基于证据推理法的城镇综合承灾能力网格化评价方法

陈涛; 陈智超

doi:10.16511/j.cnki.qhdxxb.2018.22.024

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清华大学学报（自然科学版） ›› 2018, Vol. 58 ›› Issue (6) : 570-575. DOI: 10.16511/j.cnki.qhdxxb.2018.22.024

物理与工程物理

基于证据推理法的城镇综合承灾能力网格化评价方法

陈涛, 陈智超

作者信息 +

Comprehensive disaster-bearing capacity assessment of the urban area using grid cells based on an evidential reasoning method

CHEN Tao, CHEN Zhichao

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文章历史 +

摘要

目前针对区域综合承灾能力的研究大多仍基于城市尺度，少有针对城镇尺度的研究，且针对区域综合承灾能力的研究大多以行政单元为评价单元，精度稍显粗糙。该文根据华东某县级市实际城镇特色建立城镇综合承灾能力评价指标体系，基于证据推理法结合层次分析法，以1 km×1 km的网格为基本评价单元，从定性、定量数据两方面完成对该市综合承灾能力的评估。该文主要探索了高精度的城镇综合承灾能力评价方法，得到网格化的高精度评价结果，发现“抗灾能力→空间布局因素→重大危险源”这一指标在整体评价中具有突出重要作用，评价结果与该地区实际情况基本吻合。该评价方法对城镇级别应急管理具有很好的应用价值，对提升城镇区域减灾防灾能力有积极意义。

Abstract

Most studies on regional comprehensive disaster-bearing capacity have been based on large city scenarios with few for urban scenarios with most based on large administrative units, which leads to rough assessment results. This paper describes an index system for urban disaster-bearing capacity assessments based on the actual characteristics of an urban area in eastern China. Evidential reasoning is combined with an analytic hierarchy process to deal with qualitative and quantitative data with 1 km×1 km scale grids to assess the disaster-bearing capacity of this urban area. This paper describes the method to accurately assess the disaster-bearing capacity of the urban area with high resolution assessment results. The index of "anti-disaster ability→spatial factors→major hazard sources" plays a very important role in the whole assessment. These results are in accord with the actual situation in this area. Thus, this assessment method can be used for urban-level emergency management and to improve disaster prevention and mitigation capacities.

导出引用

陈涛, 陈智超. 基于证据推理法的城镇综合承灾能力网格化评价方法[J]. 清华大学学报（自然科学版）. 2018, 58(6): 570-575 https://doi.org/10.16511/j.cnki.qhdxxb.2018.22.024

CHEN Tao, CHEN Zhichao. Comprehensive disaster-bearing capacity assessment of the urban area using grid cells based on an evidential reasoning method[J]. Journal of Tsinghua University(Science and Technology). 2018, 58(6): 570-575 https://doi.org/10.16511/j.cnki.qhdxxb.2018.22.024

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基金

国家“十二五”科技支撑计划（2015BAK10B02）；北京市科委项目（Z161100001116010）

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收稿日期	出版日期
2017-12-06	2018-06-15
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2018-06-15

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