ArticleScientific data2026
A high-resolution gridded dataset of biomass resource potentials in China with policy-aware land-use constraints for renewable energy planning.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
3 authors.
Funding
Abstract
The pursuit of carbon neutrality in China demands a rapid, spatially informed scale-up of renewable energy, including biomass, yet high-resolution, policy-aware data for site-specific planning remain scarce. To bridge this gap, we develop China's high-resolution spatially explicit biomass resource potential dataset, which integrates five biomass categories (agricultural residues, forestry residues, energy crops, animal manure, and municipal waste) at 1 km resolution for 2020, with projections to 2050. This dataset incorporates key constraints such as food security, ecological conservation, and land use suitability. It provides heat value potential distribution maps in GeoTIFF and PDF formats, and heat value potential data in Excel format. By combining multi-source geospatial data, statistical downscaling, and machine learning, this dataset enables precise assessment of resource conditions and provides forward-looking planning for biomass power deployment, rural revitalization, and carbon reduction strategies, thereby meeting China's critical need for integrated, location-aware open data in energy and land-use decision-making.
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Registered trials
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