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2004 | nr 3 | 15--24
Tytuł artykułu

Modelowanie czasowo-przestrzenne metodami geostatycznymi

Warianty tytułu
Modelling by Geostatistical Methods in Respect of Time and Space
Języki publikacji
Geostatystyka jest działem statystyki, który dostarcza metod opisu ciągłości przestrzennej oraz adaptuje metody regresji klasycznej w celu wykorzystania tej ciągłości. Do podstawowych zagadnień, którymi zajmuje się geostatystyka należy interpretacja oraz przewidywanie (estymacja, symulacja) rozkładów przestrzennych badanych zjawisk. Celem artykułu jest przedstawienie sposobu wykorzystania metod geostatystycznych do opisu zjawisk czasowo-przestrzennych i omówienie najważniejszych trudności.
There are many random phenomena which are intrinsically spatio-temporal in which relevant role plays both temporal variability and spatial one. These variabilities should be taken into consideration together. Spatio-temporal phenomena are frequent in technology, economy, agriculture, geography, the environmental studies etc. There is urgent need to develop statistical methods for description of such phenomena. The most appropriate for this purpose are geostatistical methods. Geostatistical methods of modelling the spatio-temporal phenomena have been intensively developed and studied for over a dozen years. The main trend in these studies consists in the extension of geostatistical methods designed for spatial analysis into the space-time domain, by adding the temporal dimension. Despite the straightforward simplicity of this extension, the application of these methods for analysing real spatio-temporal phenomena is very difficult. The difficulties arise from different properties of spatial and temporal data. Geostatistical methods of modelling the spatio-temporal phenomena take advantage of kriging methods in which both spatio-temporal variable and the elements of covariance matrix used in cok-riging equations are the functions of time and spatial co-ordinates. The most difficult is modelling of two-dimensional empirical covariances (or equivalent empirical semivari-ances). These models are necessary for calculation elements of the covariance matrix used in kriging equations. The appropriate separation and subsequent independent modelling of temporal and spatial parts of the covariance matrix makes that the modelling of the spatio-temporal changes much easier. The intensive studies are also carried on the development of non-separable models of the spatio-temporal covariance. (original abstract)
Opis fizyczny
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