With the rapid advancement of the global climate crisis, the pursuit of carbon neutrality has become an increasingly urgent issue in South Korea and worldwide. Forest ecosystems play a pivotal role in carbon sequestration and are critical in mitigating this crisis. A comprehensive understanding of the distribution and structural dynamics of forest ecosystems is essential for effective forest carbon management. Given the vast expanse of domestic forests, the integration of remote sensing technologies is indispensable for monitoring and assessing these ecosystems. Specifically, the use of three-dimensional LiDAR remote sensing data allows for the quantitative representation of vertical structural characteristics, such as forest height, that are crucial for evaluating the vertical distribution of forests. The Global Ecosystem Dynamics Investigation (GEDI) satellite mission provides valuable forest biomass information across different levels; however, certain regions, including parts of Asia, require model improvements due to a relative paucity of data. Therefore, this study developed a forest ground biomass estimation methodology based on GEDI spaceborne LiDAR and national forest inventory data, and applied it to a case study in South Korea. To calculate above-ground biomass, canopy height profile indicators were derived from GEDI Level 2 data, and biomass estimates were generated using species-specific biomass coefficients and diameter at breast height and tree density information from the national forest inventory. The estimated aboveground biomass densities for Icheon, Gwangju, and Yeoju were 29.1742, 75.8275, and 46.8442 Mg/ha, respectively. These findings underscore the importance of incorporating regional forest characteristics using domestic forest spatial data and highlight the potential for more accurate forest biomass estimation based on precise elevation data obtained from spaceborne LiDAR. This approach represents a significant advancement in our ability to effectively assess and manage forest carbon resources.
