Environmental Monitoring Using Image Analysis

  • Alexey Anufriev
  • Heikki Kälviäinen
  • Arto Kaarna
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)


Environmental monitoring is an important task while estimating for example the influence of human activities in the nature. In this paper image analysis methods for performing these monitoring tasks are presented. We focus on the analyses of vegetation changes in lake water areas. Aerial photos taken in years 1996 and 1999 are used for the environmental monitoring of the largest Finnish lake, called Lake Saimaa. The first image analysis step is a geometrical correction that maps the analyzed images to the same coordinate system and to the same scale. The second step is to match the corresponding local regions. The third step is to find changes in vegetation. To detect vegetation we apply different classification approaches, including supervised and unsupervised classification methods. Experiments with different images, influenced by illumination, weather conditions, photographing angles, gave promising results.


Environmental Monitoring Near Neighbor Digital Image Analysis Geometric Correction Ground Control Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    ENVI Tutorials. Research Systems, 2001.Google Scholar
  2. 2.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison-Wesley, 2nd edition, 2002.Google Scholar
  3. 3.
    Kaarna, A., Kälviäinen, H., Anufriev, A., Mankki, J., Malkavaara, T., Jantunen, M.: Geometric Correction and Segmentation of Images in Change Detection of Water Plants in Soinilansalmi. Accepted to Proceedings of International Geoscience and Remote Sensing Symposium, IGARSS’2003, Toulouse, France, 2003.Google Scholar
  4. 4.
    Kaarna, A., Spacil, R., Jantunen, M.: Pattern Recognition Methods as Tools of Restoration Project in Maavesi Water Area, Proceedings of International Geoscience and Remote Sensing Symposium, IGARSS’2002, Toronto, Canada, 23–27 June, 2002, vol VI, pp. 3264–3266.CrossRefGoogle Scholar
  5. 5.
    Lillesand, T.M., Kiefer, R.W.: Remote Sensing and Image Interpretation. John Wiley and Sons, 2000.Google Scholar
  6. 6.
    Mankki, J., Malkavaara, T.: Water Plants in Soinilansalmi at Ruokolahti, Resume of the actions in 1996–1999. Kymijoki Water Protection Association, Report No. 31/2000 (in Finnish).Google Scholar
  7. 7.
    Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS 2002), Toronto, Canada, 2002.Google Scholar
  8. 8.
    Schalkoff, R.: Pattern Recognition: Statistical, Structural, and Neural Approaches. John Wiley & Sons, Inc., 1992.Google Scholar
  9. 9.
    Richards, J.A.: Remote Sensing Digital Image Analysis. Springer-Verlag, Berlin, 1993.Google Scholar
  10. 10.
    Thomas, P.: Image Registration by Differential Evolution. Proceedings of Irish Machine Vision and Image Processing Conference, Londonderry, Northern Ireland, September 10–13, 1997, pp. 221–225.Google Scholar
  11. 11.
    Tou, J.T., Gonzalez, R.C.: Pattern Recognition Principles. Addison-Wesley, 1974.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Alexey Anufriev
    • 1
  • Heikki Kälviäinen
    • 1
  • Arto Kaarna
    • 2
  1. 1.Laboratory of Information ProcessingLappeenranta University of TechnologyLappeenrantaFinland
  2. 2.Laboratory of Telecommunications Department of Information TechnologyLappeenranta University of TechnologyLappeenrantaFinland

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