International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004
laser data segments of unchanged buildings have been
identified:
e Generalisation. At the medium scale of 1:10.000
generalisation is applied to the objects in the topographic
database. Small intrusions and protrusions in the contour
of the building objects have been omitted, already in the
original mapping process. To allow for removed
intrusions in the database objects, it was checked whether
the database object would fit inside the dilated laser data
segment (Figure 3 top). To allow for removed
protrusions, it was checked whether the eroded laser data
segment would fit inside the database object (Figure 3
bottom). The kernel size of this dilation and erosion
depended on the specifications of the generalisation
process. This approach allows for larger differences than
those that could have been caused by generalisation. Still,
it proved to be effective for the change detection.
Figure 3: Dilated laser data segment of a building with an
intrusion (top left). Generalised database object
fits inside dilated laser data segment (top right).
Eroded laser data segment of a building with a
protrusion (bottom left). Eroded laser data
segment fits inside generalised database object
(bottom right).
e Random data noise. Noise, of course, is present in both
the map objects and the laser data. The amount of noise,
however, is much lower than the size of the
generalisation effects. The differences caused by noise
can be accounted for by slightly enlarging the
morphological kernel introduced above. This will
increase the tolerance in the change detection.
e Systematic errors. Systematic offsets were observed
between the location of groups of buildings in the
topographical database and the same buildings in the
segmented laser data. Based on the shape and size of
these buildings one would, however, conclude that many
of these buildings were not changed. To avoid a detection
of a change for these events, for each database object the
optimal alignment with the laser data segment was
determined. This shift was applied to the database object
prior to the change detection.
e Object selection. The mapping catalogue of the map
producer specifies which objects are to be mapped. In the
case of used medium scale map, the catalogue specified
that not all buildings are to be mapped. E.g. only
buildings larger than 3x3 m should be included in the
topographical database. It also specified that only those
buildings should be mapped that are visible from a street.
Le., sheds behind buildings were not to be mapped even
if their sizes exceeded the minimum size requirement.
These kind of mapping rules first need to be applied to
the building segments extracted from the laser data.
Otherwise, many “new” buildings would be found that
should not be inserted into the topographic database.
6. CHANGE DETECTION RESULTS
The above procedure has been implemented and tested. This
section describes the data used in the experiment, the result
of the building extraction step and the analysis of the
detected changes.
6.1 Data description
The study was aimed at determining the potential of airborne
laser scanning for the purpose of change detection for the
revision of the Dutch TOP10vector. database. This database
was created for usage at a scale of about 1:10.000. The
building objects have a location accuracy of 1-2 m.
The laser data was acquired by Terralmaging with an Optech
ALTMI225 scanner. The data was recorded with an average
point spacing of 1.4 m. An area was chosen in which many
buildings were constructed recently. The area contained only
little vegetation.
6.2 Extraction of building segments
All buildings were detected and extracted from the laser data.
The building segments are shown in Figure 4 together with
the road centre lines taken from the topographical database.
A large number of small sheds in gardens behind buildings
has been detected. The segments shown in red (dark) were
automatically labelled as buildings "in the second row". For
those buildings it was assumed that they should not be taken
into the topographical database as defined by the mapping
catalogue.
Figure 4: Segments in a part of the DSM that were
classified as buildings. In red the building objects
that were labelled as shed.
6.3 Offsets between the data sources
In the final step before the actual change detection, the laser
data segments were optimally aligned with the building
contours of the topographical database. Figure 5 shows the
extracted building segments together with both the original
position of the database objects (red) and the positions after
the alignment procedure (black). À clearly systematic pattern
of shifts between the database objects and the laser data
segments can be observed. However, the shifts are not
constant. The directions vary and the sizes range from 2 to 4
m. In the overlay of the laser data with a more accurate map
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