Qi Zhong / China University of Mining and Technology
Guie Li / China University of Mining and Technology
Yangyang Jiao / China University of Mining and Technology
Jie Li / China University of Mining and Technology
Chunying Li / China University of Mining and Technology
Resource-based cities are important strategic energy security bases in China, and the sustainable development of resource-based cities is not only an intrinsic requirement for local development, but also an important part of China's overall sustainable development strategy. However, due to the current unbalanced, uncoordinated and unsustainable problems in domestic economic development, the sustainable development of resource-based cities is facing serious challenges, so it is of great significance to quantitatively study its sustainable development. The Sustainable Development Goals (SDGs) provides a new guideline for global sustainable development. Based on the SDGs, this paper takes 114 prefecture-level resource-based cities in China in 2006, 2010, 2015 and 2020 as the research objects, and centers on the development characteristics of resource-based cities to construct the sustainable development index system of resource-based cities in terms of resources, environment, economy and society, and then use principal component analysis to construct a comprehensive index of sustainable development. On this basis, spatial autocorrelation analysis and self-organizing neural network were used to analyze the spatio-temporal patterns of sustainable development capability of resource-based cities. The purpose of this paper is to reveal the spatio-temporal evolution law of sustainable development capability of resource-based cities, and to provide theoretical and practical support for the formulation of sustainable development strategies in the future.