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.