International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B2. Istanbul 2004
Figure 7. Detail plot from LiDAR and digital photo.
13.5 Combining data for feature extraction
LiDAR is very important for feature extraction and has been
widely used with other data sources for this purpose. Haala &
Brenner (19993) have demonstrated the combination of LIDAR
data with multispectral aerial images for the automatic
classification of buildings and trees. Haala and Brenner (1999b)
have also shown automatic 3D building reconstruction in a
system which combines 2D GIS data and LiDAR. Based on
given outlines of the respective buildings which were integrated
with dense surface data from airborne LIDAR measurements,
virtual city models were created for an extensive number of test
sites using this software. Sohn and Dowman (2004) have
combined low density LiDAR with high resolution satellite
sensors to extract buildings. Dell'Acqua et al, (2003) have
combined LiDAR with IfSAR in urban areas. The paper shows
that it is possible to exploit LIDAR DEM to improve to some
extent the two- and three-dimensional representation of
buildings extracted from IfSAR data. The method helps in
recovering building displacement and distortion due to the side-
looking nature of radar. This is shown in figure 8.
Figure 8. 3D characteristic of buildings from IfDSAR and
LiDAR. After Dell'Acqua et al, (2003).
98
14. DISCUSSION
It can be seen that LIDAR and IfSAR are important new sources
of data for generating geospatial products. They have opened
up new markets by filling gapes which could not be filled by
aerial photography or optical satellite imagery. It can also be
seen that LIDAR and IfSAR are themselves complementary,
and also complementary to other sources of data. It has been
shown that IfSAR is more economical for wide area coverage,
provides an intensity image, which can be orthorectified, a
coherence image and multifrequency and multipolarised data
which can give more information about the land cover than
hitherto possible. LiDAR on the other hand gives a high
density cloud of 3D points which can accurately define both
elevation and plan position. There are however a number of
restriction on wider use of LiDAR and IfSAR and open
questions on their future development.
Although LiDAR has the potential for application in building
extraction and 3D city modelling, automatic feature extraction
is still not mature and therefore the output is unreliable, and
manual editing is very expensive. | LiDAR is also very
expensive for small areas. Wider use of LiDAR may therefore
have to wait until better feature extraction algorithms are
available. New airborne technologies such as 3 line optical
sensors could also compete with LiDAR when they become
more mature and can acquire data with higher resolution than at
present. Three line data avoids occlusions and adds redundancy
to the data set. Multi sensor data could also do this. The use of
a digital camera with LIDAR is already commonplace, but a
good model for reconstruction and error analysis is needed. In
order to inspire confidence in the data better theoretical models
are required, both for single sensors, and for data fusion, in
order that the errors can be better understood. Potential errors
such as multipath and transparency effects also need to be
studied much more. More comparative tests, especially with
different algorithms, need to be carried out, although this is now
happening through ISPRS (Vosselman and Sithole, 2003) and
EuroSDR (http://www.oeepe.org/2002/index.htm), for example.
IfSAR could also benefit from comparative testing and the
establishment of international test sites would be beneficial.
CEOS and EuroSDR could contribute to this.
A better understanding of the quality measures and error
statistics, and development of understandable uncertainty
measures would also be beneficial. Organisation such as USGS
and Ordnance Survey are establishing good practice in this area
by showing heritage and uncertainty in their data; this should be
encouraged, and their methods publicised.
15. NEW DEVELOPMENTS
A number of clear trends have been identified. These include
more accurate, higher density data, new applications and the
development of new algorithms. High density LIDAR point
clouds mean that buildings can be better extracted, and details
of highway surfaces and infrastructures can be surveyed more
easily.
The main developments in progress are in the area of [{SAR,
particularly the development of multi frequency, multi polarised
SAR. The ESA spaceborne ENVISAT mission is already
operating the ASAR sensor and other mission such as the
Japanese ALOS PALSAR will be launched shortly. Satellite
SAR resolution is being improved, as is the positional and
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