The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
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The objective of this paper is to present a comparative analysis 
of indirect georeferencing using real data to evaluate the use of 
three sources of control data, namely, ground control points, 
LiDAR patches, and LiDAR lines. Section 2 of this paper 
describes indirect georeferencing using LiDAR patches and 
LiDAR lines. A semi-automated approach for the extraction of 
patches and lines from LiDAR data is presented and used to 
obtain the image EOP from LiDAR control features. In Section 
3, quantitative analysis, using RMSE analysis, and qualitative 
analysis, using orthoimage generation, are presented to 
demonstrate the comparison between the object reconstruction 
results using the three sources of control data. Finally, the 
conclusions are summarized in Section 4. 
2. GEOREFERENCING METHODS 
Photogrammetric georeferencing is the process of relating the 
image and ground coordinate systems by defining the position 
and orientation information (EOP) of the camera at the moment 
of exposure relative to the object space coordinate system. 
Computing the EOP is performed either directly (direct 
georeferencing) when GPS/INS is available onboard the 
imaging platform, or indirectly (indirect georeferencing) using 
ground control information. Ground control points (GCPs) are 
traditionally the most commonly used source of control for 
photogrammetric indirect georeferencing. Despite its proven 
accuracy in photogrammetric reconstruction, using GCPs as a 
source of control is costly and labour intensive as it requires 
field surveying. For this reason, other sources of control data 
require investigation. The availability of LiDAR data, however, 
allows for alternative methods for image georeferencing. In 
particular, LiDAR-derived control features can be utilized for 
the georeferencing of the photogrammetric data relative to the 
LiDAR reference frame. Since the LiDAR footprints are 
irregularly distributed, however, no point-to-point 
correspondence can be assumed between the photogrammetric 
and LiDAR data. As such, it is almost impossible to identify 
distinct conjugate points in overlapping photogrammetric and 
LiDAR data. Consequently, LiDAR patches (Section 2.1) and 
LiDAR lines (Section 2.2) will be used as control information 
for the georeferencing of the photogrammetric data. 
2.1 Indirect Georeferencing using LiDAR patches 
This section outlines the procedure in which LiDAR patches are 
used to obtain the image georeferencing parameters. The steps 
for this procedure include the extraction of the LiDAR patches 
from the LiDAR point cloud, followed by the incorporation of 
LiDAR-derived areal features in the photogrammetric 
triangulation procedure. 
2.1.1 Extraction of LiDAR Patches: In order to utilize 
LiDAR control features, the features must be extracted from the 
LiDAR point cloud. This section outlines the process for the 
extraction of areal features from irregular LiDAR footprints 
(Al-Durgham, 2007). The extraction of features from LiDAR is 
performed using a developed program. The process begins by 
displaying the LiDAR intensity images in the program window, 
in which the user selects an area where it appears that areal 
features might be present. The user clicks on the centre of the 
area after defining the radius of a circle within which the 
original LiDAR footprints will be extracted. It should be noted 
that the LiDAR intensity images are only used for visualization 
purposes. Figure la shows a sample area as well as the original 
LiDAR footprints located in a selected area. Then, a 
segmentation technique (Kim et al., 2007) is used to identify 
planar patches in the point cloud within the selected area. The 
outcome from the segmentation is an aggregated set of points 
representing planar patches in the selected area (Figure lb). 
(a) (b) 
Figure 1: a) Area of interest selection and LiDAR point cloud 
extraction, b) Segmented planar patches. 
2.1.2 Incorporation of Areal Features for Image 
Georeferencing: The approaches used to incorporate areal 
features extracted from LiDAR data in a photogrammetric 
triangulation procedure are now presented. The first outlined 
approach is the coplanarity-based incorporation of areal 
features. The second approach involves the use of a point-based 
incorporation of areal features, where the weight matrix of the 
utilized points is modified. 
Coplanarity-based Incorporation of Planar Patches 
In this approach, the planar patch in the imagery is defined by a 
minimum of three points, for example points a, b, and c, which 
are located in the image space, while the LiDAR patch is 
defined as a set of LiDAR points in object space (Habib et al., 
2007). The points, a, b, and c should be visible in at least two 
overlapping images. The collinearity equations are used to 
relate the image space coordinates of the points a,b,c to their 
object space coordinates, A,B,C. The LiDAR points belonging 
to a certain planar-surface patch should coincide with the 
photogrammetric patch representing the same object space 
surface. The coplanarity of the LiDAR and photogrammetric 
points is explained mathematically in Habib et al. (2007). In 
physical terms, this constraint means that the normal distance 
between any LiDAR point P and the corresponding 
photogrammetric surface consisting of the three points should 
be zero. In other words, the volume of the tetrahedron 
comprised of the four points (A, B, C and P) should be equal to 
zero, as these points belong to the same plane. This constraint is 
applied for all LiDAR points located within this surface patch. 
Point-based Incorporation of Planar Patches 
A second approach for the incorporation of planar patches uses 
a point-based technique, in which existing bundle adjustment 
procedures which are based on the collinearity equations, can 
be used for the incorporation of control areal features 
(Aldelgawy et al., 2008). For this approach, conjugate patch 
vertices are defined in at least two overlapping images. Then, 
the corresponding control patch is extracted from the LiDAR 
point cloud using the procedure described in section 2.1.1. 
From the extracted LiDAR control patch, which consists of 
hundred of points, some points are selected as patch vertices. 
The number of points selected in the LiDAR patch should be 
equivalent to the number of vertices defined in the imagery.