SPACE TRANSFORMATION-METHODS IN THE REPRESENTATION OF GEOPHYSICAL RANDOM-FIELDS

CHRISTAKOS, G; PANAGOPOULOS, C

dc.contributor.author	CHRISTAKOS, G	en
dc.contributor.author	PANAGOPOULOS, C	en
dc.date.accessioned	2014-03-01T01:41:32Z
dc.date.available	2014-03-01T01:41:32Z
dc.date.issued	1992	en
dc.identifier.issn	0196-2892	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/23519
dc.subject	RANDOM FIELDS	en
dc.subject	SPACE TRANSFORMATIONS	en
dc.subject	SIMULATION	en
dc.subject	GEOSTATISTICS	en
dc.subject	RADON OPERATIONS	en
dc.subject.classification	Geochemistry & Geophysics	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.classification	Remote Sensing	en
dc.subject.other	SIMULATION	en
dc.title	SPACE TRANSFORMATION-METHODS IN THE REPRESENTATION OF GEOPHYSICAL RANDOM-FIELDS	en
heal.type	journalArticle	en
heal.language	English	en
heal.publicationDate	1992	en
heal.abstract	Random fields are frequently used to represent a variety of geophysical processes which develop in space and/or in time. This paper is devoted to the study of various aspects of multidimensional random fields by means of space transformations. The latter are elegant and comprehensive Radon operations which can solve complex multidimensional problems by transforming them to a suitable unidimensional setting, where analysis is considerably simpler. The underlying concept has both substance and depth, and possess attractive properties in the physical and the frequency domains. It is shown that spatial correlation functions in R(n) are uniquely determined by means of their space transformations in Rn. Necessary and sufficient conditions are established in order that a spatial random field (in R(n)) be represented as the linear combination of pairwise uncorrelated random processes (in R1). Space transformations provide analytically tractable criteria for testing the permissibility of correlation functions. Also, they constitute a particularly attractive instrument for spatial and spatiotemporal random field simulation, as well as for studying stochastic partial differential equations. To gain insight into the techniques involved, several examples and a case study are discussed.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING	en
dc.identifier.isi	ISI:A1992HC42200005	en
dc.identifier.volume	30	en
dc.identifier.issue	1	en
dc.identifier.spage	55	en
dc.identifier.epage	70	en