Papers by Muhammad Zulkarnain Abd Rahman
IEEE Geoscience and Remote Sensing Letters, 2014
High-density airborne light detection and ranging (LiDAR) data with point densities over 50 point... more High-density airborne light detection and ranging (LiDAR) data with point densities over 50 points/m 2 provide new opportunities, because previously inaccessible quantities of an individual tree can be derived directly from the data. We introduce a skeleton measurement methodology to extract the diameter at breast height (DBH) from airborne point clouds of trees. The estimates for the DBH are derived by analyzing the point distances to a suitable tree skeleton. The method is validated in three scenarios: 1) on a synthetic point cloud, simulating the point cloud acquisition over a forest; 2) on examples of free-standing and partly occluded trees; and 3) on automatically extracted trees from a sampled forest. The proposed diameter estimation performed well in all three scenarios, although influences of the tree extraction method and the field validation could not be fully excluded.
Forests, 2017
Recent methods for detailed and accurate biomass and carbon stock estimation of forests have been... more Recent methods for detailed and accurate biomass and carbon stock estimation of forests have been driven by advances in remote sensing technology. The conventional approach to biomass estimation heavily relies on the tree species and site-specific allometric equations, which are based on destructive methods. This paper introduces a non-destructive, laser-based approach (terrestrial laser scanner) for individual tree aboveground biomass estimation in the Royal Belum forest reserve, Perak, Malaysia. The study area is in the state park, and it is believed to be one of the oldest rainforests in the world. The point clouds generated for 35 forest plots, using the terrestrial laser scanner, were geo-rectified and cleaned to produce separate point clouds for individual trees. The volumes of tree trunks were estimated based on a cylinder model fitted to the point clouds. The biomasses of tree trunks were calculated by multiplying the volume and the species wood density. The biomasses of branches and leaves were also estimated based on the estimated volume and density values. Branch and leaf volumes were estimated based on the fitted point clouds using an alpha-shape approach. The estimated individual biomass and the total above ground biomass were compared with the aboveground biomass (AGB) value estimated using existing allometric equations and individual tree census data collected in the field. The results show that the combination of a simple single-tree stem reconstruction and wood density can be used to estimate stem biomass comparable to the results usually obtained through existing allometric equations. However, there are several issues associated with the data and method used for branch and leaf biomass estimations, which need further improvement.
Silvilaser 2009 Proceedings, Oct 1, 2009
This paper presents a new method for individual tree measurement from Airborne LiDAR data. This m... more This paper presents a new method for individual tree measurement from Airborne LiDAR data. This method involves 3 steps; 1) individual tree crown delineation based on density of high points (DHP), 2) tree filtering, and 3) measurement of tree trunk diameter at breast height (DBH). In the second step, a special tree filtering algorithm is introduced which combines a histogram analysis and region growing (RG) segmentation method. In forest area, undergrowth vegetation is considered as noise and it should be removed to ease ...
High-density airborne light detection and ranging (LiDAR) data with point densities over 50 point... more High-density airborne light detection and ranging (LiDAR) data with point densities over 50 points/m 2 provide new opportunities, because previously inaccessible quantities of an individual tree can be derived directly from the data. We introduce a skeleton measurement methodology to extract the diameter at breast height (DBH) from airborne point clouds of trees. The estimates for the DBH are derived by analyzing the point distances to a suitable tree skeleton. The method is validated in three scenarios: 1) on a synthetic point cloud, simulating the point cloud acquisition over a forest; 2) on examples of free-standing and partly occluded trees; and 3) on automatically extracted trees from a sampled forest. The proposed diameter estimation performed well in all three scenarios, although influences of the tree extraction method and the field validation could not be fully excluded.
High-density airborne light detection and ranging
(LiDAR) data with point densities over 50 point... more High-density airborne light detection and ranging
(LiDAR) data with point densities over 50 points/m2 provide
new opportunities, because previously inaccessible quantities of an
individual tree can be derived directly from the data.We introduce
a skeleton measurement methodology to extract the diameter at
breast height (DBH) from airborne point clouds of trees. The estimates
for the DBH are derived by analyzing the point distances to
a suitable tree skeleton. Themethod is validated in three scenarios:
1) on a synthetic point cloud, simulating the point cloud acquisition
over a forest; 2) on examples of free-standing and partly occluded
trees; and 3) on automatically extracted trees from a sampled
forest. The proposed diameter estimation performed well in all
three scenarios, although influences of the tree extraction method
and the field validation could not be fully excluded.
ABSTRACT: High density airborne LiDAR, for example FLI-MAP 400 data, has opened an opportunity fo... more ABSTRACT: High density airborne LiDAR, for example FLI-MAP 400 data, has opened an opportunity for individual tree measurement. This paper presents a method for individual tree delineation and undergrowth vegetation removal in forest area. The delineation of individual trees involves two steps namely 1) tree crown delineation based on density of high points (DHP) and 2) separation of dominant trees and undergrowth vegetation.
High-density airborne light detection and ranging (LiDAR) data with point densities over 50 point... more High-density airborne light detection and ranging (LiDAR) data with point densities over 50 points/m 2 provide new opportunities, because previously inaccessible quantities of an individual tree can be derived directly from the data. We introduce a skeleton measurement methodology to extract the diameter at breast height (DBH) from airborne point clouds of trees. The estimates for the DBH are derived by analyzing the point distances to a suitable tree skeleton. The method is validated in three scenarios: 1) on a synthetic point cloud, simulating the point cloud acquisition over a forest; 2) on examples of free-standing and partly occluded trees; and 3) on automatically extracted trees from a sampled forest. The proposed diameter estimation performed well in all three scenarios, although influences of the tree extraction method and the field validation could not be fully excluded.
IEEE Geoscience and Remote Sensing Letters, 2014
High-density airborne light detection and ranging (LiDAR) data with point densities over 50 point... more High-density airborne light detection and ranging (LiDAR) data with point densities over 50 points/m 2 provide new opportunities, because previously inaccessible quantities of an individual tree can be derived directly from the data. We introduce a skeleton measurement methodology to extract the diameter at breast height (DBH) from airborne point clouds of trees. The estimates for the DBH are derived by analyzing the point distances to a suitable tree skeleton. The method is validated in three scenarios: 1) on a synthetic point cloud, simulating the point cloud acquisition over a forest; 2) on examples of free-standing and partly occluded trees; and 3) on automatically extracted trees from a sampled forest. The proposed diameter estimation performed well in all three scenarios, although influences of the tree extraction method and the field validation could not be fully excluded.
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Papers by Muhammad Zulkarnain Abd Rahman
(LiDAR) data with point densities over 50 points/m2 provide
new opportunities, because previously inaccessible quantities of an
individual tree can be derived directly from the data.We introduce
a skeleton measurement methodology to extract the diameter at
breast height (DBH) from airborne point clouds of trees. The estimates
for the DBH are derived by analyzing the point distances to
a suitable tree skeleton. Themethod is validated in three scenarios:
1) on a synthetic point cloud, simulating the point cloud acquisition
over a forest; 2) on examples of free-standing and partly occluded
trees; and 3) on automatically extracted trees from a sampled
forest. The proposed diameter estimation performed well in all
three scenarios, although influences of the tree extraction method
and the field validation could not be fully excluded.