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首页> 外文会议>International Symposium on Earth Hazard and Disaster Mitigation >Spatial Modeling of Infrastructure Resilience to the Natural Disasters Using Baseline Resilience Indicators for Communities (BRIC) - Case Study: 5 Districts/Cities of Bandung Basin Area
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Spatial Modeling of Infrastructure Resilience to the Natural Disasters Using Baseline Resilience Indicators for Communities (BRIC) - Case Study: 5 Districts/Cities of Bandung Basin Area

机译：基础设施对自然灾害的基础设施适应自然灾害的空间建模（Bric） - 案例研究：万隆盆地地区5区/城市

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The Bandung Basin area has highly susceptible to the natural disasters. Therefore, resilience measurement is useful to find out the capacity of an area in the facing of a natural disaster. Natural disaster resilience can be measured using BRIC (Baseline Resilience Indicators for Communities) model. This model comprises several indicators; includes social, economic, community, institution, infrastructure, and the environment. This research tries to measure resilience to the natural disasters with still focusing on infrastructure resilience measurement by spatial modeling and analyzed the dominant driving factor that contributes to this resilience trend. We generated a spatial modeling by applying a spatial analysis to the infrastructure objects. The infrastructure objects consist of the road, school, and health facilities. Those objects will be given some radius levels that indicate the resilience level by using buffer processing. An area closest to those objects will have high resilience and contrarily. Our result showed that almost all city areas (Bandung and Cimahi City) have high resilience because they have many infrastructure objects. But contrarily with the district areas which are still contained many patterns of low and moderate resilience level. The dominant driving factor of infrastructure resilience in this research area is a road. The areas which are closest to the road have high resilience and farther away from the road will have low resilience.
机译：万隆盆地地区非常易受自然灾害的影响。因此，弹性测量是有用的，无法找到面对自然灾害的区域。可以使用Bric（社区基准弹性指标）模型来衡量自然灾难恢复能力。该模型包括若干指标;包括社会，经济，社区，机构，基础设施和环境。该研究试图通过空间建模仍然专注于基础设施弹性测量的自然灾害来衡量自然灾害的抵御能力，并分析了有助于这种弹性趋势的主导驱动因素。我们通过对基础架构对象应用空间分析来生成空间建模。基础设施对象包括道路，学校和卫生设施。这些对象将给出一些半径级别，通过使用缓冲处理来指示弹性级别。最靠近这些物体的区域将具有高弹性和反之亦好。我们的结果表明，几乎所有城市地区（万隆和Cimahi City）都具有很高的弹性，因为它们有许多基础设施对象。但与区区仍然包含许多低和中度弹性水平的地区。这项研究区域的基础设施复原力的主导驱动因素是一条道路。最接近道路的区域具有高弹性，远离道路的距离将具有低弹性。

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