Gain to be achieved from stand delineation in LANDSAT TM image-based estimates of stand volume

Forest Ecology and Management

Volumn 124, Issue 2-3, 1999, Pages 105-111

  Kilpeläinen, Pertti ^a   Tokola, Timo ^a  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

Author keywords

Multisource data; Remote sensing; Satellite image interpretation; Stand inventory

Indexed keywords

BIOMASS; ESTIMATION METHOD; FOREST MANAGEMENT; LANDSAT THEMATIC MAPPER; REMOTE SENSING; STANDING STOCK;

EID: 0345148982     PISSN: 03781127     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0378-1127(99)00059-6     Document Type: Article

References (38)

1. Ardö J. Volume quantification of coniferous forest compartments using spectral radiance recorded by LANDSAT Thematic Mapper. Internat. J. Remote Sensing. 13(9):1992;1779-1786.
2. Askne, J., Dammert, P., Smith, G., 1997. Interferometric SAR Observations of forested areas. The 3rd ERS Symposium (ESA), 18-21 March 1997, Florence, Italy.
3. Bauer, M.E., Burk, T.E., Ek, A.R., Coppin, P.R., Lime, S.D., Walsh, T.A., Walters, D.K., Befort, W., Heinzen, D.F., 1997. Satellite Inventory of Minnesota Forest Resources. Photogrammetric Engineering and Remote Sensing (in press).
4. Campbell, J.M., 1987. Introduction to Remote Sensing. The Guildford Press, New York. pp. 541.
5. Dralle K., Rudemo M. Stem number estimation by kernel smoothing in aerial photos. Can. J. For. Res. 26:1996;1228-1236.
6. Franklin J. Thematic Mapper analysis of coniferous forest structure and composition. Internat. J. Remote Sensing. 7:1986;1287-1588.
7. Franklin S.E., Wilson B.A. A three-stage classifier for remote sensing of mountain environments. Photogram. Eng. Remote Sensing. 58:1992;449-454.
8. Franklin S.E. Discrimination of subalpine forest species and canopy density using digital CASI, SPOT PLA, and LANDSAT TM data. Photogram. Eng. Remote Sensing. 60:1994;1233-1241.
9. Hagner, O., 1989. Computer aided forest mapping and estimation of stand characteristics using satellite remote sensing. Swedish University of Agricultural Sciences, Department of Biometry and Forest Management, Work report. pp. 11.
10. Holmgren P., Thuresson T., Holm S. Estimating forest characteristics in scanned aerial photographs with respect to requirements for economic forest management planning. Scand. J. For. Res. 12:1997;189-199.
11. Holopainen, M., Lukkarinen, E., 1994. Digitaalisten ilmakuvien käyttö metsävarojen inventoinnissa. University of Helsinki, Department of Forest Resource Management Publications 4. ISBN 951-45-6677-7.
12. Horler D.N.H., Ahern F.J. Forestry information content of Thematic Mapper data. Internat. J. Remote Sensing. 7(3):1986;405-428.
13. Hutchinson C.F. Techniques for combining LANDSAT and ancillary data for digital classification improvement. Photogram. Eng. Remote Sensing. 48:1982;123-130.
14. Hyppänen H. Spatial autocorrelation and optimal spatial resolution of optical remote sensing data in boreal forest environment. Internat. J. Remote Sensing. 17(17):1996;3441-3452.
15. Hyyppä, J., 1998. Uudet menetelmät metsien kaukokartoituksessa (New methods in remote sensing of forests). Final report. Helsinki University of Technology, Laboratory of Space Technology. pp. 23 (in Finnish).
16. Kilkki P., Päivinen R., 1986. Reference sample plots to combine field measurements and satellite data in forest inventory. In: Remote Sensing-aided Forest Inventory. Proc. seminars organised by SNS, Hyytiälä, Finland, Dec. 10-12, 1986. University of Helsinki, Department of Forest Mensuration and management, Research Notes No 19. pp. 209-215.
17. Laasenaho, J., Päivinen, R., 1986. Kuvioittaisen arvioinnin tarkistamisesta (Summary: On the checking of inventory by compartments). Folia For. 664, pp. 1-19. (In Finnish with English summary).
18. Muinonen, E., Tokola, T., 1990. An application of remote sensing for communal forest inventory. Proceedings from SNS/IUFRO workshop in Umeå 26-28 Feb., 1990. Remote Sensing Laboratory, Swedish University of Agricultural Sciences, Report 4. pp. 35-42.
