The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
The ground control station also includes a flight simulator, 
which allows the simulation of the real flight to verify the 
predefined flight path (see Figure 2). 
3. RANDA 
3.1 Project Aims 
The focus of the geological project Randa is to characterize the 
large-scale rockslide in Randa (Wallis, Swiss Alps; see Figure 
3). This rockslide will be used as an example of the ultimate 
evolutionary stages corresponding to the complete development 
of the basal shear surface(s) and internal rock mass deformation. 
In order to understand this failure stage in a better way, the 
interrelationships between pre-existing tectonic fractures, 
subsequent tensile fracturing and shearing of intact rock bridges 
will be investigated. Furthermore, for the understanding of the 
rock mass structure and kinematics during this evolutionary 
stage, the basal shear planes must be identified, the internal 
rock mass deformation has to be further studied, and the 3D 
time-dependent displacement field has to be measured more in 
detail using the UAV-image data and the generated DSM 
(Randa, 2008). 
Figure 2: Screenshot of the ground control station software 
showing the flight lines of the Randa data acquisition. In off 
line mode the software can be used for the simulation of the 
flight. The orange shading shows the lower part of the Randa 
rock cliff. 
Figure 3: The Randa rockslide failure (Wallis, Switzerland). 
The lower part is situated 1400 a.s.l. The height difference from 
the bottom to the top is more than 800m. 
Therefore, a high-resolution digital surface model (DSM) with a 
spatial resolution of 10-20cm had to be generated and oriented 
images with a footprint of 2-5cm in object space had to be 
acquired. Because of the non-nadir case and a difficult terrain, the 
standard aerial flight planning procedures could not be applied. 
Furthermore, the sight was acquired by a manned helicopter in 
November 2007, using the Helimap system, combining laser 
scanning and oblique images (Vallet, 2007). The system is based 
on a Riegl LMS-Q240i-60 laser scanner for point cloud 
generation and a Hasselblad HI camera with a Dos Imacon 
Xpress 22Mpix back, which is normally used for texture mapping. 
Using the two comparable systems, the autonomous flying model 
helicopter and the manned helicopter, at one site, allowed the 
analysis of the performance of the systems. Moreover, it is 
possible to compare and integrate the two data sets. 
3.2 Flight planning 
Before doing the flight, the main parameters of the autonomous 
flight were defined. For the Randa rockslide we decided to use the 
Nikon D2Xs, which has a CMOS-sensor with 4288x2848 pixels 
using a 50mm lens (Nikon, AF NIKKOR 50mm 1:1.8D) and a 
pixel size of 5.5pm. For the recognition of features with a length 
of 10-20cm, an image scale of 1:4500 was selected which results 
in a pixel footprint of approximately 3cm. The distance to the cliff 
was defined to 230m, which is equal to the normally used flying 
height above ground. Finally, the side and end lap were set to 
75%. Using this high overlapping along and across strip it was 
possible to avoid occlusions and gaps in the image data (see 
Figure 6). The flight velocity was defined to 3m/s, while the 
shutter speed was 1/1000s. Therefore, the influence of the image 
motion was negligible. 
After defining these parameters, the most recent elevation model 
with the highest available point density was used. Therefore, the 
LiDAR data provided by swisstopo was selected. Using this data 
set and the available orthophoto (swissimage, swisstopo®) 
allowed the definition of the area of interest. Hence, the area was 
separated in three sections. The sections were selected using the 
inclination and aspect values of the slope. 
Figure 4: Our model helicopter during a test flight with the 
inclined camera looking perpendicular to the flight direction. 
For each particular section a plane was defined in a way that the 
average 3D distance of the surface to the plane was reduced to a 
minimum. While looking perpendicular to the surface, we 
assumed to reduce the occlusion in the images. After the 
definition of the plane equation, the normal of the plane was 
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