Abstract

Carbon neutrality, achieved by increasing carbon sinks, is an effective strategy for solving the increasingly serious global climate change problem. The continuous exploitation of resources has damaged, the original ecosystem of mining cities leading to poor vegetation growth environment and decreased regional carbon sink capacity. Therefore, it is crucial to restore and enhance the ecological environment of the region and strengthen the carbon sink capacity of vegetation. However, studies on ecological spatial network optimization for mining cities are few. Here, we constructed the ecological spatial network of Xuzhou City, a mining city in China, using a modified minimal cumulative resistance model (MCR). Subsequently, we calculated the topological properties of ecological nodes and ecological spatial network in Xuzhou City by combining complex network theory with ecological network theory and proposed a scheme to optimize the landscape space based on ecological conditions. The functionality of ecological sources was determined by coupling the results of the Functional description of ecological sources by Remote Sensing Index (RSEI) and integral index of connectivity (dIIC). Carbon sinks were estimated by land use and the topological indicators were correlated with carbon sinks. Carbon sinks showed a significant positive correlation with betweenness centricity. We proposed an optimization strategy in accordance with the functionality and carbon sink capacity of ecological sources. Finally, we determined the effect of optimization by the change in robustness and carbon sink. The stability of the optimized ecological spatial network and ecological restoration capacity of Xuzhou City significantly improved, while the carbon sink was simultaneously enhanced. Through national ecological construction projects, restoration and renewal of ecological space can effectively enhance the carbon sink of mining cities, and thus achieve the goal of carbon neutrality. This study provides a theoretical and measure reference for future ecological engineering of mining cities. Additionally, it can also be applied in remote sensing to promote urban development and sustainability.

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