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Applicability of Geo-spatial Processing Open Sources to Geographic Object-based Image Analysis (GEOBIA)

  • Lee, Ki-Won (Dept. of Information Systems Engineering, Hansung University) ;
  • Kang, Sang-Goo (Dept. of Information Systems Engineering, Hansung University)
  • Received : 2011.05.20
  • Accepted : 2011.06.08
  • Published : 2011.06.30

Abstract

At present, GEOBIA (Geographic Object-based Image Analysis), heir of OBIA (Object-based Image Analysis), is regarded as an important methodology by object-oriented paradigm for remote sensing, dealing with geo-objects related to image segmentation and classification in the different view point of pixel-based processing. This also helps to directly link to GIS applications. Thus, GEOBIA software is on the booming. The main theme of this study is to look into the applicability of geo-spatial processing open source to GEOBIA. However, there is no few fully featured open source for GEOBIA which needs complicated schemes and algorithms, till It was carried out to implement a preliminary system for GEOBIA running an integrated and user-oriented environment. This work was performed by using various open sources such as OTB or PostgreSQL/PostGIS. Some points are different from the widely-used proprietary GEOBIA software. In this system, geo-objects are not file-based ones, but tightly linked with GIS layers in spatial database management system. The mean shift algorithm with parameters associated with spatial similarities or homogeneities is used for image segmentation. For classification process in this work, tree-based model of hierarchical network composing parent and child nodes is implemented by attribute join in the semi-automatic mode, unlike traditional image-based classification. Of course, this integrated GEOBIA system is on the progressing stage, and further works are necessary. It is expected that this approach helps to develop and to extend new applications such as urban mapping or change detection linked to GIS data sets using GEOBIA.

Keywords

References

  1. Addink, E. and F. V. Coillie, 2010. Object-based Image Analysis: Beyond the Squares, GIM International, 24(1).
  2. Blaschke, T., 2010. Object based image analysis for remote sensing, ISPRS Journal of Photogrammetry and Remote Sensing, 65: 2-16. https://doi.org/10.1016/j.isprsjprs.2009.06.004
  3. Blaschke, T., S. Lang, and G. J. Hay, 2010. Objectbased image analysis: spatial concepts for knowledge-driven remote sensing applications, Lecture Notes in Geoinformation and Cartography. Springer, Berlin.
  4. Christophe, E., J. Inglada and A. Giros, 2008. Orfeo Toolbox: A Complete Solution for Mapping from High Resolution Satellite Images, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII. Part B4.
  5. Christophe, E. and J. Inglada, 2009. Open Source Remote Sensing: Increasing the Usability of Cutting-Edge Algorithms, IEEE Geoscience and Remote Sensing Society Newletter, 3: 9-15.
  6. Hay, G. J. and G. Castilla, 2006. Object-based Image Analysis: Strength, Weakness, Opportunities and Threats (SWOT), Commission VI, WG VI/4, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.
  7. Inglada, J. and E. Christophe, 2010. Pragmatic Remote Sensing: A Hands-on Approach to Processing, Tutorial Workshop at IGARSS 2010.
  8. Jakubowski, M., 2007. Software Options for OBIA, Workshop in OBIA Symposium 2007.
  9. Kang, S. and K. Lee, 2010. Open Source Remote Sensing of ORFEO Toolbox and Its Connection to Database of PostGIS with NIX File Importing, Korean Journal of Remote Sensing, 26: 361-371. https://doi.org/10.7780/kjrs.2010.26.3.361
  10. Lang, S., F. Albrecht, and T. Blaschke, 2006. OBIA Tutorial - Introduction to Object-based Image Analysis, v. 1.0, Presentation Material at 2006 OBIA Workshop, Salzburg.
  11. Lang, S., 2009. Object-based Image Understanding: Chances and Challenges for Multi-Scale Landscape Analysis, Presentation Material at Object-based Land Analysis 09, RSPSoc.
  12. Lee, J. B., J. Heo, and Y.-D. Eo, 2007. Study on Selection of Optimized Segmentation Parameters and Analysis of Classification Accuracy for Object-oriented Classification, Korean Journal of Remote Sensing, 23: 521-528. https://doi.org/10.7780/kjrs.2007.23.6.521
  13. Michel, J., C. Valladeau, J. Malik, and J. Inglada, 2010. Object-based and Geo-spatial Image Analysis: A Semi-automatic Pre-operational System, Presentation Material at the CNES Workshop.
  14. Navulur, K., 2006. Multispectral Image Analysis Using the Object-Oriented Paradigm, CRC Press, 184p.
  15. Niemeyer, I., 2009. Object-based Image Analysis: Short Course Remote Sensing 2009, URL http://www.geomonitoring.tu-freiberg.de.
  16. OTB Development Team, 2010. The ORFEO Tool Box Software Guide, Updated for OTB-3.8, 670p.
  17. Yoon, Y., 2007. Object-based Image Fusion Methods using Hypersepctral Remote Sensing Data, 2007 Spring Conference Proceedings of Korean Society of Remote Sensing, in Korean.