Estimation of Forest Biomass and Absorbed CO2 by Remote Sensing in Can Gio, Vietnam

Abstract

In recent years, the Can Gio district in Vietnam has faced escalating challenges linked to climate change, including deforestation, urbanization, and rising carbon emissions. This study employs remote sensing techniques to estimate critical forest metrics, particularly aboveground biomass (AGB) and carbon sequestration potential in the region. Through meticulous data collection and analysis, this research establishes strong correlations between vegetation indices derived from remote sensing data and AGB, as well as CO2 absorption. Our results reveal that the Can Gio mangrove forest boasts an impressive AGB ranging from 200 to 500 tons/ha and demonstrates significant variations in carbon sequestration potential across different sub-zones. These findings not only contribute to efficient AGB estimation methods but also facilitate sustainable forest management and climate change mitigation strategies, vital for the Can Gio district and regions globally grappling with similar challenges.