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Rozpoznanie form pokrycia i użytkowania ziemi na zdjęciu satelitarnym Landsat ETM+ metodą klasyfikacji obiektowej

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EN
Identification of land cover and land use forms on landsat ETM+ satellite image using the method of object-oriented classification
Języki publikacji
PL
Abstrakty
EN
The results of object-oriented classification based on multispectral and panchromatic Landsat ETM+ data, conducted with the use of eCognition software, are presented in the paper. The classification image was prepared using an algorithm aimed at obtaining a database similar to the one resulting from traditional visual interpretation. After the classification, generalisation of data was performed using a working unit of 1 ha for built-up areas and 4 ha for the remaining classes. Next, raster to vector conversion was performed and the edges of objects delineations were smoothed. Verification using a method of visual interpretation was the last stage of works. After combining the verification results with the classification, the final database was obtained. The applied methods of classification enabled identification of 18 land cover and land use classes, at least four of which cannot be identified using traditional methods. The obtained total accuracy of classification reached 94%. The principles of segmentation of the Landsat ETM+ image based on the panchromatic channel and fused multispectral and panchromatic data are specified in the paper. Fusion was based on PanSharp algorithm within PCI Geomatica software, which preserves spectral characteristics of the original data. The adopted principles of land use and land cover classes were also described. What is particularly worth attention is the method of identification of four built-up land classes, which were extracted from the general class of built-up areas classified using the nearest neighbour method. This task involved use of a parameter defined as a square root of the sum of squares of differences between spectral values of particular channels, while the classification of shadows of buildings was used for identification of built-up areas with apartment blocks. The presented method of classification and processing of the obtained results can support or, in certain cases, entirely replace traditional visual interpretation of satellite images, aimed at creating a land cover and land use database.
Czasopismo
Rocznik
Strony
139--150
Opis fizyczny
Bibliogr. 16 poz.
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autor
Bibliografia
  • 1. Baatz M., Banz U., Dehghani S., Heynen M., Holtje A., Hofmann P., Lingenfelder I., Mimler M., Sohlbach M., Weber M., Willhauck G., 2001: eCognition user guide. Definiens Imaging GmbH.
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  • 3. GMES 2004: Global monitoring for environment and security, final report for the GMES initial period (2001-2003).
  • 4. GMES 2006: GMES Fast Track Service Precursor (FTSP) on European land monitoring, FTSP technical implementation . discussion paper, ver l1.4, 23.06.2006.
  • 5. Heymann Y., Steenmans C., Croisille G., Bossard M., 1993: CORINE land cover technical guide. European Commission, EUR 12585.
  • 6. De Kok R., Buck A., Schneider T., Ammer U., 2000a: Analysis of image objects from VHR imagery for forest GIS updating in the Bavarian Alps. Procc. ISPRS Amsterdam, July 2000, Working Group III/5.
  • 7. De Kok R., Buck A., Schneider T., Ammer U., Baatz M., 2000b: Data fusion with Landsat 7 imagery. STROBL, J. et al. (Hrsg), Angewandte Geographische Informationsverarbeitung XII, Beitrage zum AGITSymposium Salzburg 1999, Karlsruhe, Herbert Wichmann Verlag, pp.90-97.
  • 8. Lewiński S., 2000: The satellite maps of Poland elaborated on the basis of Landsat MSS, TM and IRS-1C images. Proceedings of 28 th International Symposium on Remote Sensing of Environment, Cape Town, RPA,27-30 March 2000.
  • 9. Lewiński S., Zagajewski B., 2002: The map of the Narew River National Park on the scale of 1:25000 elaborated on the basis of the merger of the satellite and aerial imagery. Miscellanea Geographica vol. 10, s. 307-318, Warszawa.
  • 10. Lewiński S., Poławski Z.F., 2005: The comparison of interpretation possibility of RGB composite of LISS-III and ETM+ scanner. Proceedings of the 24th Symposium of European Association of Remote Sensing Laboratories, Dubrovnik, Croatia.
  • 11. Lewiński S., 2005: Klasyfikacja obiektowa narzędziem wspomagającym process interpretacji zdjęć satelitarnych. Polskie Towarzystwo Informacji Przestrzennej, Roczniki Geomatyki, t. III, z. 2, s. 97-106. Warszawa.
  • 12. Lewiński S., 2006: Land use classification of ASTER image . Legionowo test site. Proc. of the 25th Symposium of the European Association of Remote Sensing Laboratories, Porto, Portugal, 6-9 June 2005. Global Developments in Environmental Earth Observation from Space.
  • 13. Nunes de Lima M.V., 2005: CORINE Land Cover updating for the year 2000. IMAGE2000 and CLC2000, products and methods. JRC-IES.
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  • 15. Zhang Y., 1999: A new merging method and its spectral and spatial effects. International Journal of Remote Sensing, vol. 20, No. 10, pp. 2003-2014.
  • 16. Zhang Y., 2002. Problems in the fusion of commercial high-resolution satellite images as well as Landsat 7 images and initial solutions. International Archives of Photogrammetry and Remote Sensing (IAPRS), vol. 34, part 4.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPW7-0008-0044
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