Semi-automated procedures for tree species identification in high spatial resolution data from digitized colour infrared-aerial photography

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 51, Issue 1, 1996, Pages 5-16

  Meyer, P ^a   Staenz, K ^b   Itten, K I ^a  

^a UNIVERSITY OF ZURICH   (Switzerland)

^b CANADA CENTRE FOR REMOTE SENSING   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

AERIAL PHOTOGRAPHY; CLASSIFICATION; COLOUR INFRARED PHOTOGRAPHY; DIGITISED PHOTOGRAPHY; REMOTE SENSING; SPECIES IDENTIFICATION; TREE; TREE SPECIES IDENTIFICATION;

EID: 0029667336     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/0924-2716(96)00003-2     Document Type: Article

References (40)

1. Ahern, F.J. and Leckie, D.G., 1987. Digital remote sensing of forestry: requirements and capabilities, today and tomorrow. Geocarto Int., 3: 43-52.
2. Ahern, F.J., Sirois, J., McColl, W.D., Gauthier, R.P., Alföldi, T.T., Patterson, W.H. and Erdle, T.H., 1991. Progress toward improving aerial defoliation survey methods by using electronic imagers. Photogramm. Eng. Remote Sensing, 57(2): 187-193.
3. Czaplewski, R.L., Cost, N.D., Moore, R.A. and Bernu, C.J., 1989. Photointerpreting forest type and stand characterization in South Carolina. 12th Biennial Workshop Color Aerial Photography and Videography, Sparks, Nev., pp. 51-59.
4. Dipix, 1990. ARIES-II V-Stream User's Manual. Dipix Systems Ltd., Ottawa, Ont.
5. EAFV, 1984. Schadenkarte 1:5000, Wald Würenlingen/ Döttingen. Swiss Federal Institute of Forestry Research, Birmensdorf.
6. Fritz, N., 1967. Optimum methods for using infrared sensitive color film. Photogramm. Eng., 33(6): 1128-1138.
7. Gougeon, F.A., 1993. Individual tree identification from high resolution MEIS images. International Forum on Airborne Multispectral Scanning for Forestry and Mapping, Information Report PI-X-113, Forestry Canada, Val-Morin, Que., pp. 117-128.
8. Gougeon, F.A., 1995a. Comparison of possible multispectral classification schemes for tree individually delineated on high spatial resolution MEIS images. Can. J. Remote Sensing, 21(1): 1-9.
9. Gougeon, F.A., 1995b. A crown-following approach to the automated delineation of individual tree crowns in high spectral resolution aerial images. Can. J. Remote Sensing, 21(3): 274-284.
10. Gougeon, F.A. and Moore, T., 1988. Classification individuelle des arbres à partir d'images à haute résolution spatiale. 6th Congr. Assoc. québécoise de télédétection, Sherbrooke, Que., pp. 185-196.
11. Guyot, G., Guyon, D. and Riom, J., 1989. Factors affecting the spectral response of forest canopies: a review. Geocarto Int., 3: 3-18.
12. Hertel, D., Pelz, E. and Wienhold, C., 1992. Standardisierung von Farbinfrarot-Luftbildern als Grundlage für das Monitoring von Waldschäden. Photogramm. Fernerkund., 6: 181-189.
13. Hildebrandt, G. and Kadro, A., 1984. Aspects of country wide inventory and monitoring of actual forest damages in Germany. Bildmess. Luftbildwes., 3a: 201-216.
14. Itten, K.I., Meyer, P., Kellenberger, T., Leu, R., Sandmeier, St., Bitter, P. and Seidel, K., 1992. Correction of the impact of topography and atmosphere on Landsat-TM forest mapping of alpine regions. Department of Geography, University of Zurich, Remote Sensing Ser., Vol. 18, 48 pp.
15. Kadro, A., 1990. Forest damage inventory using Landsat imagery by means of computer-aided classification. Proc. Symp. Global and Environmental Monitoring, ISPRS Comm. VII, Victoria, B.C., pp. 425-432.
16. Kalayeh, H.M. and Landgrebe, D.A., 1983. Predicting the required number of training samples. IEEE Trans. Pattern Anal. Machine Intell., 5: 493-504.
17. Kalensky, Z.D., Moore, W.C., Campbell, G.A., Wilson, D.A. and Scott, A.J., 1981. Summary forest resource data from Landsat images. Final Report of a Pilot Study for Northern Saskatchewan, Information Report PI-X-5, Petawawa National Forestry Institute, Canadian Forestry Service, Chalk River, Ont., 84 pages.
18. Kritikos, G., Kuebler, D., Kadro, H. and Koch, D., 1984. Untersuchung von Flugzeugscannerdaten zur Erfassung von Waldschaeden. Institute for Optoelectronics, DLR, Oberpfaffenhofen, 98 pp.
