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AUTOMATIC TEMPLATE GENERATION FOR INDIVIDUAL TREE IDENTIFICATION IN REMOTE SENSING DATA USING (1+1) EVOLUTIONARY ALGORITHM

Gulbe, Linda

First published: 2014-06-20https://doi.org/10.5593/sgem2014/b23/s10.008View metrics

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Title
AUTOMATIC TEMPLATE GENERATION FOR INDIVIDUAL TREE IDENTIFICATION IN REMOTE SENSING DATA USING (1+1) EVOLUTIONARY ALGORITHM
Authors
Gulbe, Linda
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 14th SGEM GeoConference on INFORMATICS, GEOINFORMATICS AND REMOTE SENSING
Publisher
Stef92 Technology
Year
2014
Pages
Not available yet
ISSN
1314-2704
ISBN
978-619-7105-12-4
Language
en
Publication type
Conference Paper
References16

  1. Ke, Y., & Quackenbush, L. J. A review of methods for automatic individual tree- crown detection and delineation from passive remote sensing. International Journal of Remote Sensing, 32/17, pp. 4725-4747, 2011.

  2. Pollock, R. J. The automatic recognition of individual trees in aerial images of forests based on a synthetic tree crown image model (Doctoral dissertation, Concordia University), 1996 .

  3. Korpela, I. Individual tree measurements by means of digital aerial photogrammetry (Vol. 3). Helsinki, Finland: Finnish Society of Forest Science, 2004 .

  4. Pollock, R. Individual tree recognition based on a synthetic tree crown image model. In Proceedings of the International Forum on Automated Interpretation of High Spatial Resolution Digital Imagery for Forestry. Victoria, BC: Canadian Forest Service, Pacific Forestry Center, pp. 25-34, 1998.

  5. Larsen, M., & Rudemo, M. Using ray-traced templates to find individual trees in aerial photographs. In Proceedings of the Scandinavian Conference on Image Analysis, Vol. 2, pp. 1007-1014, 1997.

  6. Larsen, M. Finding an optimal match window for Spruce top detection based on an optical tree model. In Proc. International Forum on Automated Interpretation of High Spatial Resolution Digital Imagery for Forestry, Victoria, British Columbia, Canada, pp. 55-66, 1998.

  7. Whitley, D. An overview of evolutionary algorithms: practical issues and common pitfalls. Information and software technology, 43/14, pp. 817-831, 2001.

  8. Gulbe, L. Automatic Identification of Individual Tree Crowns in Mixed Forests Using Fusion of LIDAR and Multispectral Data. Technologies of Computer Control, 14, 2013.

  9. Ke, Y., & Quackenbush, L. J. A review of methods for automatic individual tree- crown detection and delineation from passive remote sensing. International Journal of Remote Sensing, 32/17, pp. 4725-4747, 2011.

  10. Pollock, R. J. The automatic recognition of individual trees in aerial images of forests based on a synthetic tree crown image model (Doctoral dissertation, Concordia University), 1996 .

  11. Korpela, I. Individual tree measurements by means of digital aerial photogrammetry (Vol. 3). Helsinki, Finland: Finnish Society of Forest Science, 2004 .

  12. Pollock, R. Individual tree recognition based on a synthetic tree crown image model. In Proceedings of the International Forum on Automated Interpretation of High Spatial Resolution Digital Imagery for Forestry. Victoria, BC: Canadian Forest Service, Pacific Forestry Center, pp. 25-34, 1998.

  13. Larsen, M., & Rudemo, M. Using ray-traced templates to find individual trees in aerial photographs. In Proceedings of the Scandinavian Conference on Image Analysis, Vol. 2, pp. 1007-1014, 1997.

  14. Larsen, M. Finding an optimal match window for Spruce top detection based on an optical tree model. In Proc. International Forum on Automated Interpretation of High Spatial Resolution Digital Imagery for Forestry, Victoria, British Columbia, Canada, pp. 55-66, 1998.

  15. Whitley, D. An overview of evolutionary algorithms: practical issues and common pitfalls. Information and software technology, 43/14, pp. 817-831, 2001.

  16. Gulbe, L. Automatic Identification of Individual Tree Crowns in Mixed Forests Using Fusion of LIDAR and Multispectral Data. Technologies of Computer Control, 14, 2013.

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