The British Population retains a strong sense of regional identity, epitomized by periodic campaigns for Scottish and Welsh devolution, or for Cornish self-government. There have been few studies into the regionalization of British surnames and none that utilize any register that can claim to be nationally representative. The National Social Map presented in this paper is the first comprehensive attempt to create a regional geography of Great Britain based upon the clustering of surnames. The resulting map illustrates a strong relationship between the population’s surnames and geographic location. The homogeneity within each of the surname regions identified is striking given that spatial contiguity constraints were not included within the clustering process. The map will hopefully set a bench-mark for future work by geographers in the field of surname research.
Cheshire, J.A., Longley, P.A. and Singleton, A.D. (2010) The Surname Regions of Great Britain, v2010, 401-409. 10.4113/jom.2010.1103
The article can be downloaded here.
I have been asked on two occasions in the past month to present on the topic of my current and future research activity (both methodological and substantive). These draw together my activities over the past seven years at UCL made up of both PhD and Post Doctoral research.
I have uploaded both these talks to slideshare for anyone who is interested:
Shorter Talk: Current and Future Research
Longer Talk: Socio-Spatial Differentiation – People, Places and Interaction
Geodemographic classifications provide discrete indicators of the social, economic and demographic characteristics of people living within small geographic areas. They have hitherto been regarded as products, which are the final “best” outcome that can be achieved using available data and algorithms. However, reduction in computational cost, increased network bandwidths and increasingly accessible spatial data infrastructures have together created the potential for the creation of classifications in near real time within distributed online environments. Yet paramount to the creation of truly real time geodemographic classifications is the ability for software to process and efficiency cluster large multidimensional spatial databases within a timescale that is consistent with online user interaction. To this end, this article evaluates the computational efficiency of a number of clustering algorithms with a view to creating geodemographic classifications “on the fly” at a range of different geographic scales.
Muhammad Adnan , Paul A Longley, Alex D Singleton and Chris Brunsdon
The paper can be downloaded here.
NYC Yellow Cabs have GPS fitted to them which have been tracked for the past year or so… anyway, there is an excellent article on this in the New York Times with obligatory map visualization:
http://www.nytimes.com/2010/04/03/nyregion/03icab.html
map (http://www.nytimes.com/interactive/2010/04/02/nyregion/taxi-map.html?ref=nyregion)
If we assume that taxi are the generally present in areas where people
are, this could be a useful source of population mobility and certainly the sort of data which may be useful in real-time geodemographics.
I am very excited by the massive expansion of Google Street View which I blogged about elsewhere. It is a good opportunity to present my Google Street View chronology:
1980 – 1988
Alnwick, Northumberland
1988-1990
Alnmouth, Northumberland
1990-1993
Allestree, Derby
1993-1998
Shenley Church End, Milton Keynes
1998-1999
Frimley, Surrey
1999-2003
Central Manchester, Manchester
Hulme, Manchester
Longsight, Manchester
Withington, Manchester
2003-2004
Worcester, Worcestershire
2004-2005
Witney, Oxfordshire
2005-2006
West Hampstead, London
2006-2010
Catford, London
I just had notification of an article I recently wrote for a special issue of GIS Development on Neogeography. This is available online: here or to download as a PDF here.
In brief, my article provides an overview of Neogeography and then details where I think the next developments will occur.
This paper reports on a cross-cultural outreach activity of the current UK ‘Spatial Literacy in Teaching’ (SPLINT) Centre of Excellence in Teaching and Learning (CETL), a past UK Economic and Social Research Council (ESRC) grant, and shared interests in family names between Japanese and UK academics. It describes a pedagogic programme developed for Japanese postgraduates and advanced undergraduates that entailed quantitative and qualitative analysis of the spatial distributions of Japanese family names. The authors describe some specific semantic, procedural and theoretical issues and, more generally, suggest how names analysis provides a common framework for engaging student interest in GIS.
Paul A. Longley; Alex D. Singleton; Keiji Yano; Tomoki Nakaya
Available on JGHE for those with academic access:
here.
