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Zastosowanie klasyfikacji obiektowej wysokorozdzielczych obrazów teledetekcyjnych oraz analiz przestrzennych GIS w kartowaniu drzewostanów

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
EN
Application of object oriented classification of quickbird vhr satellite images and GIS spatial analysis in forest stand mapping
Języki publikacji
PL
Abstrakty
EN
Single crown detection in forest stands based on VHR imagery has been the subject of research for over a decade. Recent progress in crown detection shows how hotspots can be isolated from tree crowns. The spatial distribution of hotspots is related to tree species, stand development and clown density. Due to high resolution (spectral & spatial) of the QuickBird data set, insight into the relationship between crown-hotspots, tree age and crown density - can be analyzed in more detail. The data fusion of spatial information obtained by forest inventory, GPS measurements and the relation between SILP attribute and geometrical database (digital forest map . LMN) allows to build up the connection to the spectral signature registered by the satellite imagery. Estimation of crown diameter based on the hotspots from Quickbird data, as well as the spatial distribution of the total crown area is the main goal of this study. Various concepts (Thyssen polygon, irregular triangulation etc) open diverse modeling possibilities. In this study, a selection of available models is applied to the point set of crownhotspots. For this purpose, Quickbird image (15.09.2003) of a part of the Niepolomice Forest (south Poland) was used. Crown distribution and development of stands are related to the age and height of trees. The cross validation between different measurements clarify the potential of VHR data to achieve a reliable level of crown density estimation. This allows extrapolating the model over the whole forest area. For the forest management, stand age, species and height are the attributes incorporated in the SILP database (Polish State Forest). However, for the evaluation of successful growth per stand, crown density estimations are crucial and can change abruptly in a few growing seasons due to calamities. Only remote sensing methods and geoinformation techniques can assure low-cost and quick data collection over large forest areas and they are crucial when the needed information is reliable enough to provide decision support.
Czasopismo
Rocznik
Strony
99--108
Opis fizyczny
Bibliogr. 29 poz.
Twórcy
autor
  • Laboratorium GIS i Teledetekcji, Katedra Ekologii Lasu, Wydział Leśny Akademia Rolnicza w Krakowie
autor
  • Laboratorium GIS i Teledetekcji, Katedra Ekologii Lasu, Wydział Leśny Akademia Rolnicza w Krakowie
autor
  • Laboratorium GIS i Teledetekcji, Katedra Ekologii Lasu, Wydział Leśny Akademia Rolnicza w Krakowie
Bibliografia
  • 1. Bednarczyk P., 2005: Ocena przydatno.ci wysokorozdzielczych zobrazowań satelitarnych QuickBird w zasilaniu atrybutowych i geometrycznych baz danych na przykładzie Nadleśnictwa Niepołomice. Praca magisterka wykonana w Laboratorium GIS i Teledetekcji, KEL, WL Akademia Rolnicza w Krakowie, maszynopis.
  • 2. Blaschke T., Hay G. J., 2001: Object-oriented image analysis and scale-space: theory and methods for modeling and evaluating multiscale landscape structure. Int. Archives Photogrammetry and Remote Sens., 34, part 4/W5, ss. 22-29.
  • 3. Brandtberg, T., Warner T.A., Landerberger R.E., McGraw J.B., 2003: Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America. Remote Sensing of Environment, 85 (3), ss. 290-303.
  • 4. Burnett C., Blaschke T., 2003: A multi-scale segmentation/object relationship modeling methodology for landscape analysis. Ecological Modelling, Vol. 168, Issue 3, ss. 233-249.
  • 5. Cormen T. H., Leiserson C. E., Rivest R., 2004: Wprowadzenie do algorytmów. Wydawnictwa Naukowo-Techniczne. Warszawa.
  • 6. de Kok R., Kozioł K., Wężyk P., Zajączkowski G., 2004: Modeling tree crown density based on Quickbird data. Book of Abstarcts. GGRS2004. 1st Goettingen GIS & Remote Sensing Days. Environmental Studies.
  • 7. de Kok R., 2004: Object oriented analysis of spatial structural dynamics. Presentation on the eCognition User Meeting, Munich.
  • 8. Diedershagen O., Koch B., Weinacker H., Schutt C., 2003: Combining Lidar and GIS data for the extraction of forest inventory parameters. In: ScandLaser Scientific Workshop on Airborne Laser Scanning of Forests. Umel, Sweden. Swedish University of Agricultural Sciences, Department of Forest Resource Management and Geomatics.Working paper 112. 273 p.
  • 9. Franklin S.E., Wulder M., Gerylo G.R., 2001: Texture analysis of IKONOS panchromatic data for Douglasfir forest age class separability in British Columbia. Int. Journal of Remote Sensing, 22(13), ss. 2627-2632.
