Biomass Carbon Map over Forests in Malaysia Produced from Landsat-Based Aboveground carbon Density Indicator (ACDI) and a Collection of 12 Years Inventory Data
Hamdan Omar*, Muhamad Afizzul Misman, Valeria Linggok, Suhaini Haron, Ahmad Ashrin Mohd Bohari, and Mohammad nor Firdaus Sariee
ABSTRACT
The accurate estimation of biomass carbon in forests is of paramount importance for effective forest management and mitigating climate change. This study presents a novel approach to produce a high-resolution map of biomass carbon over forests in Malaysia using the Aboveground Carbon Density Indicator (ACDI) and a comprehensive collection of 12 years of inventory data, i.e., from 2011 to 2023. The ACDI was derived based on several vegetation indices (VIs) that were produced from the original Landsat images to indicate the level of aboveground biomass carbon (AGC) stock in the forested areas. The ACDI was then integrated with ground-based measurements and became a single indicator for estimating AGC. This calculation was conducted on Google Earth Engine (GEE) platform to match the date of field observation with the satellite imagery datasets. Latest dates of Landsat imagery were used to produce a forest cover map throughout the country, which comprised three major forest types, which are dry inland forest, mangrove forest, and peat swamp forest. Results indicated significant spatial variations in AGC across Malaysia’s forests. Based on the estimates, a 30-metre resolution, wall-to-wall map of AGC across the entire forested region of Malaysia has been created. The total AGC in all types of forests in Malaysia was estimated at 3.0 billion Mg C with an attainable accuracy of about 80%. The presented methodology showcases the value of combining advanced remote sensing techniques with long-term inventory data, which contributes to the understanding of carbon dynamics in Malaysian forests and promotes effective strategies for mitigating climate change through better-informed forest conservation and management practices.
