Modification and loss of forests due to natural and anthropogenic disturbances contribute an estimated 20% of annual greenhouse gas (GHG) emissions worldwide. Accounting GHG emissions associated with forestry, specifically, and land use generally is crucial in recent days because forests play major roles in balancing terrestrial carbon and contribute to the mitigation of global warming and climate change. Consequent to the awareness of climate change, reducing emission from deforestation and forest degradation, and conservation (REDD+) programmed was introduced at the international level to promote forest conservation and enhance forest governances. Intergovernmental Panel on Climate Change (IPCC) came out with protocols on how to account the carbonstored and released from the forests. Principally there are five primary carbon pools in a forest, which are above-ground biomass, below-ground biomass, deadwood, litter, and soils that accumulate and in some conditions release carbon. However, about 98% of carbon stored in a forest comprises trees components (aboveground and belowground living biomass, deadwood and litters) and the remaining is stored in soils. Many factors interact to affect the flux dynamics of these carbon pools, including the type of forest ecosystem, the age of the forest, and if harvested, the length of stand rotation cycles and the forestry practices used. Logging these forests, in a sense, represents an opportunity cost, as the time necessary for a harvested forest to regain its carbon sink capacity can take many decades, and if left undisturbed, would have gone on to expand its carbon pool or at least remain in constant over time. In this study, the lowland dipterocarp forest, where logging often takes place, is profiled in terms of biomass carbon. Pahang, which has the largest forest cover and biggest timber production in Peninsular Malaysia, was selected as the study area. The dipterocarp forests comprise both protection and production functions were categorized into strata based on year elapsed after logging (i.e. logged 1-10, 11-20, 21-30, and > 30 years). Measurements have been conducted on the ground and all the carbon pools in these strata were assessed. The study found significant differences between each stratum in terms of carbon and the results are presented in this paper. The effects of harvesting practices on carbon pools are also discussed.
Rapid growth of Malaysia’s economy recently is often associated with various environmental disturbances, which have been contributing to depletion of forest resources and thus climate change. The need for more spaces for numerous land developments has made the existing forests suffer from deforestation. This chapter presents an overview and demonstrates how remote sensing data is used to map and quantify changes of tropical forests in Malaysia. The analysis dealt with image processing that produce seamless mosaics of optical satellite data over Malaysia, within 15 years period, with 5-year intervals. The challenges were about the production of cloud-free images over a tropical country that always covered by clouds. These datasets were used to identify eligible areas for carbon offset in land use, land use change and forestry (LULUCF) sector in Malaysia. Altogether 580 scenes of Landsat imagery were processed to complete the observation period and came out with a seamless, wall to wall images over Malaysia from year 2005 to 2020. Forests have been identified from the image classification and then classified into three major types, which are dry-inland forest, peat swamp and mangroves. Post-classification change detection technique was used to determine areas that have been undergoing conversions from forests to other land uses. Forest areas were found to have declined from about 19.3 Mil. ha (in 2005) to 18.2 Mil. ha in year 2020. Causes of deforestation have been identified and the amount of carbon dioxide (CO2) that has been emitted due to the deforestation activity has been determined in this study. The total deforested area between years 2005 and 2020 was at 1,087,030 ha with rate of deforestation of about 72,469 ha yr.−1 (or 0.37% yr.−1). This has contributed to the total CO2 emission of 689.26 Mil. Mg CO2, with an annual rate of 45.95 Mil. Mg CO2 yr.−1. The study found that the use of a series satellite images from optical sensors are the most appropriate sensors to be used for monitoring of deforestation over the Malaysia region, although cloud covers are the major issue for optical imagery datasets.
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