Abstract
Spatial scale is inherent in the definition of landscape heterogeneity and diversity. For example, a landscape may appear heterogeneous at one scale but quite homogeneous at another scale. In assessing the impact of burning and grazing on the Konza Prairie Research Natural Area (a tallgrass prairie), spatial scale is extremely important. Textural contrast algorithms were applied to various scales of remote sensing data and related to landscape units for assessment of heterogeneity under a variety of burning treatments. Acquired data sets included Landsat multispectral scanner (MSS), with 80 m resolution, Landsat thematic mapper (TM), with 30 m resolution, and high resolution density sliced aerial photography (with a 5 m resolution). Results suggest that heterogeneous areas of dense patchiness (e.g., unburned areas) must be analyzed at a finer scale than more homogeneous areas which are burned at least every four years.
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References
Abrams, M.D., Knapp, A.K. and Hulbert, L.C. 1986. A ten-year record of aboveground biomass in a Kansas tallgrass prairie: Effects of fire and topographic position. Am. J. Bot. 73: 1509–1515.
Bragg, T.B. and Hulbert, L.C. 1976. Woody plant invasion of unburned Kansas bluestem prairie. J. Range Man. 29: 19–24.
Colwell, R. (ed.) 1983. Manual of remote sensing, Vol. I & II American Society of Photogrammetry and Remote Sensing: Falls Church, VA.
Frank, T.D. 1984. The effect of change in vegetation cover and erosion patterns on albedo and texture of Landsat Images in semiarid environments. Ann. Ass. Am. Geogr. 74: 393–407.
Haralick, R. and Shanmugan, K. 1974. Combined spectral and spatial processing of ERTS imagery data. Rem. Sens. Environ. 3: 3–13.
Haralick, R. 1979. Statistical and structural approaches to texture. Proceedings, Institute of Electrical and Electronics Engineers 67: 786–804.
Haralick, R., Shanmugan, K. and Dinstein, I. 1983. Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics. SMC-3: 610–621.
Hsu, S. 1978. Texture-tone analysis for automated land-use mapping. Photogr. Engin. Rem. Sens. 44: 1393–1404.
Jensen, J.R. 1983. Biophysical remote sensing. Ann. Ass. Am. Geogr. 73: 111–132.
Jensen, J.R. 1986. Introductory digital image processing. Prentice-Hall: Englewood Cliffs, N.J.
Knapp, A.K. and Seastedt, T.R. 1986. Detritus accumulation limits productivity of tallgrass prairie. BioScience 36: 662–668.
Reichman, O. 1987. Konza prairie: A tallgrass natural history. University Press of Kansas, Lawrence.
Schowengerdt, R. 1983. Techniques for image processing and classification and remote sensing. Academic Press, New York.
Shih, E. and Schowengerdt, R. 1983. Classification of arid geomorphic surfaces using Landsat spectral and textural features. Photogr. Engin. Remote Sens. 49: 337–347.
Tucker, C. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8: 127–150.
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Nellis, M.D., Briggs, J.M. The effect of spatial scale on Konza landscape classification using textural analysis. Landscape Ecol 2, 93–100 (1989). https://doi.org/10.1007/BF00137153
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DOI: https://doi.org/10.1007/BF00137153