Abstract
Digital images contain so much information that it is difficult to identify and interpret spatial structures that they might contain. We have investigated kriging analysis to reveal structure in imagery and to estimate its spatial scales separately. We applied the analysis to part of a SPOT image of a dissected landscape in the south eastern United States. Variograms for the three wavebands in the imagery and the normalized difference vegetation index (NDVI) showed variation on two distinct spatial scales, which we modelled with a nested (double) exponential function, with effective ranges of 140 to 300 m and 2340 to 3400 m. By kriging analysis we estimated the separate contributions of the short- and long-range spatial components. The maps of the short-range components seem to represent a patchiness in the ground cover, whereas the long-range component seems to Refslect the coarser pattern imposed by the gross physiography. The paper is illustrated with the results of analysing the NDVI.
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Gaili, A., Gerdil-Neuillet, F. and Dadou, C. (1984) Factorial kriging analysis: a substitute to spectral analysis of magnetic data. In: G. Verly, M. David, A. Journel and A. Marechal (eds), Geostatistics for Natural Resources Characterization, D. Reidel, Dordrecht, pp. 543–557.
Goovaerts, P. and Webster, R. (1994) Scale-dependent correlation between topsoil copper and cobalt concentrations in Scotland. European Journal of Soil Science, 45, 79–95.
Jaquet, O. (1989) Factorial kriging analysis applied to geological data from petroleum exploration. Mathematical Geology, 21, 683–691.
Matheron, G. (1982) Pour une analyse krigeante de données régionalisées. Note N-732, Centre de Géostatistique, Ecole des Mines de Paris, Fontainebleau.
Van Der Meer, F. (1993) Classification of high spectral resolution imagery using an indicator kriging based technique. In: A. Soares (ed.), Geostatistics Troia ‘92, Volume 2, Kluwer Academic Publishers, Dordrecht, pp. 829–840.
Webster, R., Curran, P. J. and Munden, J. W. (1989) Spatial correlation in Refslected radiation from the ground and its implications for sampling and mapping by ground-based radiometry. Remote Sensing of Environment, 29, 67–78.
Wen, R. and Sinding-Larsen, R. (1997) Image filtering by factorial kriging— sensitivity analysis and application to Gloria side-scan sonar images. Mathematical Geology, 29, 433–468.
Woodcock, C. E., Strahler, A. H. and Jupp, D. L. B. (1988) The use of variograms in remote sensing II. Real digital images. Remote Sensing of Environment, 25, 349–379.
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© 1999 Springer Science+Business Media Dordrecht
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Oliver, M.A., Webster, R., Slocum, K. (1999). Image Filtering by Kriging Analysis. In: Gómez-Hernández, J., Soares, A., Froidevaux, R. (eds) geoENV II — Geostatistics for Environmental Applications. Quantitative Geology and Geostatistics, vol 10. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9297-0_46
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DOI: https://doi.org/10.1007/978-94-015-9297-0_46
Publisher Name: Springer, Dordrecht
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