additional sensory input, for example imagery. Com-
plementary surface information becomes available from
stereopsis. As indicated in the diagram, such informa-
tion can be merged with laser data in the segmenta-
tion process, extending the process to a fusion problem.
Csathó et al. (1999) present a conceptual framework
for including panchromatic, multispectral/hyperspectral
imagery, and laser ranging data for the purpose of object
recognition and analyzing urban scenes.
5 Concluding Remarks
Photogrammetry and airborne laser ranging are the two
most widely used methods for generating DSMs. In some
applications, the two methods compete. In this case, the
market decides; for example cost, expertise of service
providers, availability, project duration. Other applica-
tions are clear-cut cases either for laser ranging, such
as measuring ice sheets, snow fields, and beaches; or
for photogrammetry, for example projects that require
imagery for object recognition.
Since the two methods have different performance char-
acteristics, it stands to reason to combine the two meth-
ods to solve more challenging problems. Such a combi-
nation is facilitated by the possibility of mounting both
systems on the same platform. Hence, the data acqui-
sition time does not increase. Perhaps more important,
the same GPS/IMU can be used to orient both systems.
The ultimate solution in this respect would be an imager
that also measures the range, at least of some of the
pixels.
The full potential of airborne laser ranging, particularly
in combination with photogrammetry, has not nearly
been reached. Enthusiasm about the new method is
not enough, however. Considerable effort must be de-
voted to processing the raw laser data. The fair assess-
ment of quality and performance requires transparent
processing methods that should be as application in-
dependent as possible. Ad-hoc methods should give
way for algorithms with a more theoretical underpinning.
Some problems look simple at first sight but prove much
harder when attempting general and robust solutions.
Thinning laser data sets may serve as an example. Most
everyone involved with processing laser data developed
some sort of thinning algorithm. Do we have a solution
that is universally accepted and capable of dealing with
profilers and scanners alike? We can compile an impres-
sive list of problems whose efficient solutions require
the expertise of different specialists.
A distinct improvement on the system level of laser rang-
ing systems would be the complete recording of the re-
turning signal for the time interval the laser beam in-
teracts with the surface(s). Preliminary studies indicate
that additional information about the footprint can be
expected—information that is most desirable for solving
the difficult object recognition problem.
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Baltsavias, E. (1999). A comparison between photogram-
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Csathó, B., T. Schenk, D.C. Lee and S. Filin (1999). In-
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KEYWORDS:
ABSTRACT
Preliminary resul
global remote sen
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adoption rate anc
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commercial remc
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community com
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designs are base
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al. 1991; Kral
Photogrammetry
1999). Comme
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and built proprie
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