Abstract
Reforestation is an important component to mitigate climate change because trees absorb carbon from the air and store it in their biomass. But even though people know that reforestation is good for the environment, there isn’t enough local data on how much carbon is stored in these areas, which makes it hard to tell how well they work to fight climate change. This study helped to fix the deficiency of local carbon stock data in reforested areas within the City of Koronadal by employing forest inventory data and remote sensing techniques. The study employed a quantitative research design that integrated field-based forest measurements with remote sensing analysis. NDVI results showed a positive relationship with field data, indicating that remote sensing is a useful tool in measuring NDVI. Measurements were done on tree species, diameter at breast height (DBH), height, and wood density in 200 m perimeter Barangay San Isidro, Barangay Assumption and Barangay San Jose. Allometric equations were used to determine aboveground biomass, which was further transformed into carbon stock according to IPCC. The Landsat 9 satellite images were provided in QGIS and used to compute the Normalized Difference Vegetation Index (NDVI) and to evaluate vegetation cover. The findings indicate a difference between the sites with Barangay San Jose (0.16 t C/ha) and Barangay Assumption (NDVI 0.50) having higher biomass and carbon stock which are dominated mainly by Swietenia macrophylla (Mahogany) for monitoring forest biomass. The findings provide baseline information that can help local government units improve forest management such as the National Greening Program and support climate change mitigation efforts.