Brunsdon, Chris and Charlton, Martin (2006) Local trend statistics for directional data—A moving window approach. Computers, Environment and Urban Systems, 30 (2). pp. 130-142. ISSN 0198-9715

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Abstract

The ideas of directional distributions for random data are reviewed, in particular focussing on descriptive directional statistics to summarise these distributions. Consideration is then given to spatial variations in directional distributions; for example how does the directional distribution of wind direction vary across geographical space, and how may this be analysed? To investigate this issue, an approach to moving window-based smoothing of directional data is proposed, based on the application of a geographical kernel-based weighting scheme to find localised mean directions (and related statistics) to directions represented as complex numbers of magnitude one. Consideration is also given to the visualisation of the outputs of an analysis such as this. The paper concludes with two applications of the techniques proposed; an analysis of wind speeds across Europe drawn from NOAA observations, and an analysis of US inter-county net migration counts between 1985 and 1990.

Item Type:	Article
Keywords:	Directional data; Smoothing; Wind speed; Circular statistics;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
Item ID:	5870
Identification Number:	https://doi.org/10.1016/j.compenvurbsys.2005.08.004
Depositing User:	Martin Charlton
Date Deposited:	19 Feb 2015 12:03
Journal or Publication Title:	Computers, Environment and Urban Systems
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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