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<p>High-integrity carbon offset systems require scientifically robust and spatially explicit frameworks to quantify carbon pools and fluxes across ecosystems. We present an integrative methodology that combines eddy covariance measurements, airborne and satellite remote sensing, and modeling to extrapolate near real-time carbon flux monitoring to larger areas, using the old-growth temperate forests of Chilean Patagonia as a case study. Our approach delivers high-resolution aboveground biomass carbon density (30&#xa0;m) and net ecosystem exchange (NEE, 30&#xa0;m—30&#xa0;min) estimates using flux tower data. By integrating ground-based flux measurements with high-resolution remote sensing, the proposed methodology constrains model parameters and spatial extrapolation, thereby reducing uncertainty relative to conventional inventory-based approaches. Our approach offers a replicable framework for informing climate policy, conservation planning, and emerging nature-based finance instruments while meeting operational needs in terms of scalability, technological integration, reproducibility, and traceability. </p>

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An integrative methodology to estimate high-resolution carbon stock and fluxes: a case study in the old-growth forests of the Chilean Patagonia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月24日

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  • Taryn Fuentes-Castillo,
  • Aarón Grau-Neira,
  • Eduardo Morales-Santana,
  • Deelan Rus-Valledor,
  • David Trejo-Cancino,
  • Adrián Pascual,
  • Jorge F. Perez-Quezada

摘要

High-integrity carbon offset systems require scientifically robust and spatially explicit frameworks to quantify carbon pools and fluxes across ecosystems. We present an integrative methodology that combines eddy covariance measurements, airborne and satellite remote sensing, and modeling to extrapolate near real-time carbon flux monitoring to larger areas, using the old-growth temperate forests of Chilean Patagonia as a case study. Our approach delivers high-resolution aboveground biomass carbon density (30 m) and net ecosystem exchange (NEE, 30 m—30 min) estimates using flux tower data. By integrating ground-based flux measurements with high-resolution remote sensing, the proposed methodology constrains model parameters and spatial extrapolation, thereby reducing uncertainty relative to conventional inventory-based approaches. Our approach offers a replicable framework for informing climate policy, conservation planning, and emerging nature-based finance instruments while meeting operational needs in terms of scalability, technological integration, reproducibility, and traceability.