XXII ISPRS Congress 2012: Technical Commission VII

Bibliographic data

Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/7, III/2, V/1, V/3, ICWG V/I: LOW-COST UAVS (UVSS) AND MOBILE MAPPING SYSTEMS]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: AERIAL TERRAIN MAPPING USING UNMANNED AERIAL VEHICLE APPROACH K. N. Tahar

Document type:: Multivolume work

Structure type:: Chapter

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

Access restriction

Copyright

fullscreen: Technical Commission VII (B7)

Multivolume work

Volume

Chapter

Chapter

Table of contents

Cite and reuse

Volume

Chapter

Image

Image fragment

Citation links

Citation recommendation