Clas-Göran Persson

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Andrej Dujella

University of Zagreb

Hemin Koyi

Uppsala University

Jana Javornik

University of East London

Armando Marques-Guedes

UNL - New University of Lisbon

Graham Martin

University of Leicester

Gwen Robbins Schug

University of North Carolina at Greensboro

Gabriel Gutierrez-Alonso

University of Salamanca

John Sutton

Macquarie University

Eros Carvalho

Universidade Federal do Rio Grande do Sul

Kevin Arbuckle

Swansea University

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Papers by Clas-Göran Persson

Uncertainty in area determination

This report gives a thorough description of the determination of two-dimensional areas and the es... more This report gives a thorough description of the determination of two-dimensional areas and the estimation of area uncertainty. Considering the formulas for area determination, the basis is regular shapes, e.g. triangles, squares, rectangles, rhombi and regular (closed) polygons. The given formulas are valid as such; however, they also indicate how they can be simplified. The report presents strict as well as approximate formulas for area uncertainty estimates. The approach is mainly from a statistical point of view. However, there are some geometric factors/ variations which have an influence on the size of the area. They are dealt with by mathematical means. In addition, less mathematical, more argument-based (philosophical) descriptions of other "areal defects", having an influence on the area uncertainty, are presented. Examples of these defects are given to illustrate their impact on uncertainty estimation. The report is mainly an English translation of an earlier Swedish report [1]. Therefore, some minor parts refer to Swedish conditionse.g. regarding coordinate systems, map projections etc.

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The effect of correlation on uncertainty estimates – with GPS examples

Journal of Geodetic Science, 2013

This article deals with the effect of correlation on the estimates of measurement uncertainty, wi... more This article deals with the effect of correlation on the estimates of measurement uncertainty, with some focus on Global Positioning Satellite (GPS) time series analysis. Analytical derivations and Monte Carlo simulations form the theoretical basis, which shows that uncompensated correlation produces unrealistic uncertainty estimates. Tools for handling correlation in connection with estimation of uncertainty, construction of confidence intervals, hypothesis testing, design of measurement strategies, and development of tolerances are outlined and demonstrated. The GPS observation time series used in the article has a short to medium range correlation, and can therefore be handled with the presented tools - based on a simple Location-model and stationary stochastic processes.

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