Maximum Autocorrelation Factorial Kriging

Allan Aasbjerg Nielsen; Knut Conradsen; John L. Pedersen; Agnete Steenfelt; W.J. Kleingeld; D.G. Krige

Maximum Autocorrelation Factorial Kriging

Allan Aasbjerg Nielsen, Knut Conradsen, John L. Pedersen, Agnete Steenfelt, W.J. Kleingeld (Editor), D.G. Krige (Editor)

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

This paper describes maximum autocorrelation factor (MAF) analysis, maximum autocorrelation factorial kriging, and its application to irregularly sampled stream sediment geochemical data from South Greenland. Kriged MAF images are compared with kriged images of varimax rotated factors from an ordinary non-spatial factor analysis, and they are interpreted in a geological context. It is demonstrated that MAF analysis contrary to ordinary non-spatial factor analysis gives an objective discrimination of largescale as well as small-scale geological features which are related to crustal structure and the occurrence of specific rock types.

Original language	English
Title of host publication	Proceedings of the 6th International Geostatistics Congress, Geostats 2000
Publication date	2000
Pages	538-547
Publication status	Published - 2000
Event	Proceedings of the 6th International Geostatistics Congress, Geostats 2000 - Duration: 1 Jan 2000 → …

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Conference	Proceedings of the 6th International Geostatistics Congress, Geostats 2000
Period	01/01/2000 → …

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@inproceedings{e26a976465b540ba95731e1297915e7b,

title = "Maximum Autocorrelation Factorial Kriging",

abstract = "This paper describes maximum autocorrelation factor (MAF) analysis, maximum autocorrelation factorial kriging, and its application to irregularly sampled stream sediment geochemical data from South Greenland. Kriged MAF images are compared with kriged images of varimax rotated factors from an ordinary non-spatial factor analysis, and they are interpreted in a geological context. It is demonstrated that MAF analysis contrary to ordinary non-spatial factor analysis gives an objective discrimination of largescale as well as small-scale geological features which are related to crustal structure and the occurrence of specific rock types.",

author = "Nielsen, {Allan Aasbjerg} and Knut Conradsen and Pedersen, {John L.} and Agnete Steenfelt and W.J. Kleingeld and D.G. Krige",

year = "2000",

language = "English",

pages = "538--547",

booktitle = "Proceedings of the 6th International Geostatistics Congress, Geostats 2000",

note = "Proceedings of the 6th International Geostatistics Congress, Geostats 2000 ; Conference date: 01-01-2000",

}

Maximum Autocorrelation Factorial Kriging. / Nielsen, Allan Aasbjerg ; Conradsen, Knut; Pedersen, John L.; Steenfelt, Agnete; Kleingeld, W.J. (Editor); Krige, D.G. (Editor).

Proceedings of the 6th International Geostatistics Congress, Geostats 2000. 2000. p. 538-547.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Maximum Autocorrelation Factorial Kriging

AU - Nielsen, Allan Aasbjerg

AU - Conradsen, Knut

AU - Pedersen, John L.

AU - Steenfelt, Agnete

A2 - Kleingeld, W.J.

A2 - Krige, D.G.

PY - 2000

Y1 - 2000

N2 - This paper describes maximum autocorrelation factor (MAF) analysis, maximum autocorrelation factorial kriging, and its application to irregularly sampled stream sediment geochemical data from South Greenland. Kriged MAF images are compared with kriged images of varimax rotated factors from an ordinary non-spatial factor analysis, and they are interpreted in a geological context. It is demonstrated that MAF analysis contrary to ordinary non-spatial factor analysis gives an objective discrimination of largescale as well as small-scale geological features which are related to crustal structure and the occurrence of specific rock types.

AB - This paper describes maximum autocorrelation factor (MAF) analysis, maximum autocorrelation factorial kriging, and its application to irregularly sampled stream sediment geochemical data from South Greenland. Kriged MAF images are compared with kriged images of varimax rotated factors from an ordinary non-spatial factor analysis, and they are interpreted in a geological context. It is demonstrated that MAF analysis contrary to ordinary non-spatial factor analysis gives an objective discrimination of largescale as well as small-scale geological features which are related to crustal structure and the occurrence of specific rock types.

M3 - Article in proceedings

SP - 538

EP - 547

BT - Proceedings of the 6th International Geostatistics Congress, Geostats 2000

T2 - Proceedings of the 6th International Geostatistics Congress, Geostats 2000

Y2 - 1 January 2000

ER -

Maximum Autocorrelation Factorial Kriging

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