Gutierrez, J.

The voluntary blue carbon market is severely bottlenecked by outdated methodologies that apply broad, coast-level carbon averages across low-resolution spatial units, systematically failing to account for micro-site ecological realities and critical socio-political constraints. To resolve this structural deficit, this paper introduces the High-Resolution Geographically-Explicit Blue Carbon Assessment (HiGEBCA) pipeline, an innovative geospatial architecture that shifts site intelligence from monolithic raster grids to a topologically verified, hyper-dimensional polygon infrastructure. Operating on 1,601 distinct mangrove features across Colombia, the pipeline mathematically binds 47 ecological attributes to each polygon, integrating Monte Carlo uncertainty propagation, climate-stratified soil organic carbon, and rigorous biodiversity quantification spanning 293 taxon-code pairs. A diagnostic CatBoost machine learning emulator (R2 = 0.926) deployed within the pipeline empirically demonstrates that local climate classes and biodiversity metrics drive over 96% of the variance in carbon density, proving that traditional broad biome classifications are inadequate for accurate micro-site valuation. Crucially, the HiGEBCA framework pioneers the integration of operational reality into natural capital assessment. When applied to Colombia's theoretical national estate of 276,430 hectares (containing an estimated 478 million tCOe), the pipeline executes a rigorous REDD+ white space assessment alongside hard mathematical filters for legal land tenure, armed conflict, and regulatory overlap. This strict governance filtration shatters the illusion of massive, easily accessible natural capital, systematically reducing the viable, investment-grade portfolio to a highly de-risked 4,000 to 12,000 hectares. Designed for cross-jurisdictional replication, the HiGEBCA pipeline establishes a new, transparent standard for prioritizing high-integrity blue carbon assets, providing a quantitative mandate for investors seeking to maximize climate impact, capture biodiversity premiums, and definitively mitigate operational risk.