Comprehensive analysis of energy consumption and spatial heterogeneity in urban fringe towns and subdistricts

Against the background of addressing climate change and promoting low-carbon development, accurately characterizing the spatial distribution of regional energy consumption at the micro-scale holds significant importance. As major hubs for population agglomeration and industrial transition, urban fringe areas urgently require a refined energy consumption accounting method applicable at the subdistrict and town scale. This study integrates remote sensing imagery, POI, road network density, and statistical yearbook data to construct a 300m grid-scale energy consumption estimation model covering four sectors: primary industry, industry, transportation, and residence. We conduct an empirical analysis using Huangyan District in Taizhou City as a case study. The results indicate that energy consumption in Huangyan District exhibits a “one center, multiple clusters” spatial pattern, closely aligning with the regional development plan. Significant differences exist in energy consumption between streets and towns: the eight core subdistricts account for 75 % of total energy use, and their per capita total energy consumption is 1.38 times that of the towns, reflecting clear urbanization characteristics. This study provides a new spatial computation method and foundational dataset for energy analysis at the street and township scales, offering essential support for future investigations into the spatial patterns of energy consumption and spatial governance strategies, while also contributing scientific evidence for urban low-carbon transformation and sustainable development.