Full text: Technical Commission VII (B7)

  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
superimposition between digital orthophoto and error distribution 
for GPS onboard and Google Earth respectively. 
  
Elsvation 
Eastme 
Northing 
  
  
Easting Northing 
  
  
(a) 
(b) 
Figure 6. Error Distribution; (a) GPS onboard; (b) Google Earth 
Based on Figure 6, most of the errors were distributed at the 
diagonal of digital orthophoto. It might be caused by interpolation 
of control points during image processing. The distribution error 
for x, and in this study, the accuracy of all photogrammetric 
products that were produced by using GPS onboard and GE 
control points were calculated by using root mean square error 
(RMSE). The accuracy was achieved based on digital orthophoto 
and digital elevation model from both methods. There were 57 
checkpoints that were established randomly in the study area. 
RMSE for GPS onboard is +11.853 and RMSE for GE control 
points is 413.770 (Figure 7). 
  
  
RMSE Chart 
  
iis; 
  
  
  
onboard GPS Google Earth 
  
  
Figure 7. RMSE results 
Based on Figure 7, the accuracy of GPS onboard gives a medium 
accuracy. Thus, it can be used for updating Google Earth image 
because satellite images from google earth gives error within 
+15m (Redzwan and Ramli, 2007). 
6. CONCLUSION & FUTURE WORK 
In conclusion, the proposed image registration method can 
improve image processing result with the condition that GPS 
onboard is stable during image acquisition. Furthermore, the 
difference of GPS onboard and GE control points is about 
+2meter. It can be concluded that GPS onboard has its limitation 
in x and y positioning which might be caused by GPS error. In 
future, calibration of GPS onboard will be carried out and the 
accuracy of GPS onboard will be assessed. 
ACKNOWLEDGEMENT 
Faculty of Architecture, Planning and Surveying Universiti 
Teknologi MARA (UiTM) and Faculty of Geoinformation & Real 
Estate, Universiti Teknologi Malaysia (UTM) are greatly 
acknowledged. 
REFERENCES 
498 
David, G.S.III, and Benjamin, R.D., Charles, R., 2008. Development and 
Application of an Autonomous Unmanned Aerial Vehicle for Precise 
Aerobiological Sampling above Agricultural Fields. Journal of Field 
Robotics, 25 (3), pp. 133-147. 
Dingus, B.R., Schmale, D.G., and Reinholtz, C.F., 2007. Development of 
an autonomous unmanned aerial vehicle for aerobiological sampling. 
Phytopathology, 97(7), pp. 184. 
Jwa, S. and Ozguner, U., 2007. Multi-UAV sensing over urban areas via 
layered data fusion. Statistical Signal Processing, SSP '07. IEEE/SP 145 
workshop on, pp. 576-580 
Grenzdorffer, GJ, Engel, A, and Teichert, B. 2008. The 
Photogrammetric Potential of Low-Cost UAVs in Forestry and 
Agriculture. The international Archives of the Photogrammetry, Remote 
Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. 
Beijing, pp. 1207-1214 
Herwitz, S.R., Johnson, L.F., Dunagan, S.E., Higgins, R.G., Sullivan, 
D.V., Zheng, J., Lobitz, B.M., Leung, J.G., Gallmeyer, B., Aoyagi, M., 
Slye, R.E. and Brass, J., 2004. Demonstration of UAV-based imaging for 
agricultural surveillance and decision support. Computer and Electronics 
in Agriculture, 44, pp.49-61 
Osborne, J. and Rysdyk, R.,2005. Waypoint Guidance for Small UAVs in 
Wind. American Institute of Aeronautics and Astronautics University of 
Washington, Seattle, WA, 98115,USA. 
Paul R.W. and Bon A.D., 2004. Elements of Photogrammetry with 
application in GIS. International Edition. McGrawHill, pp. 551-554. 
Potere, D., 2008. ,Horizontal Positional Accuracy of Google Earth’s High 
Resolution Imagery Archive Sensors 2008, 8, 7973-7981; DOI: 
10.3390/s8127973 
Redzwan, G., and Ramli, M.F.,2007. Geo-referencing the Satellite Image 
from Google Earth by Relative and Absolute Positioning. Malaysian 
Journal of Science, 26 (2), pp. 135-141. ISSN 13943065 
UVSIA, 2010. UAV Categories. Unmanned Vehicle Systems. 
International Association http://www.uav-info.com/uav-pdf/uav- 
categories.pdf (20 February 2011) 
Tahar, K.N and Ahmad, A.,2011. Capability of Low Cost Digital Camera 
for Production of Orthophoto and Volume Determination. CSPA 2011 7th 
International Colloquium on Signal Processing & Its Applications IEEE. 
Penang, Malaysia, pp. 67-71. 
Tahar, K.N., and Ahmad, A., 2012. A simulation study on the capabilities 
of rotor wing unmanned aerial vehicle in aerial terrain mapping. 
International Journal of Physical Sciences, 7(8), pp.1300 — 1306. doi: 
10.5897/IJPS11.969
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.