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Advancing Malaysia^s Forest Monitoring Through Remote Sensing: Integrating Landsat and Google Earth Engine for Carbon Stock Assessment
Hamdan O.1, Muhamad Afizzul M.1, Simon D.2 & Karen C.2

1. Forest Research Institute Malaysia (FRIM), 52109 Kepong, Selangor
2. Ministry of Natural Resources & Environmental Sustainability (NRES), 62000 Federal Territory Putrajaya


Abstract

Malaysia remains firmly committed to maintaining at least 50% forest cover, underscoring its role in global climate mitigation through advanced spatial data integration. To enhance the accuracy and transparency of forest monitoring, Malaysia adopts a stepwise reporting approach aligned with Biennial Update Reports (BUR-3 in 2018 and BUR-4 in 2022) and the Biennial Transparency Report (BTR-1 in 2024). This study leverages Google Earth Engine (GEE)-derived activity data and Landsat imagery collected at approximately five-year intervals from 2005 to 2024, facilitating a transition from gazetted area-based statistics to satellite-driven verification. This methodological refinement significantly improves the precision of Forest Reference Level (FRL) and Forest Reference Emission Level (FREL) assessments, strengthening national reporting frameworks. The analysis reveals that Malaysia^s forested areas span 18,497,327 hectares, covering approximately 54% of the nation^s landmass. A comprehensive forest carbon inventory estimates the annual carbon sink at 238,262 MgCO2e for 2024, while total forest carbon stock has exhibited a slight decline from 3.19 billion MgC in 2005 to 3.08 billion MgC in 2024. These findings highlight Malaysia^s substantial contribution to climate change mitigation, as its forests continue to sequester approximately 65% of the nation^s total emissions. By harnessing cutting-edge remote sensing technologies, Malaysia reinforces the integrity of its forest monitoring system, enabling data-driven policy decisions and reaffirming its commitment to sustainable forest management and long-term climate resilience.

Keywords: forest monitoring, remote sensing, carbon stock assessment, GEE

Topic: Topic E: Sustainable Development Goals

Plain Format | Corresponding Author (HAMDAN OMAR)

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