Addressing the need to harmonize environment conservation and sustainable economic development within the Yellow River Basin (YRB) requires a profound comprehension of the spatiotemporal dynamics of urban ecosystem resilience. This study developed an index system utilizing the resistance-adaptability-recovery framework to measure these dynamics. By applying the advanced multi-attribute boundary area comparison method and a spatial autocorrelation model, we investigated the spatiotemporal variations and spatial correlation patterns of urban ecological resilience across the YRB. The results of this study indicated that: (1) from 2011 to 2020, the value of urban ecological resilience index (UERI) in the YRB consistently ranged between 0.43 and 0.83, and the resilience degree of the urban ecosystem in the YRB progressively improved, with notably higher resilience in the southeast compared to the northwest; (2) the resilience degree of the urban ecosystem in the YRB was non-equilibrium in space. Spatial analysis indicates significant disparities in resilience levels across different areas within the YRB, marked by considerable fluctuations in the global Moran's I index and significant changes in local autocorrelation clustering patterns; and (3) key factors such as wastewater discharge volume, sewage treatment rate, and the rate of non-hazardous treatment of domestic waste were identified as critical determinants of the overall ecological resilience. This research not only deepens our understanding of the factors driving urban ecological resilience but also aids in the formulation of strategic regional policy for sustainable development across the YRB.
Keywords: Machine learning; Moran index; Spatial autocorrelation analysis; Urban ecological resilience; Yellow River Basin.
© 2024. The Author(s).