Issues in species classification of trees in old growth conifer stands

Canadian Journal of Remote Sensing

Volumn 31, Issue 2, 2005, Pages 175-190

  Leckie, Donald G ^a   Tinis, Sally ^a   Nelson, Trisalyn ^a   Burnett, Charles ^a   Gougeon, François A ^a   Cloney, Ed ^a   Paradine, Dennis ^a  

^a PACIFIC FORESTRY CENTRE   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATION; CLASSIFICATION (OF INFORMATION); GROWTH KINETICS; IMAGE SENSORS; IMAGING TECHNIQUES; LIGHTING; OBJECT ORIENTED PROGRAMMING; RADIOMETRY;

COMPACT AIRBORNE SPECTROGRAPHIC IMAGER (CASI); IMAGE CLASSIFICATION; PLANT GROWTH; SPECIES CLASSIFICATION;

FORESTRY;

AUTOMATION; CLASSIFICATION; FORESTRY; GROWTH; ILLUMINATION; RADIOMETRY;

EID: 20044383980     PISSN: 07038992     EISSN: 17127971     Source Type: Journal    
DOI: 10.5589/m05-004     Document Type: Article

References (32)

1. Anger, C.D., Mah, S., and Babey, S.K. 1994. Technological enhancements to the compact airborne spectrographic imager (CASI). In Proceedings of the 1st International Airborne Remote Sensing Conference and Exhibition, 12-15 September 1994, Strasbourg, France. ERIM International, Ann Arbor, Mich. Vol. 2, pp. 205-213.
2. Arnott, J.T., and Beese, W.J. 1997. Alternatives to clearcutting in BC coastal montane forests. Forestry Chronicle, Vol. 73, No. 6, pp. 670-678.
3. Babey, S., Anger, C., Achal, S., Ivanco, T., Moise, A., Costella, P., and DeBliek, J. 1999. Development of a next-generation compact airborne spectrographic imager: CASI-2. In Proceedings of the 4th International Airborne Remote Sensing Conference and Exhibition, 21-24 June 1999, Ottawa, Ont. ERIM International, Ann Arbor, Mich. Vol. 1, pp. 229-238.
4. Blackburn, G.A. 2002. Remote sensing of forest pigments using airborne imaging spectrometer and LIDAR imagery. Remote Sensing of Environment, Vol. 82, No. 2, pp. 311-321.
5. Brandtberg, T. 1997. Towards structure-based classification of tree crowns in high resolution aerial images. Scandinavian Journal of Forest Research, Vol. 12, pp. 89-96.
6. Deering, D.W., Middleton, E.M., and Eck, T.F. 1994. Reflectance anisotropy for a spruce-hemlock forest canopy. Remote Sensing of Environment, Vol. 47, pp. 242-260.
7. Dungan, J., Johnson, L., Billow, C., Matson, P., Mazzurco, J., Moen, J., and Vanderbilt, V. 1996. High spectral resolution reflectance of Douglas fir grown under different fertilization treatments: experiment design and treatment effects. Remote Sensing of Environment, Vol. 55, No. 3, pp. 217-228.
8. Gerylo, G., Hall, R.J., Franklin, S.E., Roberts, A., and Milton, E.J. 1998. Hierarchical image classification and extraction of forest species composition and crown closure from airborne multispectral images. Canadian Journal of Remote Sensing, Vol. 24, No. 3, pp. 219-232.
9. Gougeon, F.A. 1995. Comparison of possible multispectral classification schemes for tree crowns individually delineated on high spatial resolution MEIS images. CanadianJournal of Remote Sensing, Vol. 21, No. 1, pp. 1-9.
10. Gougeon, F.A., and Leckie, D.G. 2003. Forest information extraction from high spatial resolution images using an individual tree crown approach. Canadian Forest Service, Natural Resources Canada, Victoria, B.C. Information Report BC-X-396. 26 pp.
11. Goward, S.N., Huemmrich, K.F., and Waring, R.H. 1994. Visible-near infrared spectral reflectance of landscape components in western Oregon. Remote Sensing of Environment, Vol. 47, pp. 190-203.
12. Hughes, J.S., Evans, D.L., and Burns, P.Y. 1986. Identification of two pine species in high-resolution aerial MSS data. Photogrammetric Engineering & Remote Sensing, Vol. 52, No. 8, pp. 1175-1180.
13. Jacquemoud, S., and Ustin, S.L. 2001. Leaf optical properties: a state of the art. In Proceedings of the 8th International Symposium on Physical Measurements and Signatures in Remote Sensing, 8-12 January 2001, Aussois, France. Centre Nationales d’Etudes Spatiales, Toulouse, France. pp. 223-232.
14. Key, T., Warner, T.A., McGraw, J.B., and Fajvan, M.A. 2001. A comparison of multispectral and multitemporal information in high spatial resolution imagery for classification of individual tree species in a temperate hardwood forest. Remote Sensing of Environment, Vol. 75, pp. 100-112.
15. Kimes, D.S., Smith, J.A., and Ranson, K.J. 1980. Vegetation reflectance measurements as a function of solar zenith angle. Photogrammetric Engineering & Remote Sensing, Vol. 46, pp. 1563-1573.
