Research on the spatiotemporal characteristics of the socioeconomic development level of mountainous earthquake-stricken areas under a long-time series after the earthquake

Strong earthquake geological hazards cause significant social and economic losses. The assessment of post-earthquake socioeconomic development levels is one of the important bases from which to measure the recovery capacity of hazard areas. However, the long-term impact of geological hazards is rarely considered in the assessment of the socioeconomic development level of a mountainous earthquake-stricken area. The purpose of this paper is to study the complex relationship between earthquake geological hazard effects and socioeconomic development in the long-term post-earthquake development and reconstruction of mountainous extremely earthquake-stricken areas, to provide a reference for the study area to achieve regional sustainable development goals and high-quality development. On this basis, using the economic, social, ecological environment and other relevant data from 2008 to 2016, and using unsupervised machine learning algorithms, a socioeconomic development level evaluation model based on spectral clustering was established, and the effects of different kernel function scale parameters on the model were analyzed. The optimal parameters were determined, and the spatiotemporal analysis of the socioeconomic development level of the study area was carried out. The research results show that the performance of the evaluation model is optimal when the output category is 4 and the scale parameter is 0.26, and the scale parameter of the kernel function is an important indicator that affects the accuracy of the model. From 2008 to 2016, the socioeconomic development level of Qingchuan has always been at a very low level, Wenchuan and Beichuan have always been at a low level, Shifang and Mianzhu have always been at a high level, and Pengzhou and Dujiangyan have always been at a very high level. The socioeconomic development level of Anxian, Maoxian and Pingwu fluctuates greatly over time. Another interesting finding is that the socioeconomic development level of the mountainous earthquake-stricken area has a strong correlation with its own industrial structure and landslide hazard effects. The work done in this paper is of great significance for understanding the temporal and spatial effects of hazards and understanding the complexities of regional disaster systems.