Abstract
Problems in the earth sciences are often spatial in nature, and many involve images either on a macroscopic scale (e.g., satellite imagery) or on a microscopic scale (e.g., electron micrographs). Many of the methods applied to such problems are either explicitly statistical (e.g., kriging) or can be interpreted in terms of spatial statistics. There is no doubt about the importance of the topic today or in the foreseeable future.
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References
Chauvet, P., 1982: The variogram cloud, 17th APCOM Symposium Colorado School of Mines, Golden, Colorado.
Cliff, A.D. and J.K. Ord, 1973: Spatial Autocorrelation, Pion, London.
Cook, D.G. and S.J. Pocock, 1983: Multiple regression in geographical mortality studies with allowance for sptailly correlated errors, Biometrics, 39 p.
Mardia, K.V. and R.J. Marshall, 1984: Maximum likelihood estimation of models for residual covariance in spatial regression, Biometrika, 71 p.
Switzer, P., 1984: Inference for spatial autocorrelation functions, in Geostatistics for Natural Resoruces Characterization, G. Verly, et al., editors, Reidel, Dordrecht, Holland.
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© 1988 D. Reidel Publishing Company, Dordrecht, Holland
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Ripley, B.D. et al. (1988). Workshop on Spatial Statistics and Image Processing. In: Chung, C.F., Fabbri, A.G., Sinding-Larsen, R. (eds) Quantitative Analysis of Mineral and Energy Resources. NATO ASI Series, vol 223. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-4029-1_43
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DOI: https://doi.org/10.1007/978-94-009-4029-1_43
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-8288-4
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