Objective Against the background of rapid urbanization and global warming, Wuhan is frequently hit by extreme heat events, which not only poses a serious threat to the health status of local residents, but also brings great losses to socio-economic development. Mapping the high temperature disaster risk in the urban development area of Wuhan and analyzing the high temperature disaster risk and influencing factors thereof at the local scale can provide an important basis for the prevention of high temperature disasters in the city.

Methods Based on the “hazard – exposure – vulnerability” high temperature disaster risk assessment framework proposed by the Intergovernmental Panel on Climate Change, this research constructed an assessment system by utilizing multi-source data, and then pre-processes all relevant indicators to make them dimensionless. Then, a combination of the analytic hierarchy process and principal component analysis is adopted to assign weights to the indicators, with such weights being finally superimposed to obtain the hazard map, exposure map and vulnerability map, respectively. On this basis, a high temperature disaster risk map of the urban development area of Wuhan is synthesized to identify the distribution characteristics of high temperature disaster risk in the research area. Then Landsat 8 remote sensing images are processed with SAGA GIS software, Google Earth Pro software, and Random Forest algorithm to classify the urban development area of Wuhan into 17 local climate zone (LCZ) types based on the remote sensing image classification method of World Urban Database and Access Portal Tools (WUDAPT). With 70% random samples used for drawing and 30% random samples used for checking, LCZ maps that meet the requirements of classification accuracy are obtained and analyzed for site identification at the local scale. The LCZ maps are then superimposed on the high temperature disaster risk map to identify the local-scale characteristics of high temperature disaster risk, analyze the degree of high temperature disaster risk for each LCZ type and the differences in high temperature disaster risk between different LCZ types, and explore the reasons for such differences. Finally, eight types of LCZ landscape pattern indices are preliminarily selected at the type and landscape scale levels, and the optimal research size is obtained using the moving window method in Fragstats 4.2 software. Furthermore, highly correlated LCZ types are screened out under the optimal size, the multicollinearity of all LCZ landscape pattern indices is examined and those with multicollinearity are excluded. Finally, geographically weighted regression (GWR) models are used to explore the effect of LCZ landscape patterns on spatial heterogeneity of high temperature disaster risk.

Results The characteristics of high temperature disaster risk in each district do not differ much, and the overall spatial presentation of the development center of each district gradually decreases from high to low, with high-risk areas mainly located in the south-central part of Caidian District, the west and north of Jiangxia District, the dense industrial parks in the south of Dongxihu District, the Wuhan Iron and Steel Factory in Qingshan District, and the Tianhe Airport in Huangpi District, and the low-risk areas are mainly in the watershed part. Jianghan, Qiaokou, and Qingshan districts have relatively high average value of high temperature disaster risk due to high population density or dense buildings, while Wuchang and Hongshan districts have relatively low average value of high temperature disaster risk due to the presence of large areas of water and green areas therein. Overlaying the LCZ maps with the normalized high temperature disaster risk maps, it can be seen that, among the building types, sparse built-up area (LCZ 9) has the lowest average value of high temperature disaster risk, and the average value of high temperature disaster risk is significantly higher than that of the other building types in large low-rise buildings (LCZ 8) and heavy industrial buildings (LCZ 10), which are mainly industrial plants and heavy industrial zones with large building area. Among the natural environment types, water area (LCZ G) has the lowest average value of high temperature disaster risk, which indicates that water can effectively mitigate the risk of high temperature disaster; while for bare rock (LCZ E), exposed sand (LCZ F), and construction building (LCZ H) exposed outdoor, they typically have higher values of high temperature disaster risk due to solar radiation for a long time. As to landscape pattern indices, the area percentage of landscape (PLAND) has a higher influence on high temperature disaster risk than aggregation index (AI).

Conclusion Based on the research results above, strategies to cope with high temperature disasters are proposed. First, the area of vegetation and water should be increased. Secondly, the building layout should be rationally planned. Meanwhile, anthropogenic heat source emissions should also be controlled. Finally, high temperature service facilities should be improved to enhance the city's coping ability.