Metropolitan areas, as pivotal hubs for global tourism and economic growth, necessitate sustainable spatial planning to balance development with ecological preservation. As critical geospatial datasets, nighttime light (NTL) and point of interest (POI) data enable the robust analysis of urban structural patterns. Building upon coupling coordination theory and polycentric spatial frameworks, this study investigates the spatial interdependencies between tourism POI and NTL data in China’s Changsha–Zhuzhou–Xiangtan Metropolitan Area (CZTMA). Key findings reveal high spatial coupling homogeneity, with three urban cores exhibiting radial value attenuation from city centers toward the tri-city intersection; concentric zonation patterns where NTL-dominant rings encircle high-coupling nuclei, contrasting with sporadic POI-intensive clusters in peri-urban towns; and sector-specific luminosity responses, where sightseeing infrastructure demonstrates the strongest localized NTL impacts through multiscale geographically weighted regression (MGWR). These findings establish a novel “data fusion-spatial coupling-governance” analytical framework and provide actionable insights for policymakers to harmonize tourism-driven urbanization with ecological resilience, contributing to United Nations Sustainable Development Goal (SDG) 11 (Sustainable Cities).
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