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Arid Land Geography ›› 2022, Vol. 45 ›› Issue (2): 512-521.doi: 10.12118/j.issn.1000-6060.2021.280

• Earth Information Sciences • Previous Articles     Next Articles

Assessing heat wave risk in Ningxia segment based on remote sensing

ZHAO Zhixin1,2(),HUO Aidi1,2(),ZHANG Dan3,YI Xiu1,2,CHEN Siming1,2,CHEN Sibin1,2,CHEN Jian1,2   

  1. 1. School of Water and Environmental, Chang’an University, Xi’an 710054, Shaanxi, China
    2. Key Laboratory of Subsurface Hydrology and Ecological Effects in the Arid Region Ministry of Education, Chang’an University, Xi’an 710054, Shaanxi, China
    3. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2021-06-18 Revised:2021-09-26 Online:2022-03-25 Published:2022-04-02
  • Contact: Aidi HUO E-mail:zhao1201xin@163.com;huoaidi@163.com

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