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Grid models of population: temporal comparison by fixing the geography . David Martin, School of Geography University of Southampton. Overview. Problems of comparison over time Merits of using gridded data Data sources Grid modelling principles Grid modelling resources

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Grid models of population: temporal comparison by fixing the geography

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Grid models of population temporal comparison by fixing the geography l.jpg

Grid models of population: temporal comparison by fixing the geography

David Martin,

School of Geography

University of Southampton


Overview l.jpg

Overview

  • Problems of comparison over time

  • Merits of using gridded data

  • Data sources

  • Grid modelling principles

  • Grid modelling resources

  • Example: Southampton 1981-2003

  • Conclusions


Problems of comparison over time l.jpg

Problems of comparison over time

  • Population changes location and composition

  • Boundaries and definitions are recast between data collection events; measurement success varies

  • Cannot disentangle true change from representation and measurement

  • If geographical units remained the same, one part of the problem would be addressed


Southampton 1991 eds l.jpg

Southampton 1991 EDs

  • N = 417

  • mean address count = 228

  • Population 197,000


Southampton 2001 oas test data l.jpg

Southampton 2001 OAs (test data)

  • N = 762

  • mean address count = 125

  • 6.2% overall population increase


Intersection of eds and oas l.jpg

Intersection of EDs and OAs

  • N = 1771

  • mean address count = 54

  • Where was the increase?

  • (and ED to ED was no better)


Merits of using gridded data l.jpg

Merits of using gridded data

  • Grid cell data comparable through time

  • Settlement geography is retained

  • No boundary data required for geographical comparison

  • Readily combined with gridded environmental models


Data sources l.jpg

Data sources

  • Great Britain: 1971 census gridded data published but not available

  • Northern Ireland: 1971-2001 grid square data published

  • No general GB grid counts 1981-

  • Spatial modelling required

    • 1971-2001 population-weighted centroid locations published

    • Postcode locations can be treated as centroids


Grid modelling principles 1 l.jpg

Grid modelling principles (1)

  • Population-weighted centroid(s) as summary points of local distribution

  • Locally adaptive kernel estimation based on inter-centroid distances

  • Redistribution of centroid counts into grid

  • Could use dasymetric and other methods

  • This is NOT interpolation


Grid modelling principles 2 l.jpg

Grid modelling principles (2)

Weighting

wij

a

Distance

dij

k

Centroid


Grid modelling principles 3 l.jpg

Grid modelling principles (3)

Centroids and boundaries

Gridded population model


Ni surfaces 1991 l.jpg

NI surfaces 1991

  • Construct surfaces from NI 1991 ED centroids

  • Experiment with dispersion, postcode centroids, directional interpolators

  • Selective comparison with grid square data

  • Martin, Tate and Langford (2000)


Slide14 l.jpg

Standard model

Postcode centroids

Empirical kernel width

Directional kernels


Grid modelling resources l.jpg

Grid modelling resources

  • NI grid square dataare true count data for download

  • SURPOP provides 1981 and 1991 ready-made surfaces

  • SurfaceBuilder allows construction of own surfaces from centroid data

  • (URLs on final slide…)


Surpop l.jpg

Surpop

  • Requires census data registration

  • 200m cells

  • 1981 or 1991

  • Select variable

  • Extract window

  • Export to GIS


Surfacebuilder l.jpg

SurfaceBuilder

  • Download and install VB program

  • Download X,Y,Z centroid data file

  • Specify surface parameters

  • Run and preview model

  • Export to GIS


Surfacebuilder sequence l.jpg

SurfaceBuilder sequence


Example southampton 1981 2001 l.jpg

Example: Southampton 1981-2001

  • 25 x 25km region centred on City of Southampton

  • Population change 1981-2003 from census and postcode data

  • 1980s: large-scale greenfield development at urban fringe

  • 1990s: combined with brownfield redevelopment within urban area


Slide20 l.jpg

1981 population count 0.2m


Slide21 l.jpg

1991 population count 0.2m


Slide22 l.jpg

2001 population count 0.2m


Slide23 l.jpg

1991-1981 population diff 0.2m


Slide24 l.jpg

2001-1991 population diff 0.2m


Slide25 l.jpg

1981-91-01 change, 0.2km

1981

1991-81

1991

2001-91

2001


Slide26 l.jpg

1981-91-01 change, 1km

t2-t1

(t2-t1)/(t2+t1)

1981

1991

2001


Contemporary change postcodes l.jpg

Contemporary change: postcodes

  • All Fields Postcode Directory providing quarterly postcode record

  • Downloadable from UKBORDERS

    • Very big files!

  • Postcodes as centroids with household counts can be modelled onto grid

  • Census counts could be reallocated


Slide28 l.jpg

2001-02-03 change, 0.2km

(AFPD households)

2001

2002-01

2002

2003-02

2003


Conclusions l.jpg

Conclusions

  • Grid-based modelling offers specific advantages over small areas

    • Longer-scale neighbourhood change

    • Monitoring contemporary change

    • Practical modelling advantages

  • Problem of noise due to centroid relocation (requires smoothing)

  • Challenge of definitional drift and measurement error remains


Key urls l.jpg

Key URLs

  • Northern Ireland grid square data http://census2.mc.man.ac.uk/cdu/2001/ni/GRID/index.htm

  • Surpop http://census.ac.uk/cdu/software/surpop/

  • SurfaceBuilder http://www.geog.soton.ac.uk/users/martindj/davehome/software.htm


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