A study on the spatial and temporal evolution and dynamic simulation of urban resilience in Yunnan Province

To explore urban resilience in Yunnan Province, this paper uses entropy weight-TOPSIS, geographic detector and BP neural network model to demonstrate urban resilience, influencing factors and future level. The results are as follows: 1) the overall resilience level of cities in Yunnan Province is low, while the areas with higher resilience are mainly distributed in the urban agglomerations of central Yunnan; meanwhile, the resilience levels among regions are quite different, but the gap tends to decrease; 2) the importance of factors affecting the urban resilience are as follows: the society > the economy > the engineering > the ecology; 3) in 2025, 2030 and 2035, the city's resilience developed slowly, with both the increase and decrease in the urban resilience. The urban resilience level was mainly divided into the low and relatively low grades, while high-level resilience cities accounted for a small part.