Abstract
As one of the important parts of Digital Terrain Analysis (DTA), spatial correlation analysis of topographic attributes (TAs) is an effective method of analysing the topographical environment. This chapter proposes a spatial correlation model for nine selected TAs, providing an effective method for quantitative DTA research and landform recognition. Forty seven different loess landforms were selected as test areas and their corresponding 5 m grid cell DEM data as test data. With grey correlation analysis, spatial correlations for these TAs were analysed and the TAs’ correlation model built. Furthermore, the variations of the correlation curves are discussed. Results show that (1) TA correlation curves are similar to the spectrum, which provides a means of modelling the natural environment; (2) the correlation curve changes with the topographical area; and (3) the correlation curve reflects the landform and evolution pattern of the sample area.
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References
Zou, B. (1985), Principle of small geomorphology,Beijing: Commercial Press (in Chinese).
Da Silva, J.R.M. and Alexandre, C. (2005), Spatial variability of irrigated corn yield in relation to field topography and soil chemical characteristics, Precision Agriculture, 6: 453–466.
Deng, J. (ed.) (1988), Grey System Book, Windsor: Sci-Tech Information Services.
Garner, M.E. (1998), Effects of anthropogenic activities upon land cover change in Johnson County, Arkansas, PhD thesis, University of Arkansas.
Giles, P.T. and Franklin, S.E. (1998), An automated approach to the classification of the slope units using digital data, Geomorphology, 21: 251–264.
Deng, J. (1987), Basical method of gray system, HuaZhong Technology College Press (in Chinese).
Keck, T.J., Quimby, W.F. and Nielsen, G.A. (1993), Spatial distribution of soil attributes on reconstructed mine soils, Soil Sci. Soc. Am. J.,57: 782–786.
Li, B. and Tao, S. (2000), Correlation between AVHRR NDVI and climate factors, Acta Ecologica Sinica, 5: 898–902.
Shary, P.A. and Sharaya, L.S. (in press), Criteria of TAs selection in predictive soil and vegetation mapping, International Journal of Ecology & Development.
Shary, P.A., Sharaya, L.S. and Mitusov, A.V. (2002), Fundamental quantitative methods of land surface analysis, Geoderma, 107: 1–32.
Luo, S., Sun, X. and Chen, Y. (1988), Research of natural conditions in Loess Plateau, Xi’an: Shaanxi People’s Press (in Chinese).
Liu, S., Guo, T. and Dang, Y. (1999), Theory and application of gray system, Science Press (in Chinese).
Tang, G. and Zhao, M. (2003), Modeling slope uncertainty derived from DEMs in Loess Plateau, Acta Geographica Sinica, 58: 824–830.
Tang, G. (1991), Foundation and application of digital slope model, Journal of Northwest University, 21: 33–41.
Western, A.W., Grayson, R.B. and Bloschl, G. (1999), Observed spatial organization of soil moisture and its relation to terrain indices, Water Research, 35: 797–810.
Wei, Y. (2005), Principle and method of geographical modelling, Science Press (in Chinese).
Yue M. (1998), The relation among ecological factors and diameter growth of platycladus orientalis in the south of Northern ShaanXi Province, Journal of WuHan Botanical Research, 16: 47–53.
Zhao, Y., Long, Y., Zhao, Q. and Luo, Z. (1997), Application of gray system theory in geography, HuaZhong Polytechnic University Press (in Chinese).
Gan, Z. (1990), Research of geomorphology of Loess Plateau and soil erosion, Xi’an: Shaanxi People’s Press (in Chinese).
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Ting, Z., Jun, L., Chun, W., Lei, Z. (2008). Spatial Correlation of Topographic Attributes in Loess Plateau. In: Zhou, Q., Lees, B., Tang, Ga. (eds) Advances in Digital Terrain Analysis. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77800-4_22
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DOI: https://doi.org/10.1007/978-3-540-77800-4_22
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