Integrating Building Footprints and Bioenergy Potential to Support Effective Decentralised Energy Planning: A Scalable Framework Based on Open Data

This study develops a high-resolution workflow to assess rural bioenergy gaps by integrating building-based energy demand and locally collectable biomass supply across Jianghan Plain, China. Building footprint, height and density were extracted from the 10 m 3D-GloBFP dataset and aggregated to 1 km grids to approximate demand intensity. County-level crop straw and livestock manure data were downscaled to generate 1 km supply layers. Subtracting demand from supply yielded a DIFF surface, revealing that 91.8% of rural cells face shortfalls, while only 2.3% are surplus zones, mainly in Songzi, Qianjiang, Tianmen and Xiantao. These counties combine high biomass (> 1200 GJ km−2) with moderate density. Severe deficits (DIFF < −0.25) dominate Honghu and Jianli. Strong negative correlations were found between bioenergy supply and building height (r = −0.74) and footprint area (r = −0.48). The resulting supply–demand atlas enables structural classification and identifies decentralised intervention zones, providing a scalable tool for rural energy planning in mixed-farming regions.