Key Laboratory of Digital Land and Resources, East China University of Technology, Nanchang, 330013, Jiangxi, PR China; Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran.
Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran.
Environ Pollut. 2021 Jun 15;279:116859. doi: 10.1016/j.envpol.2021.116859. Epub 2021 Mar 10.
In this work, a sand and dust storm vulnerability mapping (SDS-VM) approach is developed to model the vulnerability of urban blocks to SDS using GIS spatial analysis and a range of geographical data. The SDS-VM was carried out in Ahvaz, IRAN, representing one of the most dust-polluted cities in West Asia. Here, vulnerability is defined as a function of three components: exposure, sensitivity, and adaptive capacity of the people in the city blocks to sand and dust storms. These components were formulated into measurable indicators (i.e. GIS layers) including: PM, wind speed, distance from dust emission sources, demographic statistics (age, gender, family size, education level), number of building floors, building age, land surface temperature (LST), land use, percentage of literate population, distance from health services, distance from city facilities (city center, shopping centers), distance from infrastructure (public transportation, main roads and highways), distance from parks and green spaces, and green area per capita. The components and the indicators were weighted using analytical hierarchy process (AHP). Different levels of risks for the components and the indicators were defined using ordered weighted averaging (OWA). Urban SDS vulnerability maps at different risk levels were generated through spatial multi-criteria data analysis procedure. Vulnerability maps, with different risk levels, were validated against field-collected data of 781 patients hospitalized for dust-related diseases (i.e. respiratory, cardiovascular, and skin). Results showed that (i) SDS vulnerability map, obtained from the developed methodology, gives an overall accuracy of 79%; (ii); regions 1 and 5 of Ahvaz are recognized with the highest and lowest vulnerabilities to SDS, respectively; and (iii) ORness equal to 0 (very low risk) is the optimum SDS-VM risk level for decision-making to mitigate the harmful impacts of SDS in the deposition areas of Ahvaz city.
在这项工作中，我们开发了一种沙尘暴脆弱性制图（SDS-VM）方法，该方法使用 GIS 空间分析和一系列地理数据来模拟城市街区对 SDS 的脆弱性。SDS-VM 在伊朗阿瓦士进行，阿瓦士是西亚污染最严重的城市之一。在这里，脆弱性被定义为城市街区中人们对沙尘暴的暴露、敏感性和适应能力的三个组成部分的函数。这些组成部分被制定成可衡量的指标（即 GIS 图层），包括：PM、风速、距尘源的距离、人口统计数据（年龄、性别、家庭规模、教育水平）、建筑楼层数、建筑年龄、地表温度（LST）、土地利用、识字人口比例、距医疗服务的距离、距城市设施（市中心、购物中心）的距离、距基础设施（公共交通、主要道路和高速公路）的距离、距公园和绿地的距离、人均绿地面积。使用层次分析法（AHP）对组成部分和指标进行加权。使用有序加权平均（OWA）定义组成部分和指标的不同风险级别。通过空间多准则数据分析程序生成不同风险级别的城市 SDS 脆弱性图。对不同风险级别的脆弱性图进行验证，使用了从 781 名因尘相关疾病（即呼吸道、心血管和皮肤）住院的患者中收集的现场数据。结果表明：（i）通过所开发的方法获得的 SDS 脆弱性图总体准确率为 79%；（ii）阿瓦士的 1 区和 5 区分别被认为是对 SDS 最脆弱和最不脆弱的区域；（iii）ORness 等于 0（低风险）是 SDS-VM 的最佳风险水平，用于在阿瓦兹市的沉积区做出减轻 SDS 有害影响的决策。
