<p>The United Nations’ Sustainable Development Goals (SDGs) offer a comprehensive framework for measuring global sustainability progress. However, localized assessments often face challenges in integrating spatial data and capturing interactions among economic, social, and environmental dimensions, and studies conducting systematic coupling analyses at finer spatial scales based on multi-source data remain relatively scarce. This study addresses these gaps by constructing a multidimensional evaluation system for Zhejiang Province, China, that combines statistical and geospatial data to assess sustainable development at the municipal scale. Drawing on the global indicator framework for the SDGs (SGIF), we developed an index system covering 44 indicators across 13 SDGs, employing the entropy weight method and linear weighted summation to calculate composite indices. The Coupling Coordination Degree (CCD) model was applied to assess the synergy among subsystems, while regional disparities and dynamic trends were evaluated using the Dagum Gini Coefficient (DGC) and Kernel Density Estimation (KDE). Results show that from 2011 to 2020, overall sustainable development levels in Zhejiang Province improved steadily, accompanied by enhanced coordination among economic, social, and environmental subsystems. Nevertheless, notable spatial disparities persist, with economic and environmental differences widening over time, while social disparities narrowed. Inter-regional differences were the dominant source of inequality. These findings highlight the spatially differentiated nature of sustainability transitions and underscore the need for targeted, region-specific policy interventions. The study contributes a replicable approach for subnational SDG monitoring and provides empirical evidence to inform sustainable development strategies in Zhejiang and similar contexts.</p>