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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. P art B5. Beijing 2008 
• Perform a first TLS acquisition that covers both the moving 
and stable areas. In this stage it is important to consider that 
the key parameters of the acquisition, like the sensor-to- 
object distance and the sampling density, have a direct 
impact on the deformation analysis results. Another key 
factor is given by the distribution of the stable areas in the 
observed scene. The best scenarios are given by the 
deformation area completely surrounded by stable areas. 
This aspect can strongly impact the quality of the global 
matching, which in turn can generate systematic errors in 
the derived deformation results. This can be relaxed by 
using co-registration procedures based on a set of ground 
control points (GCPs) or tie points distributed in the scene, 
e.g. see Giussani and Scaioni (2004). 
• After a given time period, which depends on the 
characteristics of the deformation at hand, perform a second 
TLS acquisition over the same area. Note that this operation 
can be repeated several times, getting a complete temporal 
deformation monitoring. We restrict the discussion to the 
simplest case, based on two acquisitions. It is worth noting 
that the geometry of the second acquisition can be slightly 
different from the previous one. In fact, the procedure does 
not assume to perform the data acquisition from the same 
viewpoint. 
2. Global Matching: We name hereafter master the first point 
cloud, and slave the second one. Since each point cloud has its 
own reference system, we need to co-register them. This is 
achieved by applying a global LS3D matching over the areas of 
the scene that remain stable between the two acquisitions. For 
this purpose the parts of the scene that are subjected to 
deformation have to be properly removed before performing the 
co-registration. The deformation areas are often known from 
external information on the observed scene. Otherwise some 
extra processing is required to identify stable and deformation 
areas. As already mentioned above, the global matching 
represents a critical step of the procedure, which can directly 
affect the estimation of the deformation parameters. For this 
reason, the key characteristics of the studied area have to be a 
priori properly considered, and the feasibility of the global 
matching have to be assessed. In case of weak configurations 
one should consider the option of performing a co-registration 
based on GCPs or tie points. If the configuration is feasible and 
the global matching is performed, its quality has to be checked 
by taking advantages of the standard LS based tools, e.g. 
analysis of the residuals, outlier rejection, etc. 
3. Local matching: Once the two point clouds are co-registered, 
the deformation analysis involves two key steps: 
• Identification of the specific areas to be analysed. This can 
be done by selecting on the master point cloud specific 
objects or areas of interest, and can be properly performed 
working on the TLS intensity data. Alternatively, if no 
specific areas of interest have to be studied, the study area 
can be divided in subsets that contain a specified number of 
TLS samples. Note that this operation can be performed 
through an automatic procedure. 
• For each subset, using the LS3D matching, the 
corresponding subset on the slave is automatically searched, 
obtaining the transformation parameters (local matching). 
These parameters, which in the experiments described in 
this work are six, three translations and three rotations, 
describe the deformation that each subset has undergone 
between the two acquisitions. 
The presented procedure has been validated using both a 
simulated deformation scenario, which is described in the 
following section, and a real landslide monitoring scenario; see 
for in depth description Monserrat and Crosetto (2008). 
3. DESCRIPTION OF THE VALIDATION 
EXPERIMENT 
In order to verify the effectiveness and evaluate the precision of 
the proposed deformation measurement approach an experiment 
was realized. In the experiment a deformation measurement 
scenario was simulated. On this basis a comparison was done 
between results estimated with use of two independent 
techniques: the proposed TLS approach and a topographic 
survey with total station. The experiment took place in the 
Mediterranean Technology Park of Castelldefels (Barcelona), 
where the Institute of Geomatics is placed. 
Figure 2 shows the scene where the measurements took place 
and the artificial targets in its bottom part. It is an intensity 
image of the entire measured area. The scene includes some 
buildings and structures in the back that were used as stable 
areas. The numbered objects located on the bottom part of the 
image are the 10 artificial targets that were displaced during the 
experiment in order to simulate a deformation phenomenon. 
The targets have an approximate dimension of 60 by 120 cm 
and they differ one from the other for their geometry and the 
type of material (wood, concrete, aluminium, foam, cartoon, 
etc.). Figure 3 show the area selected as stable area for the 
Global Matching. 
Figure 2: TLS intensity image acquired during the experiment, 
at an average distance of 134 m. Over the same image are 
indicated the approximate directions of two of the three axes of 
the reference system used for the data analysis. The Y direction 
is approximately parallel to the TLS range direction 
The measurements have been performed with use of the laser 
scanner ILRIS 3D of Optech and Trimble 3601 DR total station. 
The experiment was realized in the following main steps: 
• Measurement of the scene with the TLS, acquiring the data 
from two different positions: 
o the first one, with an average distance sensor-object of 
134 m, is called hereafter the 100 m dataset, 
o the second one, with an average distance sensor-object 
of 225 m, is called hereafter the 200 m dataset.