Modeling Terrestrial Carbon Sequestration: A Review-Based Mathematical Framework Integrating Remote Sensing and GIS

<title>Abstract</title> <p>Terrestrial ecosystems play a vital role in mitigating climate change by sequestering atmospheric CO₂ in vegetation and soils. Accurate, large-scale, and spatially explicit quantification of carbon stocks is essential for informing climate policy, improving carbon accounting, and supporting credible carbon credit systems. However, traditional field-based methods are labor-intensive, spatially limited, and time-consuming, resulting in substantial uncertainties in national and global carbon budgets. Addressing this challenge requires scalable, efficient, and precise monitoring approaches. This review-based study presents an integrated mathematical framework that harnesses the spatial and spectral capabilities of Remote Sensing (RS) and Geographic Information Systems (GIS) to estimate carbon stocks across diverse terrestrial ecosystems. By combining satellite-derived vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), with established allometric equations and biomass-to-carbon conversion factors, the framework accurately estimates Aboveground Biomass (AGB) and associated carbon storage. It effectively captures spatial heterogeneity across forests, croplands, grasslands, and arid lands at high spatial resolution. This scalable and reproducible approach provides a powerful tool for high-resolution carbon monitoring, thereby enhancing capabilities for climate mitigation, sustainable land management, and transparent, verifiable carbon credit mechanisms, such as the Reducing Emissions from Deforestation and Forest Degradation (REDD+) mechanism.</p>