基于遥感的宁夏地区高温热浪风险评估

doi:10.12118/j.issn.1000-6060.2021.280

摘要/Abstract

摘要：

高温热浪灾害风险信息对全球气候变暖及快速城市化条件下的防控极端灾害事件具有重要的参考价值。为了解决高温热浪危险性因子评估不全面的问题,基于多源卫星遥感数据和社会经济统计数据,在结合地表温度和气象数据作为高温危险性因子的基础上,通过层次分析法和图层叠置法评估模型计算得到2014—2019年7—8月宁夏高温热浪风险等级空间分布图。结果表明：宁夏高温热浪风险总体上处于中等偏上水平,较高和高风险地区面积占比从2014年39.52%增长至2019年62.65%;受地理纬度、地形和气候的影响,高温风险分布出现明显的空间差异,北部风险总体高于南部风险（高出约13.27%）,西部风险高于东部（高出约12.30%）;高风险地区集中在中卫市和石嘴山市,这主要是城市高温和相对较低的医疗水平共同作用的结果。研究结果有助于服务城市高温灾害的预防以及制定应对高温热浪应急方案。

关键词: 高温热浪, 人居指数, 风险评估, 遥感, 宁夏

Abstract:

The disaster risk information of the heat wave is of great reference value for preventing and controlling extreme disaster events under global warming and rapid urbanization. Since the spatial distribution of population and social and economic factors are closely related to regional high temperature risk, this paper combines these two factors to the evaluation index of heat waves risk to improve the evaluation result and make the evaluation result more consistent with reality. Additionally, meteorological data were added based on the multi-source satellite remote sensing and socio-economic statistics data to solve the problem of incomplete risk assessment of heat wave. Hazard factors were obtained by combining surface temperature and meteorological data. In Matlab software, the corresponding target, criterion, and index layers are divided according to the components of heat wave risk. Pairwise comparison is conducted on the indexes. Then, a judgment matrix is constructed according to their relative importance, and a consistency test is performed. Consequently, the weight of each index is obtained. Then, the spatial overlay tool in ArcGIS 10.3 software was used to superimpose normalized indicators according to their respective weights to obtain the spatial distribution map of heat wave risk in Ningxia Province, northwest China from July to August between 2014 and 2019. The results are as follows. The overall risk of heat wave in Ningxia is at an upper-medium level, with the proportion of high and higher risk areas increasing from 39.52% in 2014 to 62.65% in 2019. There is a significant spatial difference in heat wave risk affected by geographical latitude, topography, and climate. The northern area showed higher heat risk than the southern area (about 13.27% higher), and the western area showed a slightly higher risk than the eastern area (about 12.30% higher). High-risk areas are concentrated in Zhongwei City and Shizuishan City because of the city’s high temperature and relatively low medical level. This study is essential for preventing urban disasters and formulating an emergency plan to deal with heat wave.

Key words: heat wave, human settlement index, risk assessment, remote sensing, Ningxia

赵志欣,霍艾迪,张丹,易秀,陈思名,陈四宾,陈建. 基于遥感的宁夏地区高温热浪风险评估[J]. 干旱区地理, 2022, 45(2): 512-521.

ZHAO Zhixin,HUO Aidi,ZHANG Dan,YI Xiu,CHEN Siming,CHEN Sibin,CHEN Jian. Assessing heat wave risk in Ningxia segment based on remote sensing[J]. Arid Land Geography, 2022, 45(2): 512-521.

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数据名称	观测平台	时间分辨率/次·d^-1	空间分辨率/km	数据来源
LST	Aqua	2	1.00	https://modis.gsfc.nasa.gov/
NDVI	Aqua	2	0.25	https://modis.gsfc.nasa.gov/
DMSP/OLS夜间灯光	DMSP	1	1.00	http://ngdc.noaa.gov/eog/
DEM	Terra	2	0.08	http://www.gscloud.cn/search
气象数据	-	-	-	http://data.cma.cn
社会统计数据	-	-	-	2014、2017年和2019年宁夏统计年鉴

目标层（A）	准则层（B）	指标层（C）
高温热浪风险A	高温热浪危险性B₁（+0.46）	地表温度C₁（+0.4）
		气温C₂（+0.4）
		降水量C₃（-0.1）
		风速C₄（-0.05）
		气压C₅（-0.05）
	社会经济脆弱性B₂（+0.31）	人居指数C₆（+0.6）
		常住人口C₇（+0.24）
		14岁以下65岁以上人口占比C₈（+0.1）
		建筑施工人员C₉ （+0.06）
	高温热浪风险适应性B₃ （-0.23）	人均GDP C₁₀（-0.6）
		城镇每百户空调拥有率C₁₁（-0.18）
		城镇卫生机构床位数C₁₂（-0.11）
		城镇医疗卫生技术人员C₁₃（-0.11）