Figure 8 shows DEM using measurement results at 3 stations. It
can be recognized that lack of measuring data is successfully
performed.
5. VISUAL TRAVERSE
Visual traverse survey using ground based laser scanning
sensor was proposed in this paper, and visual traverse survey
were performed using the above procedures which were
investigated in premeasurement.
The followings are the major contents for the traverse area.
Figure 9 (a) shows the scene from the station 2 and Figure 9 (b)
shows the results of 3D traverse.
+ Target: Baseball Field at TDU
+ Measurement Area: 200m*200m
+ Traverse Point: 6 points
+ Length for leg of traverse: 390m
(a) Measurement Area
(b) 3D Image (1m mesh)
Figure 9. Measurement Result of Visual Traverse
5.1 Accuracy
In order to evaluate the accuracy of visual traverse, traverse
survey using total station (accuracy:2”, +(S+2ppmxD) mm))
was also performed at the same station. Accuracy for traverse
by total station was 1/22,000, and accuracy for traverse by laser
scanning sensor was 1/9,000.
High accuracy was not estimated in comparison with total
stations due to the accuracy of laser scanning sensor is £25mm.
Nevertheless, it can be seen that good accuracy was acquired.
Furthermore, take into account that 1/5000 ~ 1/10000 is
demanded in general survey, it is concluded that traverse
survey using laser scanning sensor is enough accuracy.
6. CONCLUSION
Visual traverse using ground based laser scanning sensor was
proposed in this paper, and noise reduction and interpolation
methods and unification of coordinate system were investigated.
Visual traverse was performed, and it is recognized that the
enough accuracy can be obtained.
Consequently, it is concluded that ground based laser scanner
will become useful tool in the topographic survey. In particular,
the remarkable points as additional results are its ability to
perform 3D visual traverse survey.
Reference from Journals
1. H.Masaharu, H.Hasegawa, 2000, Three-dimensional city
modeling from laser scanner data by extracting building
polygons using region segmentation method, International
Archives of Photogrammetry and Remote Sensing, Vol.33,
Part B3, pp.556-562.
Reference from Website
2. K. Kraus, N. Pfeifer, 2001. IAPRS Vol XXXIV, Part 3/WA,
Annapolis, Maryland, USA “ADVANCED DTM
GENERATION FROM LIDAR DATA”,
http://www.ipf.tuwien.ac.at/np/articles+abstracts/annapolis_k
rauspfeifer.pdf (accessed 15 Jun. 2002)
Reference from Books
3. David F. Rogers, 1985, Procedural Elements for Computer
Graphics, McGraw-Hill, Inc.
4. AutoDesk, 2000, AutoCAD 20001 User Guide, AutoDesk
Inc.
5. David C. Kay, John. R. Levine, 1995, Graphics File Formats
Second edition, McGraw-Hill, Inc.
298.
KEY
ABS
Indu:
com
draw
com
other
the v
basec
exam
repre
subse
Obje
It is
often
objec
recog
place
cases
objec
usual
comp
indus
matcl
matcl
class
of the
A mq
edges
1988
gener
All o
high
arbitr
recog
devel
2001)
modi
the di
and t
evalu
comp
two n
All ¢
comn
repre: