Assessment of Low-Carbon Utilization in Territorial Space and Identification of Its Driving Factors: A Case Study of the Yangtze River Economic Belt in China

The low-carbon utilization (LCU) of territorial space represents a critical strategy for addressing climate change and promoting sustainable development, yet current assessments in this domain remain insufficient. This study develops an integrated assessment framework utilizing kernel density estimation, an optimal parameter-based geographical detector, and the Tobit regression model to analyze the spatiotemporal evolution, typology, and driving factors of the LCU of territorial space in the Yangtze River Economic Belt. The findings reveal that the LCU index in this region increased from 0.548 in 2005 to 0.569 in 2020, despite significant regional disparities. Cities are classified into eight distinct types of LCU, with over 80% demonstrating poor performance in at least one functional space, particularly in urban space where the number of cities below the average is highest. The analysis demonstrates that the LCU of territorial spaces is influenced by an integration of natural conditions, socio-economic factors, and landscape patterns. In light of these findings, this study systematically proposes policy recommendations to enhance the LCU of territorial space. This research contributes to the establishment of a scientific evaluation framework for the LCU of territorial space, providing empirical evidence to improve spatial governance policies and support sustainable development.