19. Leckie, D.G., 1990. Advances in remote sensing technologies for forest surveys and management. Can. J. For. Res., 20: 464-483.
20. Lindenlaub, J.C., 1973. Guide to multispectral data analysis using LARSYS. LARS Information Note 062873. Purdue University, West Lafayette, Ind., 88 pp.
21. Masumy, S.A., 1978. Analyse von Texturparametern in Luftbildern und Scanneraufzeichnungen verschiedener Masstaebe zur Identifizierung von Waldtypen. Ph.D. Thesis, Forestry Faculty, Albert-Ludwigs-University, Freiburg Br., 167 pp.
22. Maurer, H. and Meier, E., 1987. Digitale Waldschadenkartierung der Nadelhölzer. Department of Geography, University of Zurich, Remote Sensing Ser., Vol. 12, 33 pp.
23. Maurer, H., Meier, E., Haefner, H. and Frei, U., 1983. Automatisierte Baumarten-Kartierung mit grossmasstaebigen Infrarot-Farbluftbildern. Schweiz. Z. Forstwes., 1: 37-47.
24. Meyer, P., Itten, K.I., Kellenberger, T., Sandmeier, S. and Sandmeier, R., 1993. Radiometric correction of topographically induced effects on Landsat TM data in alpine terrain. ISPRS J. Photogramm. Remote Sensing, 48(4): 17-28.
25. Moore, R.E., 1980. Film-filter combinations for aerial colour photography. Canadian Department of Supply and Services, No. SMP-1263E, Ottawa, Ont., 32 pp.
26. Mueller, E. and Itten, K.I., 1985. Eignung von Landsat-4 thematic mapper daten für Waldbestandeskartierungen. Proc. IUFRO Conf. Inventorying and Monitoring Endangered Forests, Zurich, pp. 67-75.
27. Murtha, P.A. and Fournier, R.A., 1992. Varying reflectance patterns influence photo interpretation of dead tree crowns. Can. J. Remote Sensing, 18(3): 167-173.
28. Murtha, P.A. and Wiart, R.J., 1989. PC-based digital analysis of mountain pine beetle currant-attacked and non-attacked lodgepole pine. J. Remote Sensing, 15(1): 70-76.
29. Neville, R.A. and Till, S.M., 1991. MEIS FM: a multispectral imager for forestry and mapping. IEEE Trans. Geosci. Remote Sensing, 29(1): 184-186.
30. Neville, R.A., Marois, R., Schwarz, J.W. and Till, S.M., 1992. Wide-angle high-resolution line-imager prototype flight test results. Appl. Optics, 31(18): 3463-3472.
31. Neville, R.A., Rowlands, R. and Powell, L., 1995. SFSI: Canada's first airborne SWIR Imaging Spectrometer. Can. J. Remote Sensing, 21(3): 328-336.
32. Pinz, A., 1991. A computer vision system for the recognition of trees in aerial photographs. Proc. Multisource Data Integration in Remote Sensing. NASA Conf. Publ., 3099: 111-124.
33. Pinz, A.J. and Bischof, H., 1990. Constructing a neural network for the interpretation of species of trees in aerial photographs. Proc. 10th Int. Conf. Pattern Recognition, Atlantic City, N.J., pp. 755-757.
34. Sayn-Wittgenstein, L., 1978. Recognition of tree type species on aerial photographs. Canadian Forestry Service, Forest Management Institute, Information Report FMR-X-118, Ottawa, Ont., 97 pp.
35. Seidel, K., 1976. Digitale Bildverarbeitung. Technical Report, Institute for Communication Techniques, Swiss Federal Institute of Technology, Zurich, 22 pp.
36. Staenz, K., Meier, E.H., Nuesch, D.R., Itten, K.I. and Haefner, H., 1985. Resource monitoring oriented remote sensing data processing capabilities. Proc. Int. Geoscience and Remote Sensing Symposium (IGARSS'85), Amhurst, Mass., pp. 1109-1116.
37. St-Onge, B.A. and Cavayas, F., 1991. La segmentation d'images de forêt de haute résolution à l'aide de mesures de texture basées sur le demivariogramme. Proc. 7th Congr. Assoc. québécoise de télédétection, Montreal, Que., pp. 219-225.
38. Taylor, M.M., 1974. Principle components color display of ERTS imagery. Proc. 2nd Can. Symp. Remote Sensing, Guelph, Ont., pp. 214-221.
39. Vogelmann, J.E. and Rock, B., 1988. Assessing forest damage in high-elevation coniferous forests in Vermont and New Hampshire using thematic mapper data. Remote Sensing Environ., 24: 227-246.
40. Zaremba, M.B., Locas, M. and Gougeon, F.A., 1993. La reconnaissance des arbres sur une image multispectrale de haute résolution par des réseaux neuronaux. Proc. 16th Can. Symp. Remote Sensing and 8th Congr. Assoc. québécoise de télédétection, Sherbrooke, Que., pp. 757-760.