基于地理信息系统(GIS)的救护车运输服务路网分析——以埃塞俄比亚亚的斯亚贝巴Arada分城为例

Mikir Kassaw, Bedasa Asefa
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引用次数: 2

摘要

事故发生后黄金时段的最佳利用率是衡量救护车服务管理系统减少生命和财产损失有效性的一个指标。本文以阿拉达副城市为例进行了研究,该副城市位于首都亚的斯亚贝巴中部,面积11.56平方公里,是所有副城市中最古老的。人口密度高,约212009人,人口密度分布约为每平方公里18340人。在研究区域内,现有的道路网条件没有随着人口增长而发展。因此,在灾难发生时,高效救护车运输服务对正确目标区域的响应率很低,不能满足客户的满意度。因此,本研究的目的是在地理信息系统(GIS)环境下进行路网分析,以改善副城市的救护车运输服务。利用Arc GIS软件,在网络分析员的扩展下,建立了道路网络、救护车位置、事故地点和医院的详细GIS数据库。在这项研究中,一个救护站、三个事故地点和六家医院被用于计算1、2和4分钟的服务区域和最佳路线分析。阻抗值1、2和4分钟分别对应于非常紧急、中等紧急和低紧急服务区域。在非常紧急的服务领域,约有33%的卫生中心,而在中度和低度紧急的服务区域,分别约有65%和100%的卫生中心。这意味着,目前的选择将健康中心服务领域比现有方法增加了34%。此外,选定的救护车运输服务最佳路线样本是根据行驶时间(分钟)和燃料消耗量(垃圾)计算的。因此,所选样本最佳路线的估计旅行时间约为每年870/30482.20和1138.5/3772.16分钟/比尔。这意味着,拟议的研究比现有研究减少了268.5/723.96分钟/比尔的总旅行时间和成本。为此,开发了基于GIS的救护车运输服务原型模型。
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Road Network Analysis for Ambulance Transportation Service Using Geographical Information System (GIS): A Case of Arada Sub-City, Addis Ababa, Ethiopia
Optimum utilization of time after an accident which is golden hour serves as a measure of effectiveness of ambulance service management system to reduce the loss of life and property. This paper presents a case study on Arada sub-city which is the oldest of all sub-cities located in the central part of the capital Addis Ababa with 11.56 Km2 area wide. Its population, which is around 212,009, is highly dense and its spread of population density is about 18340 people per Km2. In the study area, the existing road network condition is not developing in line with the population growth. Accordingly, at time of disaster, the responsiveness rate of efficient ambulance transportation services to the right target area is low and unsatisfactory to level of customer’s satisfaction. Therefore, the purpose of this study is to conduct road network analysis in Geographic Information System (GIS) environment for the betterment of ambulance transportation service in the sub city. A detail GIS database of the road network, ambulance location, accident locations and hospitals was prepared using Arc GIS software with the extension of network analyst. In this study, one ambulance station, three accident locations and six hospitals were used to compute 1, 2 & 4 minutes service area and best route analyses. The impedance value 1, 2 & 4 minute corresponds to very urgent, moderate urgent and low urgent service areas respectively. In very urgent service area domain about 33% of health centres are found whereas in moderate and low urgent service area domains about 65% and 100% of health centers are found respectively. This implies that, the current option increases health center service area domains by 34% from the existing approach. Besides, the selected sample best routes of ambulance transportation service are computed in terms of travelling time in minutes and its fuel consumption in litters. Accordingly, the estimated travelling time of the selected sample best route is about 870/30482.20 and 1138.5/3772.16 minutes/ birrs annually. This implies that, the proposed study decreases a total travelling duration and cost by 268.5/723.96 minutes/ birr from the existing one. As a result, GIS-based ambulance transportation service proto type model was developed.
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