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Automatic Open Space Area Extraction and Change Detection from High Resolution Urban Satellite Images

Published on None 2010 by Hiremath P. S., Kodge B.G.
journal_cover_thumbnail

Recent Trends in Image Processing and Pattern Recognition
Foundation of Computer Science USA
RTIPPR - Number 2
None 2010
Authors: Hiremath P. S., Kodge B.G.
4628df00-565b-4c92-b0d5-21108df816fc

Hiremath P. S., Kodge B.G. . Automatic Open Space Area Extraction and Change Detection from High Resolution Urban Satellite Images. Recent Trends in Image Processing and Pattern Recognition. RTIPPR, 2 (None 2010), 76-82.

@article{
author = { Hiremath P. S., Kodge B.G. },
title = { Automatic Open Space Area Extraction and Change Detection from High Resolution Urban Satellite Images },
journal = { Recent Trends in Image Processing and Pattern Recognition },
issue_date = { None 2010 },
volume = { RTIPPR },
number = { 2 },
month = { None },
year = { 2010 },
issn = 0975-8887,
pages = { 76-82 },
numpages = 7,
url = { /specialissues/rtippr/number2/979-102/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Recent Trends in Image Processing and Pattern Recognition
%A Hiremath P. S.
%A Kodge B.G.
%T Automatic Open Space Area Extraction and Change Detection from High Resolution Urban Satellite Images
%J Recent Trends in Image Processing and Pattern Recognition
%@ 0975-8887
%V RTIPPR
%N 2
%P 76-82
%D 2010
%I International Journal of Computer Applications
Abstract

In this paper, we study efficient and reliable automatic extraction algorithm to find out the open space area from the high resolution urban satellite imagery, and to detect changes from the extracted open space area during the period 2003, 2006 and 2008. This automatic extraction and change detection algorithm uses some filters, segmentation and grouping that are applied on satellite images. The resultant images may be used to calculate the total available open space area and the built up area. It may also be used to compare the difference between present and past open space area using historical urban satellite images of that same projection, which is an important geo spatial data management application.

References
  1. Y. Li, R. Briggs. Scalable and error tolerant automated georeferencing under affine transformations. IEEE International Geoscience and Remote Sensing Symposium, Boston, MA, July 2008.
  2. Y. Li, R. Briggs. Automated georeferencing based on topological point pattern matching. The International Symposium on Automated Cartography (AutoCarto), Vancouver, WA, June 2006.
  3. J.B. Mena. State of the Art on Automatic Road Extraction for GIS Update: a Novel Classification. Pattern Recognition Letters, 24(16):3037-3058, 2003.
  4. M.-F. Auclair-Fortier, D. Ziou, C. Armenakis, and S. Wang. Survey of Work on Road Extraction in Aerial and Satellite Images. Technical Report 241, Département de mathématiques et d’informatique, Université de Sherbrooke, 1999.
  5. G. Vosselman, J.D. Knecht. Road Tracking by Profile Matching and Kalman Filtering. Workshop on Automatic Extraction of Man-Made Objects from Aerial and Space Images, pages 265-274, 1995.
  6. D.M. Mckeown, J.L. Denlinger. Cooperative Methods for Road Tracking in Aerial Imagery. Workshop Computer Vision Pattern Recognition, pages 662-672, 1988.
  7. A. Gruen, H. Li. Semi-automatic Linear Feature Extraction by Dynamic Programming and LSB-Snakes. Photogrammet Eng. Remote Sensing 63, pages 985-995, 1997.
  8. S.B. Hinz, A. Ebner. Modeling Contextual Knowledge for Controlling Road Extraction in Urban Areas. IEEE/ISPRS Joint Workshop Remote Sensing Data Fusion over Urban Areas, 2001.
  9. T. Ohlhof, T. Emge, W. Reinhardt, K. Leukert, C. Heipke, K. Pakzad. Generation and Update of VMAP data using satellite and airbone imagery. Remote Sensing, vol 33, pages 763-768, 2000.
  10. A. Baumgartner, C.T. Steger, H. Mayer, and W. Eckstein. Multi- Resolution, Semantic Objects, and Context for Road Extraction. In Wolfgang Förstner and Lutz Plümer, editors, Semantic Modeling for the Acquisition of Topographic Information from Images and Maps, pages 140–156, Basel, Switzerland, 1997. Birkhäuser Verlag.
  11. A. Baumgartner, C.T. Steger, C. Wiedemann, H. Mayer, W. Eckstein, and H. Ebner. Update of Roads in GIS from Aerial Imagery: Verification and Multi-Resolution Extraction. Proceedings of International Archives of Photogrammetry and Remote Sensing, XXXI B3/III:53–58, 1996.
  12. http://earth.google.com/intl/en/download-earth.html
  13. Rajiv Kumar Nath, S K Deb, Waterbody area extraction from high resolution satellite images, IJIP, Vol. 3, Issue 6, 353-372.
Index Terms

Computer Science
Information Sciences

Keywords

Automatic open space area extraction Image segmentation Feature extraction geo spatial data and change detection