The modifiable areal unit phenomenon: an investigation into the scale effect using UK census data

Geography--Statistical methods;Spatial analysis (Statistics);Geography--Methodology

Manley, D. J. (David John) ; Flowerdew, Robin ; Flowerdew, Robin

University:University of St Andrews

Department:Earth & Environmental Sciences and Geography & Sustainable Development (Schools of)

关键词: Geography--Statistical methods;    Spatial analysis (Statistics);    Geography--Methodology;   

Others  :  https://research-repository.st-andrews.ac.uk/bitstream/handle/10023/465/Manley_phd_thesis.pdf?sequence=6&isAllowed=y

来源: DR-NTU

【 摘 要 】

The Modifiable Areal Unit Phenomenon (MAUP) has traditionally been regarded as a problem in the analysis of spatial data organised in areal units. However, the approach adopted here is that the MAUP provides an opportunity to gain information about the data under investigation. Crucially, attempts to remove the MAUP from spatial data are regarded as an attempt to remove the geography. Therefore, the work seeks to provide an insight to the causes of, and information behind, the MAUP. The data used is from the 1991 Census of Great Britain. This was chosen over 2001 data due to the availability of individual level data. These data are of key importance to the methods employed. The methods seek to provide evidence of the magnitude of the MAUP, and more specifically the scale effect in the GB Census. This evidence is built on using correlation analysis to demonstrate the statistical significance of the MAUP. Having established the relevance of the MAUP in the context of current geographical research, the factors that contribute to the incidence of the MAUP are considered, and it is noted that a wide range of influences are important. These include the population size and density of an area, along with proportion of a variable. This discussion also recognises the importance of homogeneity as an influential factor, something that is referenced throughout the work. Finally, a search is made for spatial processes. This uses spatial autocorrelation and multilevel modelling to investigate the impact spatial processes have in a range of SAR Districts, like Glasgow, Reigate and Huntingdonshire, on the scale effect. The research is brought together, not to solve the MAUP but to provide an insight into the factors that cause the MAUP, and demonstrate the usefulness of the MAUP as a concept rather than a problem.