16. Knipling, E.B. 1970. Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation. Remote Sensing of Environment, Vol. 1, pp. 155-159.
17. Leckie, D.G., and Gougeon, F.A. 1999. An assessment of both visual and automated tree counting and species identification with high spatial resolution multispectral imagery. In Proceedings of an International Forum: Automated Interpretation of High Spatial Resolution Digital Imagery for Forestry, 10-12 February 1998, Victoria, B.C. Edited by D.A. Hill and D.G. Leckie. Canadian Forest Service, Natural Resources Canada, Victoria, B.C. pp. 141-152.
18. Leckie, D.G., Yuan, X., Ostaff, D.P., Piene, H., and MacLean, D.A. 1992. Analysis of high resolution multispectral MEIS imagery for spruce budworm damage assessment on a single tree basis. Remote Sensing of Environment, Vol. 40, No. 2, pp. 125-136.
19. Leckie, D., Gougeon, F., Jay, C., Tam, A., Leach, R., and Walsworth, N. 1999. A flexible view angle BRDF compensation system using aircraft orientation information. In Proceedings of the 4th International Airborne Remote Sensing Conference and Exhibition and 21st Canadian Symposium on Remote Sensing, 21-24 June 1999, Ottawa, Ont. ERIM International, Ann Arbor, Mich. Vol. 1, p. 115.
20. Leckie, D.G., Gougeon, F.A., Walsworth, N., and Paradine, D. 2003. Stand delineation and composition estimation using semi-automated individual tree crown analysis. Remote Sensing ofEnvironment, Vol. 85, pp. 355-369.
21. Leckie, D.G., Gougeon, F.A., Tinis, S., Nelson, T., Burnett, C.N., and Paradine, D. 2004a. Automated tree recognition in old growth conifer stands with high resolution digital imagery. Remote Sensing of Environment, Vol. 94, No. 3, pp. 311-326.
22. Leckie, D.G., Jay, C., Gougeon, F., Sturrock, R., and Paradine, D. 2004b. Detection and assessment of trees with Phellinus weirii (laminated root rot) using high resolution multispectral imagery. International Journal Remote Sensing, Vol. 25, No. 4, pp. 793-818.
23. Li, X., and Strahler, A.H. 1992. Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: effect of crown shape and mutual shadowing. IEEE Transactions on Geoscience and Remote Sensing, Vol. 30, pp. 276-292.
24. Lobell, D.B., Asner, G.P., Law, B.E., and Treuhaft, R.N. 2002. View angle effects on canopy reflectance and spectral mixture analysis of coniferous forests using AVIRIS. International Journal of Remote Sensing, Vol. 23, No. 11, pp. 2247-2262.
25. Myneni, R.B., Maggion, S., Iaquinta, J., Privette, J.L., Gobron, N., Pinty, B., Verstraete, M.M., Kimes, D.S., and Williams, D.L. 1995. Optical remote sensing of vegetation: modeling, caveats and algorithms. Remote Sensing of Environment, Vol. 51, pp. 169-188.
26. Preston, R.A., Culvenor, D.S., and Coops, N.C. 1999. Modeling of tree species and structural attributes from high resolution multispectral imagery using decision tree analysis for East Coast Eucalypt forests of Australia. In Proceedings of the International Forum on Automated High Resolution Digital Imagery for Forestry, 10-12 February 1998, Victoria, B.C. Edited by D.A. Hill and D.G. Leckie. Canadian Forest Service, Natural Resources Canada, Victoria, B.C. pp. 225-242.
27. Richards, J.A. 1993. Remote sensing digital analysis.2nd ed. Springer-Verlag, New York. 240 pp.
28. Rock, B.N., Williams, D.L., Moss, D.M., Lauten, G.N., and Kim, M. 1994. High-spectral resolution field and laboratory optical reflectance measurements of red spruce and eastern hemlock needles and branches. Remote Sensing of Environment, Vol. 47, pp. 176-189.
29. van Aardt, J.A.N., and Wynne, R.H. 2001. Spectral separability among six southern tree species. Photogrammetric Engineering & Remote Sensing, Vol. 67, No. 12, pp. 1367-1375.
30. Williams, D.L. 1991. A comparison of spectral reflectance properties at the needle, branch, and canopy level for selected conifer species. Remote Sensing of Environment, Vol. 35, pp. 79-93.
31. Yoder, B.J., and Pettigrew-Crosby, R.E. 1995. Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400-2500 nm) at leaf and canopy scale. Remote Sensing of Environment, Vol. 53, No. 3, pp. 199-211.
32. Zhang, Y., Tian, Y., Myneni, R.B., Knyazikhin, Y., and Woodcock, C.E. 2002. Assessing the information content of multiangle satellite data for mapping biomes I. Statistical analysis. Remote Sensing of Environment, Vol. 80, pp. 418-434.