/10.5194/nhess-2021-368
https://doi.org/10.5194/nhess-2021-368
17 Dec 2021
 | 17 Dec 2021
Status: this preprint has been withdrawn by the authors.

The Emergency Accessibility Analysis based on Traffic Big Data and Flood Scenario Simulation in the context of Shanghai Hotel industry

Qian Yao, Jiangyang Lin, Yong Shi, Zhihao Chen, and Qingwei Wang

Abstract. Underlying the impact of global warming and rapid growth of the tourism industry, the increasing frequency of flood post threats to the sustainable development of the coastal cities in China. The article proposes a methodological approach to evaluate the emergence response capability. This approach combines the flood simulation scenario method, traffic big data with the path navigation interface of the web. This article provides an empirical study to evaluate the emergency response from Fire & Rescue Service (FRS) to the tourist hotel in Shanghai from spatial accessibility perspective. The findings show that (1). The emergency response from FRS has significant relationships with the situation of transportation, the location of hotels, the intensity of flood inundation and the number, location of the urban FRS. (2). The emergency accessibility of a city caused by floods depends on the prevailing traffic conditions. The more severe traffic congestion has a significant impact on the spatial accessibility. (3) Flooding and real-time traffic conditions can change the fastest path from FRS to tourist hotels, resulting in delays in emergency response times, and the selection of the most appropriate travel routes is critical to improving the emergency response capability of cities. The results proved the validity of this proposed approach. Consequently, the approach contributes to the enhancement of the level of emergence response ability of urban tourism when they encounter disasters.

This preprint has been withdrawn.

Qian Yao, Jiangyang Lin, Yong Shi, Zhihao Chen, and Qingwei Wang

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-368', Anonymous Referee #1, 14 Jan 2022
    • AC1: 'Reply on RC1', qian yao, 20 Mar 2022
  • RC2: 'Review on nhess-2021-368', Anonymous Referee #2, 08 Feb 2022
    • AC2: 'Reply on RC2', qian yao, 20 Mar 2022

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-368', Anonymous Referee #1, 14 Jan 2022
    • AC1: 'Reply on RC1', qian yao, 20 Mar 2022
  • RC2: 'Review on nhess-2021-368', Anonymous Referee #2, 08 Feb 2022
    • AC2: 'Reply on RC2', qian yao, 20 Mar 2022
Qian Yao, Jiangyang Lin, Yong Shi, Zhihao Chen, and Qingwei Wang
Qian Yao, Jiangyang Lin, Yong Shi, Zhihao Chen, and Qingwei Wang

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This preprint has been withdrawn.

Short summary
The article proposes an approach to evaluate the emergence response capability to tourism. This approach combines the flood simulation method, traffic big data with the path navigation interface of the web. The study found that emergency response from Fire and Rescue Service (FRS) has significant relationships with the situation of transportation, the location of hotels, the intensity of flood inundation and the location of the urban FRS. It provides reference for tourism disaster management.
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