Research on Railway Emergency Rescue Path Selection Based on GIS

Tang, Zhaoping; Zhou, Shunhua; Geng, Biao; Sun, Jian

doi:10.1088/1755-1315/384/1/012105

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…GIS enable the user to process data with geographic information and visualise the results in interactive maps. They are often used in emergency planning and research, for example by [10,[36][37][38][39]. In ArcGIS, as well as some other GIS, automated models can be created via a graphic interface or by directly scripting them in a programming language.…”

Section: Spatial Assessment and Tessellation Methodsmentioning

confidence: 99%

System Criticality of Road Network Areas for Emergency Management Services—Spatial Assessment Using a Tessellation Approach

et al. 2020

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Emergency management services, such as firefighting, rescue teams and ambulances, are all heavily reliant on road networks. However, even for highly industrialised countries such as Germany, and even for large cities, spatial planning tools are lacking for road network interruptions of emergency services. Moreover, dependencies of emergency management expand not only on roads but on many other systemic interrelations, such as blockages of bridges. The first challenge this paper addresses is the development of a novel assessment that captures systemic interrelations of critical services and their dependencies explicitly designed to the needs of the emergency services. This aligns with a second challenge: capturing system nodes and areas around road networks and their geographical interrelation. System nodes, road links and city areas are integrated into a spatial grid of tessellated hexagons (also referred to as tiles) with geographical information systems. The hexagonal grid is designed to provide a simple map visualisation for emergency planners and fire brigades. Travel time planning is then optimised for accessing city areas in need by weighing impaired areas of past events based on operational incidents. The model is developed and tested with official incident data for the city of Cologne, Germany, and will help emergency managers to better device planning of resources based on this novel identification method of critical areas.

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Section: Spatial Assessment and Tessellation Methodsmentioning

confidence: 99%

System Criticality of Road Network Areas for Emergency Management Services—Spatial Assessment Using a Tessellation Approach

et al. 2020

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“…By analyzing the uncertain factors (such as dynamic traffic environment and traffic congestion), the path planning method is used to select the optimal path to ensure that rescue personnel and materials arrive at the fastest speed and ensure the safety of people's lives and property (Shi et al, 2022). Tang et al established the shortest path calculation model based on GIS network analysis, analyzed and calculated the railway network data set, and obtained the shortest distance from emergency rescue point to disaster point, which provided a reference for the selection of emergency rescue path of railway emergencies (Tang et al, 2019). Xu et al proposed an improved A-star algorithm to realize the rapid planning of the emergency rescue path of moving objects in a roadless environment (Xu et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Research on Emergency Rescue Response in Wenchuan County in China Based on Baidu Map Navigation Data

Zhou

Zhang²,

Li³

et al. 2022

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Earthquake disasters often cause massive casualties and property losses, so it is essential to achieve rapid emergency rescue response. Although many scholars have studied the speed of emergency rescue response from different perspectives, there are still many problems in the impact of road congestion on travel paths and distances, as well as the timeliness of the road network. Therefore, this study calculated the travel distance from the rescue point to the disaster point using the path planning method based on the Baidu map navigation data, and obtained the distribution map of the emergency rescue response level in Wenchuan County, Sichuan Province, China. The results show that :(1) the path planning method based on Baidu map navigation data is more realistic and accurate than the traditional method. (2) there are apparent spatial differences in the emergency rescue response in Wenchuan County, and the emergency rescue response level in Weizhou town in the north is higher than that in Wolong and Sanjiang town in the southwest. The research results have significant reference value for planning emergency rescue routes and improving rescue speed in Wenchuan County and similar counties.

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Research on Railway Emergency Rescue Path Selection Based on GIS

Cited by 2 publications

References 6 publications

System Criticality of Road Network Areas for Emergency Management Services—Spatial Assessment Using a Tessellation Approach

System Criticality of Road Network Areas for Emergency Management Services—Spatial Assessment Using a Tessellation Approach

Research on Emergency Rescue Response in Wenchuan County in China Based on Baidu Map Navigation Data

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