DISEÑO Y PLANEACIÓN

Figure 2demonstrates the overall workflow of the study. 3.1 Preprocessing of TLS data

Airborne LiDAR is already set up for measurement and analysis. However recorded terrestrial LiDAR data has to be first registered and georeferenced before doing any analysis. Registration of points from the three scan locations is then performed in Leica Cyclone 7.0.2 using algorithm called the ICP (iterative closest point) that matched the point clouds with an accuracy of 2mm (which is within the expected accuracy level of 5mm).Georeferencing of the distributed targets is done based on their GPS coordinates thus bringing the TLS data to the same coordinate reference system as the ALS data i.e. UTM zone 32N, WGS 84. Once the TLS data is now in the same coordinate system as the TLS, the two data were then merged together if desired.

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3.2 Measurement of Tree Parameters:

Height and crown diameter of the trees can be measured directly from airborne LiDAR. Diameter at breast height (dbh) cannot be measured directly because there are no points on the trunk of the tree in ALS. Dbh is the most significant parameter in estimation of above ground biomass. Crown width and height of the tree are precisely measured from ALS particularly. The cross section of the crown is not uniform. To reduce errors in measurement, crown diameter is measured in two transverse directions and the average value isused in each case. In very large forest covers, it is necessary to develop a canopy height model (CHM) and a digital terrain model (DTM) for automatic derivation of tree parameters. For typical urban areas where there exist only pockets of tree stands, individual trees can precisely be extracted without much labor. In this study all the measurements are carried out in LP360 software. In terrestrial LiDAR, dbhcan be directly measured. The terrain of the study area is almost flat, at approximately 301.4m above mean sea level. In Europe dbh is measured at 1.3m above ground. Hence, a filter is run to get rid of points below 301.4m and those above 302.7m. The bare tree stems were thus precisely measured (see Figure 3).

The measured dbh can thus be used as input parameter for for the biomass estimation.

Figure 3: Measurement of dbhbased on TLSpoint clouds (left) Selection Window (right) Extracted Tree (Visualized in LP 360)

3.3 Comparison of ALS and TLS measurements

It is observed that ALS data measurements are lower than the TLS data measurements. It is because the ALS point cloud density is much lower than the TLS data. Suárez (2004) also observed that tree heights determined from ALS data were 7% to 8% less as compared to reference data.It is found that seasonal change does have effect of the measurable parameters i.e., tree height and tree crown diameter. Nevertheless dbh remains the same. An increase in the height and crown diameter is observed in TLS data measurements. This increase is due the fact that in spring there were few leaves on the tree branches as compared to summer. Therefore for determining the biomass of deciduous trees, one has to take care of the seasonal variations.

Table 1: ALS data measurements

Average of Measurement (m) Tree No.

CD H DBH

Tree No. 1 12.05 17.58 N/A

Tree No. 2 11.91 13.58 N/A

Tree No. 3 11.26 15.43 N/A

Table 2: Spring TLS data measurements

Average of Measurement (m) Tree No.

CD H DBH

Muhammad Abdullah Sohl, Emmanuel Bobb Anya Lansana, NazirHussain

Tree No. 2 15.24 15.05 0.81

Tree No. 3 13.18 17.05 0.65

Table 3: Summer TLS data measurements

Average of Measurement (m) Tree No. CD H DBH Tree No. 1 15.98 18.01 0.90 Tree No. 2 15.32 15.22 0.81 Tree No. 3 14.54 17.30 0.65

4

Regression Analyses and Biomass Estimation

Different types of equations have been used in past to calculate the above ground biomass. According to Zianis et al., (2005) majority of the biomass equations in Europe are the modified form of following equation simple linear equation

log (M) = A + B × log (Dbh)

Where log (M) is logarithmic transformation of the biomass, log (Dbh) is the logarithmic transformation of diameter at breast height while A, and B are the estimated parameters (ibid).

The parameters, A and B, differ from tree species.

Biomass estimation equation used in Germany for tree specie Fagus sylvatica (Beech, Rotbuche, Beuk) is as

follows (ibid);

Biomass = a+b·Dbh·H2_+c·Dbh3_{……….(1)}

Where;

a = 15.589·10–3_{, b = 0.01696·10}–3_{, c = 0.01883·10}–3

Dbh is diameter at breast height

In our study area, two out of three trees (Tree 1 and Tree 2) scanned with TLS belong to the specie Rotbuche. Using above equation biomass of only two trees of these species (i.e. Rotebuche) can be determined in stadtgarten. That is because dbh for other trees of said specie is not available in ALS.

Though dbh is a tree dimension that cannot be measured directly from ALS data but it can be measured indirectly as it is strongly correlated to Crown Diameter (CD) and Height (H) of the trees. Regression models can be used to develop equations for determining dbh. Sorin (2007) used the following equation to calculate the dbh of pine trees from lidar data.

dbh = a0+a1CD+a2H……….(2)

Where;

CD is crown diameter H is tree height

a0, a1 and a2 are estimated parameters whose values vary from tree to tree specie

After inserting the values of dbh measured from TLS data, crown diameter and height of the tree, values of unknown parameters (i.e., a0, a1 and a2) is determined by using least square estimation.

A Conceptual Approach to Estimate Biomass using Airborne and Terrestrial LiDAR Data

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and Photogrammetry 65