  • 10. Gougeon F.A., 1998: Automatic individual tree crown delineation using a valley-following algorithm and a rule-based system. IEEE Transactions on Geoscience and Remote Sensing, 30(2), ss. 276-292.
  • 11. Gougeon F.A., 2000: Towards semi-automatic forest inventories using individual tree crown (ITC) recognition. Technology Transfer Note. Forestry Research Applications. Pacific Forestry Centre. No 22, ss. 6.
  • 12. Gougeon F.A., St-Onge B., Wulder M., Leckie D.G., 2001: Synergy of airborne laser altimetry and digital videography for individual tree crown delineation. Proc. 23rd Canadian Symp. on Rem. Sens., Sainte-Foy, ss. 7.
  • 13. Haralick R.M., Shapiro L.G. 1985: Survey: Image Segmentation Techniques. Computer Vision, Graphics, and Image Processing 29 (1): 100-132.
  • 14. Hyyppä H., Samberg A., 1999: Assessing Forest Stand Attributes by Laser Scanner. Laser Radar Technology and Applications IV, 3707: 57-69.
  • 15. Hyyppä J., Hyyppä H., Litkey P., Yu X., Haggren H., Rönnholm P., Pyysalo U., Pitkänen J., Maltamo M., 2004: Algorithms and methods of airborne laserscanning for forest measurements. [In:] International Archives of Photogrammetry nad Remote Sensing, XXXVI-8/W2, 82-89, Freiburg.
  • 16. Leckie D.G., Gougeon F.A., 1998: An assessment of both visual and automated tree counting and species identification with high spatial resolution multispectral imagery. Automatic Interpretation of High Spatial Resolution Digital Imagery for Forestry, Victoria, ss. 141-152.
  • 17. Mozgawa J., Choromański A., Zawiła-Nied.wiedzki T., 2001: Potencjalne i praktyczne możliwo.ci wykorzystania teledetekcji w Lasach Państwowych. Mat. I Kraj. Konf. .SIP w LP., Rogów, ss. 21.
  • 18. Prewitt J. M. S., 1970. Object Enhancement and Extraction. In Picture Processing and Psychopictorics. Ed. B. S. Lipkin and A. Resenfeld. New York: Academic Press.
  • 19. Pitkänen J., 2001: Individual tree detection in digital aerial images by combining locally adaptive binarization and local maxima methods. Canadian Journal of Forest Research 31: 832-844.
  • 20. Popescu S.C., Wynne R.H., Nelson R.F., 2003: Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass. Canadian Journal of Remote Sensing, 25(5), ss. 564-577.
  • 21. Pouliot D.A., King D.J., Bell F.W., Pitt D.G., 2002: Automated tree crown detection and delineation in highresolution digital camera imagery of coniferous forest regeneration. Remote Sensing of Environment, 82, ss. 322-334.
  • 22. Sasakawa H., Tsuyuki S. 2003: Development of forest type classification technique for the mixed forest with coniferous and broad-leaved species using the high resolution satellite data; http://definiens-imaging.com/ documents/reference2003.htm
  • 23. Solberg R., Wężyk P., 2000: Forest Environmental Monitoring and Management System .FOREMMS. .contribution to the development of sustainable use of natural resources. In: Application of Remote Sensing in Forestry, Zvolen, Slovakia
  • 24. Toutin T., Cheng P., 2002: QuickBird . A Milestone for High Resolution Mapping. Earth Observation Magazine, vol. 11, no. 4, ss. 14-18.
  • 25. Wang L. Gong P., Biging G.S., 2004: Automated individual tree crown delineationand treetop detection in highspatial resolution aerial imagery. Photogrammetric Engineering & Remote Sensing, 70 (3), ss. 351-358.
  • 26. Wężyk P., 2004: Integracja technologii geoinformatycznych w systemie monitoringu i zarządzania ekosystemami le.nym Europy, na przykładzie projektu FOREMMS (V PR UE). Teledetekcja .rodowiska. Tom 33, s.75-81.
  • 27. Wężyk P., de Kok R., 2005: Automatic mapping of the dynamics of forest succession on abandoned parcels in south Poland. In: Strobl et al. Hrsg. Angewandte Geoinformatik 2005. Wichman Verlag, Heidelberg, ss. 774-779
  • 28. Wężyk P., de Kok R., Zajączkowski G., 2004: The role of statistical and structural texture analysis in VHR image analysis for forest applications. A case study on Quickbird data in the Niepolomice Forest. Angewandte Geoinformatik. Herbert Wichmann Verlag. Heidelberg. ss. 770-775.
  • 29. Zajączkowski G., Wężyk P., 2004: Techniki teledetekcyjne w inwentaryzacji urządzeniowej lasu. Roczniki Geomatyki, Tom II, Zeszyt 4, ss. 41-50.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPW9-0005-0071
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