This study describes an emerging business model of carbon trade under REDD+ scheme arrangements by employing Artificial Intelligence (AI), satellite, and blockchain technology in the Bromo Tengger Semeru (BTS) forest protected area. An integrated methodology of GIS-based spatial analysis, stakeholder interview (qualitative), and pilot testing on blockchain was utilized for testing the viability of the model. Results indicate that AI and satellite integration improve the accuracy of carbon stock estimates and deforestation monitoring, while blockchain facilitates transparency and trust in carbon credit transactions. The study identifies the primary barriers, such as cost and capacity-building requirements, and also identifies the potential for scalability and consistency with global climate goals. The findings provide actionable suggestions for policymakers, investors, and environmental managers to enhance forest conservation and carbon market efficiency.
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