• Oğuz karan
  • H. Arsev Eraslan
  • Sefer Kurnaz
Keywords: Terrain recognition, data fusion, terrain identification


In this study, a terrain recognition system is developed by using three dimensional topographic data, two dimensional aerial images and satellite images. For this system, three dimensional Object Knowledge Based Composite Photogrammetry Technology is used. This technology is applied to terrain areas for the first time by using real data. Thus when selecting the fiducial points, important area elements such as buildings and roads are used. Feasibility of the technology is proven for terrain areas which have structures such as buildings and roads, and have only hills and hollows without human made structures.


[1] Goldolf, D.B and Huang, T.S and Lee,H. 1989. A Curvature-Based Approach to Terrain Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(11);1213 - 1217.
[2] Yihui L. and Kubik, K. and Bennamoun, M. 1998. Image segmentation and image matching for 3D terrain reconstruction. Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on. 2; 1535-1537.
[3] Blow, J. 2000. Terrain Rendering at High Levels of Details. Bolt Action Software, March 11.
[4] Zhang,C and Baltsavias, E. and Gruen.A. 2001. Knowledge-Based Image Analysis for 3D Road Construction. Asian Journal of Geoinformatics.1(4);3-14.
[5] Baltsavias, E.P. 2002. Object Extraction and Revision by Image Analysis Using Existing Geospatial Data and Knowledge: State-of-the-Art and Steps towards Operational Systems. IAPRS. XXXIV(2);13-22.
[6] Roettger, S. and Heidrich, W. and Slusallek, P. and Seidel, H.P. 1998. Real-Time Generation of Continuous Levels of Detail for Height Fields. In V. Skala, editor, Proc. WSCG 98; 315-322.
[7] Jung, I.K and Lacroix,S. 2003.High resolution terrain mapping using low altitude aerial stereo imagery. Proceedings of the Ninth IEEE International Conference on Computer Vision.2; 946.
[8] Kim, S.H. and Wohn, K. 2003. TERRAN:out-of-core Terrain Rendering for Real-time Navigation.22(3).
[9] Dachsbacher, C. and Stamminger,M. 2004. Rendering Procedural Terrain by Geometry Image Warping. Eurographics Association. Proc. Rendering Techniques; 103-110.
[10] Lee, K.S. and Grunes,M.R. and Pottier, E. and Ferro-Famil, L. 2005. Automated Terrain Classification Using Polarimetric Synthetic Aperture Radar. NRL-Review; 203-205.
[11] Pouderoux, J and Marvie, J.E. 2005. Adaptive Streaming and rendering of Large Terrains using Strip Masks. Proceedings of ACM GRAPHITE; 209-306.
[12] Vasile, A.N. and Marino, R.M. Lincoln Laboratory Journal. 15(1); 61-78.
[13] Wolf, D.F. and Sukhatme, G.S. and Fox, D. and Burgard, W. 2005.Autonomous Terrain Mapping and Classification Using Hidden Markov Models.Proceedings of the 2005 IEEE International Conference on Robotics and Automation;2038-2043.
[14] Kaichang Di, R.L. and Wang, J. and He, S. 2007. Rock Modeling and Matching for Autonomous Long Range Mars Rover Localization. Journal of Field Robotics.24(3);187-203
[15] Tidey, E. and Harris, C. and Revell, J. and Claxton, C. 2008. Map Registiration with 3D Enhanced Terrain Classification. 3rd SEAS DTC Technical Conference-Edinburgh;A9
[16] Eds Jachtvliegtuigen,
[17] Top gun:The next generation, National Guard, Government Industry, Jan 1999, McCrone, James, Seidenman, Paul
[18] A. H. Eraslan: United States Patent: Three-Dimensional Face Identification System. U.S. Patent No. US 6,381,346 B1. Preliminary application date: Dec. 1997. Date of patent: April 30, 2002.
[19] A. H. Eraslan, ILEFIS (Integrated Law-Enforcement Face-Identification System. National Technology Transfer Center-Office of Law Enforcement Technology Commercialization, March 7, 1997.
How to Cite
O. karan, H. Eraslan, and S. Kurnaz, “TOPOGRAFİK BİLGİLER VE UYDU GÖRÜNTÜ VERİLERİNİ KULLANARAK 3 BOYUTLU ALAN TANIMA SİSTEMİ”, JAST, vol. 4, no. 4, pp. 31-40, Jul. 2010.