Title page for ETD etd-10272010-190111


Document Type Master's Dissertation
Author Smit, Ansie
URN etd-10272010-190111
Document Title Interpolation in stationary spatial and spatial-temporal datasets
Degree MSc
Department Statistics
Supervisor
Advisor Name Title
Dr H Boraine Committee Chair
Keywords
  • spatial
  • statistical tool
  • mining sector
  • spatial-temporal
  • datasets
Date 2010-09-02
Availability unrestricted
Abstract

In the early 1950s the study on how to determine true ore-grade distributions in the mining sector, sparked the development of a series of statistical tools that specifically allows for spatial and subsequently spatial-temporal dependence. These statistics are commonly referred to as geostatistics, and has since been incorporated in several fields of study characterized by this dependence.

Basic descriptive statistics and mapping tools for geostatistics are defined and illustrated by means of a simulated dataset. The moments are modelled according to predefined conditions and model structures to describe the spatial and spatial-temporal variance in the data. These variograms and covariance structures are subsequently utilized in the least square procedure, namely kriging. At present, kriging is most commonly used in geostatistics for the interpolation and simulation of spatial or spatial-temporal data. The univariate and multivariate spatial and spatial-temporal kriging techniques are tested on the simulated dataset, to demonstrate how interpolation weights are determined according to the lag distances and underlying variance structure. The strength, weaknesses and inherent complexities of the methodologies are highlighted.

2010, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.

Please cite as follows:

Smit, A 2010, Interpolation in stationary spatial and spatial-temporal datasets, MSc dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-10272010-190111/ >

E10/741/gm

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