Raw point clouds obtained using Terrestrial Laser Scanner. The point clouds were collected using Leica Scanstation C10 laser scanner that operates with the green wavelength at 532nm. This scanner is capable to scan at most 300m distance object with the nominal accuracy of 4.5mm

After registration process, the unnecessary or noise point clouds of those originate from neighbouring trees, understory trees and ground surface are removed to avoid confusion and complexity in data processing. The point clouds are then separated into individual trees for further processing to estimate tree attributes. Further cleaning process of leaf and small branches are required to separate the trunk and branches prior to diameter estimation at different height intervals. The noise removal procedure has been done manually by a careful inspection of every single trees marked in the field as well as in the point clouds.

The geometric reconstruction of individual tree trunk was done by fitting the point clouds with cylinder model at different tree height.

The point clouds of tree crown is wrapped with convex-hull surface. The complete individual tree reconstruction is shown below:

Active Remote Sensing for total above ground biomass estimation over tropical forest

Abstract

The work present in this research mainly focuses on up-scalling approach for aboveground biomass (AGB) estimation employing multi-source active remote sensing data (i.e. IfSAR, TerraSAR) combined with in-situ data. The information provided by Synthetic Aperture Radar (SAR) image is useful for forest management which is the measurement of forest properties such as AGB and stem volume can be generated by non-destructive approach with more efficiently, cost-effective, and can be applied over large forest areas. This work considers study sites over tropical rainforest landscape in Pasoh Forest Reserve, Negeri Sembilan, Malaysia. As a beginning, this research was start with a brief introduction and the explaining of recent trends on monitoring and modeling of forest resources using remote sensing data and approach. This research works on the validation of forest parameters predictions and modeling, followed by estimation of AGB using up-scalling approach. Finally, this work evaluates the TAGB estimation based on allometric method and backscatter information. The results show that the different accuracy of forest parameters predictions and modeling of IfSAR data based on up-scalling approach. Moreover, the up-scalling approach also gives the different result of TAGB estimation.

Research Objective

The main objective of this research is to estimate total aboveground biomass based on up-scalling method using active remotely sensed data (i.e. Interferometric Synthetic Aperture Radar) in Pasoh Forest Reserved, Negeri Sembilan.

Study Area

The study area of this research is conducted in Pasoh Forest Reserve which located in Negeri Sembilan of Peninsular Malaysia at latitude 2º 59’N and longitude 102º 19’E. The area an approximately of 2,450 ha (Malaysia, 2012) and 145 km southeast of Kuala Lumpur. The core area 50 ha of the Forest Reserve is covered with primary lowland mixed Dipterocarp forest that includes various species of Shorea and Dipterocarpus (Kosugi et al., 2008).

Up-scalling methods

This method are consists of grid systems in order to estimate the TAGB with different type of kernel sizes. The involved of kernel size are 1) 5m × 5m, 2) 10m × 10m, 3) 20m × 20m, and 4) 50m × 50m. Each of grid have different number of trees which is the larger grid size, the more trees include in the grid. Figure 3.3 shows the grid system or kernel analysis that applied into field data and also the IfSAR data. The blue area shows the available of 25 ha field data collection in year 2009.

Tree height and DBH evaluation based on up-scalling method

The evaluation of tree height and DBH are done by comparing the sample points of IfSAR and field data. Both of data are verified by using RMSE equation. The accuracy, regression and correlation value of tree height and DBH are shown below:

Postgraduate meeting at B08

Meeting minutes:

1. Research proposal Msc defense

2. FRGS grants

3. Journal publication:

• Afif – IEEE Geoscience & Jurnal Teknologi
• Radhi – International Journal of Remote Sensing
• Suraya – Jurnal Teknologi

4. Every student has to update their progress via posting related tasks in the website

5. Suraya needs to add ALOS Palsar processing in her thesis

6. Fieldwork – Radhi at FRIM

7. ALOS Palsar data purchasing via FRGS grant – RM 10,000.00

8. Afif will be assisted by PSM final year student

9. Students are advised to join any related conferences

LiDAR is cost effective alternative to conventional mapping technologies. Areas larger than a few hundred acres are mapped more efficiently using LiDAR

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