Urban low-carbon development involves multiple socioeconomic and ecological dimensions that may not improve synchronously. This study evaluates the multidimensional low-carbon development of Wuhan, China, from 2014 to 2023 by integrating ecosystem carbon storage with carbon, economic, transportation, living, and environmental indicators. Entropy weight-TOPSIS, InVEST, coupling coordination, obstacle degree, and spatial autocorrelation analyses were combined to assess temporal performance, subsystem coordination and relative constraints, and the spatial distribution of carbon storage. Within the study-period evaluation framework, the comprehensive low-carbon development index increased from 0.398 to 0.598, while ecosystem carbon storage decreased by approximately 0.74 million t C, indicating divergent trajectories between aggregate performance and ecological carbon stocks. The coupling coordination degree increased from 0.544 to 0.782, corresponding to a shift from reluctant to intermediate coordination. The dominant relative constraint shifted from Living during 2014–2018 to Transportation during 2019–2023, with civilian vehicle ownership becoming the largest transportation-related shortfall by 2023. Carbon storage exhibited strong positive spatial autocorrelation and a broadly stable clustering pattern, characterized by peripheral high–high and central low–low clusters. These findings demonstrate the value of jointly considering overall performance, subsystem constraints, and spatial ecological conditions when evaluating urban low-carbon development.

City networks refer to the connections of physical or virtual flows among cities at different spatial scales, including population migration networks, economic networks, information networks and innovation networks. This concept has gradually evolved into an important paradigm for understanding the regional spatial structures. Based on Baidu Index data within the Yangtze River Economic Belt (YREB) in China, this paper constructs an information network and investigates its connection patterns. Using social network analysis, the structural differentiation of the information network is further investigated at both the overall and subregional scales. The results show that the connection patterns of the information network exhibit an obvious hierarchical structure, with the complexity of the spatial pattern gradually increasing from the upstream to the downstream regions. Furthermore, the structural assessment results suggest that the information network is characterized by high agglomeration, high mobility, high hierarchy and low disassortativity. These findings indicate that the information network in the YREB is dominated by several highly developed core city clusters. However, the inherently closed structure resulting from these characteristics may not be sufficiently counterbalanced by low disassortativity. Under sudden disturbances, such a structural configuration may exhibit limited adaptability, delayed response capacity, and slow reorganization and learning processes, thereby weakening structural resilience. This study provides a deeper understanding of intercity relationships within the YREB and offers policy implications for enhancing structural resilience across the Yangtze River Basin.