Non-destructive Laser-based Individual Tree Aboveground Biomass Estimation in Tropical Rainforest
Introduction
Research community mainly in forestry related applications have been exposed with numerous biophysical datasets from satellite imagery. However, these kind of datasets are not supported by accurate field measurements data that causes uncertainty in derived datasets. Terrestrial laser scanning (TLS) is a ground-based LiDAR technology that can be used to retrieve highly detailed 3-dimensional vegetation structure. For plot level forest measurement, TLS could assist the estimation of several useful tree parameters for example tree number and position, tree height, diameter at breast height (DBH), tree volume, above ground biomass and so on. Furthermore, Terrestrial TLS has huge potential to provide accurate tree structure including how the foliage and stems are arranged above the ground of a specific tree. This study aims at estimating individual tree aboveground biomass from high density point cloud obtained by terrestrial laser scanner (TLS). The point clouds were obtained together with field measurements data in 30 forest plots covering 604 trees over tropical rainforest landscape in Royal Belum State Park, Perak, Malaysia. Tree parameters such as Diameter at breast height (DBH), tree height and height to crown base were estimated from TLS for assessment of individual tree measurements. Tree parameters such as stem, branches and leaves volume were estimated from TLS to derive aboveground biomass through volume to biomass conversion factors. Cylinder fitting was applied on the point cloud of the tree stem for DBH and stem volume measurements. Tree height and height to crown base are computed using histogram analysis of the point clouds elevation. Tree branches and leaves volume is estimated by fitting a concave-hull. The results were assessed using other allometric-derived aboveground biomass.
Research objective
The main objectives of this research is to estimate the above-ground biomass using non-destructive laser scanning approach for selective tree species in Malaysia’s tropical rainforest.
Study Area
This study is carried out at the northern part of Peninsular Malaysia in Royal Belum State Park, Gerik in the state of Perak. The coordinate of the area is around 5º 33’ 25.68” N and 101º38’29.41” E, located at 230km away from Ipoh and 430.5km from Kuala Lumpur. This area receiving 1998 to 2300mm of mean annual rainfall, varies throughout the year. According to (WWF-Malaysia 2013), Royal Belum State Park (RBSP) was gazetted as a protected area on 3 May 2007 under the Perak State Parks Corporation Enactment 2001. The park covers a total area of 117,500ha in the most northerly region of the State of Perak in northern Peninsular Malaysia. RBSP lies between border of Thailand on the north, the state of Kelantan to the east and Sungai Gadong in the west. The East-West highway is on its southern border separating the RBSP with Temenggor Forest Reserve to the south. Royal Belum State Park consists of forest, grassland, abandoned agricultural plots, and a large man-made lake, Tasik Temenggor. Forest types found here are mainly lowland dipterocarp, hill dipterocarp and upper dipterocarp. The majority of species are characteristic of tropical rainforest in Peninsular Malaysia, Sumatra and Bornea such as Meranti and Keruing.
Data collection
The primary data for this study is high density point clouds data generated from Riegl VZ-400 and the secondary data is the field measured data. These two datasets were taken by UTM@RoyalBelum Scientific expedition on 19th of September 2014 till 30th of September 2014.
Raw TLS point cloud data
Images captured from digital camera mounted on TLS during scanning were used to apply color on the registered point clouds. Scan positions and signage for tree identification can be seen clearly from the colorized point clouds to assist in individual tree extraction.
Individual Tree Extraction
Individual trees were extracted from the registered point clouds. Point clouds from neighbouring trees, understorey and vicinity branches were removed. This process was done manually to get detailed structure of an individual trees.
Separation of tree parts
Extracted trees were partitioned into stem, branches and leaves for biomass estimation of every compartment.
Reconstructed Trees
Individual trees were reconstructed from cylinders of tree stem and wrapped crown structure as shown below:
