High-resolution mapping of tourism carbon footprint and its driving factors
该研究利用多源数据框架对北京旅游碳足迹进行高分辨率制图，发现核心-外围结构，住宿是最大碳源，并揭示人口密度、GDP等驱动因素的空间异质性，为可持续旅游政策提供依据。
Tourism is a major contributor to global carbon emissions, and its urban footprint shows strong spatial variation shaped by functional zoning and tourism resources. This study develops a multi-source data framework to map and analyze the tourism carbon footprint in Beijing. Results reveal a distinct core–periphery structure, concentrated in Dongcheng and Xicheng with secondary clusters along transport corridors, forming a core–multiple nodes network. Sectoral differences are evident: catering emissions disperse around attractions and hotels, accommodation and attractions cluster in hotspots, and transport follows a ring-shaped network. At the grid scale, accommodation dominates 41.5% of grids and attractions 23.2%, making accommodation the most widespread carbon source. Spatial autocorrelation confirms significant clustering, with high values in central and secondary cores, low values elsewhere, and low-value outliers along major routes. Multi-scale geographically weighted regression (MGWR) analysis shows that overall emissions (OCE) and population density (POP) exert broad spatial influence, while elevation (DEM) and gross domestic product (GDP) act locally. OCE and DEM are negatively associated with emissions, whereas GDP and POP are positive, all displaying strong spatial heterogeneity. The proposed framework enables high-resolution mapping of urban tourism carbon footprints, advancing intra-urban estimation and providing new insights into emission patterns for sustainable tourism policymaking.