International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part Bl. Istanbul 2004
LIDAR - SONY DSC-F717
Conjugate lines in photogrammetric and LIDAR datasets were
identified and measured. There were sixty eight in each of Il
and I2 datasets. Table 6 lists the parameters of the 3D
transformation function between the SONY and the LIDAR
datasets.
Il 2
Scale [0.999407 [0.0005] 1.00015 | £0.0006
X, (m) 070 | 0.19 | 0.69 | £0.20
Yı (m) -0.09 | £0.19 | -0.08 | +02
Zr(m) -0.63 | +0.13 | -0.69 | 0.1
Q (°) | -0.083 |+0.037| -0.05 | +0.027
db (°) | 0.0005 | +0.036| 0.012 | +0.026 |
K(°) | 0.131 |+0.039| 0.076 | +0.041 |
Table 6: 3D similarity parameters between LIDAR and SONY
model.
Again, the consistent shift values in Table 6 suggest the
existence of biases between the LIDAR and SONY F717
datasets. Also, the overall normal vector between conjugate
photogrammetric and LIDAR lines before and after absolute
orientation of this set is calculated and shown in Table 7, in
which the standard deviations indicate LIDAR I2 dataset has
the best result.
Before absolute orientation| After absolute orientation
Il 12 I 12
DX (m)| -0.29 |x1.08 | -0.33 |x0.69| 0.08 |x:1.03| 0.03 |+0.60
DY (m) -0.02 +1.08| 0.05 |+0.60| -0.07 |+1.09| 0.02 |+0.59
DZ (m) -0.52 +1.20|-0.57 |+1.17|-0.11 |#1.16|-0.12 |+1.14
Table 7: Overall normal | vector between conjugate
photogrammetric (SONY F717) and LIDAR lines
before and after absolute orientation.
4. CONCLUSIONS AND RECOMMENDATIONS
These experiments have demonstrated the compatibility of
LIDAR and photogrammetric models generated by
metric/analog and amateur/digital cameras. It also proved the
usefulness of using LIDAR straight lines as a source of control
for photogrammetric orientation. Straight-line features
confirmed again its versatility in photogrammetric processes.
An interesting conclusion is the feasibility of using LIDAR
intensity images to collect necessary control for orienting
photogrammetric models, although additional inaccuracies can
be attributed to some difficulties and ambiguities when
identifying linear features on the intensity image. The
experiments also highlighted the role played by the sampling
methodology through the choice of the interpolation method,
grid size, and search space. The enormous extra computational
effort and storage space spent to produce over-sampled grids
inversely affected the reconstruction of the object space.
Further work is being undertaken to clarify a number of
additional aspects arising from these experiments. This work
includes the analysis and description of the discrepancy pattern
between the true surface and generated LIDAR surfaces in the
presence of various systematic errors. The two-step nature of
the second approach can be utilised for this purpose. Also,
experiments are being performed on the automatic extraction of
the control features from the LIDAR data (intensity as well as
range images). Another vital extension of the work is to
investigate automatic correspondence among LIDAR and
photogrammetric features. A logical application would be to
develop methodologies for robust true ortho-photo generation
that could handle relief displacements in large scale imagery
over urban areas.
5. REFERENCES
Baltsavias, E., 1999. A comparison between photogrammetry
and laser scanning, /SPRS Journal of Photogrammetry &
Remote Sensing, 54(1):83—94.
Csathó, B. M., K. Boyer, and S. Filin, 1999, Segmentation of
laser surfaces, /nternational Archives of Photogrammetry and
Remote Sensing, 32(3W14):73-80.
Ebner, H., and T. Ohlhof, 1994. Utilization of ground control
points for image orientation without point identification in
image space, /nternational Archives of Photogrammetry and
Remote Sensing, 30(3/1):206—211.
Filin, S., 2002. Surface clustering from airborne laser scanning
data, International Archives of Photogrammetry and Remote
Sensing, 32(3A):119-124.
Habib, A., Y. Lee, and M. Morgan, 2001. Surface matching and
change detection using the modified Hough transform for robust
parameter estimation, Photogrammetric Record | Journal,
17(98): 303-315.
Habib, A., Y. Lee, and M. Morgan, 2002. Bundle adjustment
with self-calibration using straight lines, Photogrammetric
Record Journal, 17(100): 635-650.
Kilian, J., N. Haala, and M. Englich, 1996. Capture and
evaluation of airborne laser scanner data, International Archives
of Photogrammetry and Remote Sensing, 31(B3):383-388.
Lee, L, and T. Schenk, 2001. 3D perceptual organization of
laser altimetry data, /nternational Archives of Photogrammetry
and Remote Sensing, 34(3W4):57-65.
Maas, H., and G. Vosselman, 1999. Two algorithms for
extracting building model from raw laser altimetry data, /SPRS
Journal of Photogrammetry and Remote Sensing, 54(2-3):153-
163.
Postolov, Y., A. Krupnik, and K. McIntosh, 1999. Registration
of airborne laser data to surfaces generated by photogrammetric
means, /nternational Archives of Photogrammetry and Remote
Sensing, 32(3W 14):95-99.
Schenk, T., 1999. Determining transformation parameters
between surfaces without identical points, Technical Report
Photogrammetry No. 15, Department of Civil and
Environmental Engineering and Geodetic Science, OSU, 22
pages.
Schenk, T., and B. Csathó, 2002. Fusion of LIDAR data and
aerial imagery for a more complete surface description,
International Archives of Photogrammetry and Remote Sensing,
34(3A):310-317.
6. ACKNOWLEDGEMENTS
This research work has been conducted under the auspices of
the GEOIDE Research Network through its financial support of
the project (ACQZHAB: SIACQO05).
KEY
ABST
Precis
ephen
the pe
the bi
The ©
tropos
Kalm:
differ:
Conti
GLO?
static
the si
frame
foreca
netwo
«e P
in
a N
st
e N
m
e M
e Ir
la
The
applic
syster
statio
broad
who
Virtu:
Netw
stand
Stand
desigi
syste
Howe
RTC]!
propr
FKP
some
differ
to the
