AI4Biochar: applying AI-driven field boundary recognition to the biochar sector
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Agricultural residues in Viet Nam, a major agricultural producer, are abundant yet underutilized. Converting these residues into biochar offers a sustainable alternative to the widespread burning practices, which release greenhouse gases and air pollutants. The use of biochar as soil amendment could enhance soil structure while being a powerful carbon sequestrator. However, the sector’s development is hindered by a lack of detailed data, including geospatial, for cost–benefit analyses and for optimal placement of biochar production unit networks. To address these gaps, this paper introduces AI4Biochar, an AI-driven tool that automatically delineates crop field boundaries, integrates production data and sustainability indicators, and streamlines biochar production, resource management, environmental impact assessment, and market development within a geospatial framework. This paper presents the methodological approach used in the development of AI4Biochar and the results from a use-case application of the tool in a rice-producing district of Viet Nam.