19. Narendra, P.M., Goldberg, M., 1980. Image segmentation with directed trees. IEEE Transactions on pattern analysis and machine intelligence. PAMI-2(2). pp. 185-191.
20. Peddle D., Franklin S.E. Image texture processing and data integration for surface pattern discrimination. Photogram. Eng. Remote Sensing. 57(4):1991;413-420.
21. Poso S. Kuvioittaisen arvioinnin perusteita (Summary: Basic features of Forest Inventory by compartments). Silva Fenn. 17:1983;313-349.
22. Poso S., Häme T., Paananen R. A method of estimating the stand characteristics of a forest compartment using satellite imagery. Silva Fenn. 18(3):1984;261-292.
23. Poso S., Paananen R., Similä M. Forest inventory by compartments using satellite imagery (Summary: Satelliittikuvia hyväksikäyttävä metsän inventointi-ja seurantamenetelmä). Silva Fenn. 21(1):1987;69-94.
24. Skidmore A.K. An expert system classifies eucalypt forest types using Thematic Mapper data and a digital terrain model. Photogram. Eng. Remote Sensing. 55:1989;1449-1464.
25. Pussinen, A., 1992. Ilmakuvat ja LANDSAT TM - satelliittikuva välialueiden kuvioittaisessa arvioinnissa (Aerial photos and LANDSAT TM - image in compartmentwise survey). University of Joensuu, Faculty of Forestry. Thesis for the Master of Science in Forestry Degree. pp. 48 (In Finnish).
26. Ståhl, G., 1992. A study on the quality of compartmentwise forest stand data acquired by subjective inventory methods. Dept. of Biometry and Forest Management, Section of Forest Mensuration and Management, Swedish University of Agricultural Sciences, Umeå, Report 24. pp. 5-87. ISSN 0349-2133.
27. St-Onge B.A., Cavayas F. Automated forest structure mapping from high resolution imagery based on directional semivariogram estimates. Remote Sensing Environ. 61:1997;82-95.
28. Strahler A.H. The use of prior probabilities in maximum likelihood classification of remotely sensed data. Remote Sensing Environ. 10:1980;135-163.
29. Tokola, T., 1990. Satelliittikuvan ja VMI-koealatiedon käyttö metsätalousalueen puuston inventoinnissa (The use of satellite image and NFI - sample plots in inventory of forest management area). University of Joensuu, Faculty of Forestry. Thesis for the Lic. of Science in Forestry Degree. pp. 56 (In Finnish).
30. Tokola T., Heikkilä J. A priori site quality information in satellite image based forest inventory. Silva Fenn. 31(1):1997;67-78.
31. Tokola T., Pitkänen J., Partinen S., Muinonen E. Point accuracy of a non-parametric method in estimation of forest characteristics with different satellite materials. Internat. J. Remote Sensing. 17(12):1996;2333-2351.
32. Tomppo, E., 1986. Stand delineation and estimation of stand variates by means of satellite images. In: Remote sensing-aided forest inventory. Proc. seminars organised by SNS, Hyytiälä, Finland, Dec. 10-12, 1986. University of Helsinki, Department of Forest Mensuration and Management, Research Notes No. 19.
33. Tomppo, E., 1988. Standwise forest variate estimation by means of satellite images. University of Helsinki, Department of Forest Mensuration and Management, Research Notes No. 21. pp. 103-111.
34. Tomppo, E., 1992. Multi-source national forest inventory of Finland. Proceedings of Ilvessalo Symposium on National Forest Inventories, Finland 17-21 August 1992. The Finnish Forest Research Institute. Research Papers 444. pp. 52-60.
35. Trotter C.M., Dymond J.R., Coulding C.J. Estimation of timber volume in a coniferous plantation forest using LANDSAT TM. Internat. J. Remote Sensing. 18(10):1997;2209-2223.
36. Varjo, J., 1997. Change Detection and Controlling Forest Information Using Multi-temporal LANDSAT TM Imagery. Acta Forestalia Fennica 258. pp. 64.
37. Walsh S.J. Coniferous tree species mapping using LANDSAT data. Remote Sensing Environ. 9:1980;11-26.
38. Wegmuller U. SAR interferometric signatures of forest. IEEE Trans. Geosci. Remote Sensing. 33(5):1995;1153-1161.