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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-507fde05-7e7c-4bad-9354-a4c7cebe6eeb

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Teledetekcja Środowiska

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Zmienność przestrzenna NDVI i wskaźników tekstury Zaborskiego Parku Krajobrazowego w zależności od gospodarczego oddziaływania człowieka

Autorzy Kunz, M.  Nienartowicz, A. 
Treść / Zawartość
Warianty tytułu
EN Spatial variability of NDVI and texture indices for the Zaborski Landscape Park in the gradient of economic influence of man
Języki publikacji PL
Abstrakty
EN The landscape structure can be analysed in different ways while using different methods, research tools and initial data. One of the effective research methods is remote sensing together with satellite imageries obtained by this method. This technology used to be successfully applied in ecology, e.g. for evaluation of forest landscape structure modifi ed by economic activity of man. In the studies carried out by remote sensing methods, it was found that the current landscape structure results from its previous states and is shaped both by man and by natural processes. Having the above statements as a starting point, an analysis of forest landscape structure was performed in the territory of the Zaborski Landscape Park, based on Landsat satellite imageries from the period 1975-2003. The NDVI was calculated for the entire park as well as for three research plots situated within the park. Squares were set up as research plots, with a side of 5040 m long. Each square encompassed 28 224 pixels of dimensions 30 x 30 m. The squares were set up in areas of different intensity of forestry and different share of secondary forests on formerly arable soils. On the basis of generated images presenting the spatial diversifi cation of NDVI, the following texture parameters were defi ned for each research plot: diversity (H), fragmentation (F), fractal dimension (FD). In calculations of the diversity index and fragmentation, the size of the matrix window amounted to 5x5 pixels. The fractal dimension was calculated with the triangular prism method described by Altobelli et al. (2001). The NDVI was also calculated for three sets, each comprising 24 or 25 test areas distributed within each research plot. Test areas were squares with a side of 300x300 metre long representing all age classes of tree stands in the habitat of fresh and dry pine forest. The completed database on subdivisions of the surface area division as well as the course of the process of deforestation and afforestation of the region during the period 1796-2003, allowed the detailed analysis of the obtained results with reference to land use history in this area. In the comparative analysis of three research plots on the basis of structure indices, the graphic method of Jentys-Szaferowa (1948) was applied and methods of numerical taxonomy. On the basis of the performed analyses, it was concluded that together with the increased human pressure on the nature, the average value of NDVI decreased together with the simultaneous increase of indices expressing the diversity, fragmentation and fractal dimension of the landscape.
Słowa kluczowe
PL zmienność przestrzenna   tekstura   wskaźniki   park krajobrazowy   działalność człowieka  
EN spatial variability   texture   indices   landscape park   human activity  
Wydawca Polskie Towarzystwo Geograficzne, Oddział Teledetekcji i Geoinformatyki
Czasopismo Teledetekcja Środowiska
Rocznik 2007
Tom T. 37
Strony 51--60
Opis fizyczny Bibliogr. 17 poz., rys., tab., wykr.
Twórcy
autor Kunz, M.
  • Zakład Kartografii, Teledetekcji i GIS Instytutu Geografii Uniwersytetu Mikołaja Kopernika w Toruniu, met@umk.pl
autor Nienartowicz, A.
  • Pracownia Modelowania Procesów Ekologicznych, Instytut Ekologii i Ochrony Środowiska Uniwersytetu Mikołaja Kopernika w Toruniu, anienart@umk.pl
Bibliografia
Altobelli A., Feoli E., Ourabia L., 2001, An overview of landscape structure through the application of fractal dimension to remotely sensed images using GIS technology, [In:] Nienartowicz A., M. Kunz (eds.) GIS and remote sensing in studies of landscape structure and functioning, pp. 39-50, Nicolaus Copernicus University Press, Toruń.
Barcikowski A. 1992, Differentiation in the structure and energy fl ow in phytocenoses with primary and secondary succession, [In:] Bohr R., Nienartowicz A., Wilkoń-Michalska J. (eds.), Some ecological processes of biological systems in North Poland, pp. 35-58, Nicolaus Copernicus University Press, Toruń.
Boiński M., 1992, Osobliwości szaty roślinnej Borów Tucholskich, Tow. Miłośników Borów Tucholskich, Toruń.
Clarke K.C., 1986. Computation of the Fractal Dimension of Topographic Surface using the Triangular Prism Surface Area Methods, Computer and Geosciences, 12: 713-722.
Franklin J.F., Forman R.T.T., 1987, Creating landscape pattern by forest cutting: Ecological consequences and principles, Landscape Ecology 1: 5-18.
Jagii S., Quattrochi D.A., Lam N.S.N., 1993. Implementation and operation of three fractal measurement algorithms for analysis of remote sensing data. Computer and Geosciences, 19: 745-767.
Jentys-Szaferowa J., 1948, Grafi czna metoda porównywania kształtów roślinnych, Kosmos 66: 349-357.
De Jong S.M., Burrough P.A., 1995, A fractal approach to the classifi cation of Mediterranean vegetation types in remotely sensed images, Photogrammetric Engineering & Remote Sensing 61 (8): 1041-1053.
Kovach W. L., 1993, MVSP – A Multi Variate Statistical Package for IBM PC’s, version 2.1, Kovach Computing Services, Pentraeth, Wales, UK.
Kunz M., 1999, System Informacji Geograficznej (GIS) Zaborskiego Parku Krajobrazowego, [W:] Barcikowski A., Boinski M., Nienartowicz A. (red.), Wielofunkcyjna rola lasu. Ochrona Przyrody-Gospodarka-Edukacja, Wyd. UMK, Toruń.
Kunz M., Nienartowicz A., Deptuła M., 2000, The use of satellite remote sensing imagery for detection of secondary forests on post-agricultural soils: A case study of Tuchola Forest, northern Poland, [In:] Casanova L. (ed.), Remote Sensing in the 21st Century: Economic and Environmental Applications, pp. 61-66, A.A. Balkema/Rotterdam/Brookfi eld.
Lam M.S.N., 1990, Description and measurement of Landsat TM images using fractals, Photogrammetric Engineering & Remote Sensing 56 (2): 187-195.
Monmonier M.S., 1974, Measures of pattern complexity for choropleth maps, The American Cartographer 1(1): 159-169.
Murphy D.L., 1985, Estimating neighborhood variability with a binary comparison matrix, Photogrammetric Engineering & Remote Sensing 51(6): 667-674.
Olsen E.R., Ramsey R.D., Winn D.S., 1993, A modifi ed fractal dimension as a measure of landscape diversity, Photogrammetric Engineering & Remote Sensing 59 (10): 1517-1520.
Rouse, J.W., Haas R.H., Schell J.A., Deering D.W., 1973, Monitoring vegetation systems in the great plains with ERTS, ERTS Symposium, NASA SP-351 I: 309-317.
Turner M.G., 1989, Landscape ecology: the effect of pattern on process, Annales Reviews in Ecology and Systematics 20: 171-197.
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