Census GIS and beyond: a journey in space and time

Transcription

1 Census GIS and beyond: a journey in space and time David Martin, University of Southampton AGI Education Lecture 2011 University College London

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3 Overview Two timelines Census GIS: the historical view Census 2011: a close-up view Two timelines revisited Futures 3

4 Timeline 1 (UK, 40 years) 1981 Digital mapping as additional analysis option 1991 GIS as an exciting new analysis tool 2001 GIS important to census geography design 2011 GIS inseparable from census operation 2021 Beyond the census? 4

5 Timeline 2 (myself, one day) Get up Go to the office Travel to London AGI lecture Dinner? Travel home 5

6 Census GIS: the historical view

7 Enduring need for small area population mapping Visualization and pattern exploration Resource allocation: large areas > small areas Targeting services/marketing Site location decisions/transportation demand Denominator populations 7

8 Enumeration 8

9 First task: census enumeration Get a form to every household Enumerator delivery/postal delivery Get them filled in Enumerator completes/householder completes Get them back again Enumerator collection/mail-back Organize entire enumeration from paper maps/replace with GIS 9

10 GIS for enumeration design

11 Mapping the outputs Management and geocoding of all collected results Multiple processes for data quality, edit and imputation, statistical disclosure control From geocoded records, aggregate to levels in a hierarchy: Enumeration geography (enumeration districts) Address geography (addresses, postcodes) Output geography (output areas, super output areas) Mapping, then GIS, for data management and presentation 11

12 110+ years of poverty mapping Charles Booth: poverty in Pimlico Source: booth.lse.ac.uk Guardian Datablog: Indices of Deprivation 2010 Source:

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15 Photo: David Martin 15

16 GIS for 0utput area design Using automated zone design to combine addresses and postcodes into small areas that meet design requirements for publication of data

17 Digital census geography 2001 Output Areas (England and Wales) Mean 297 persons; 123 households

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24 Barriers to (good) census GIS Traditional representational concepts: irregular, imposed areal units, boundary changes, modifiable areal unit problem Strengths and weaknesses of census as a data source: definitions, frequency, data licensing; problems usually geographically concentrated Temporal concept: focus on night-time residential base All these factors continue to affect most mainstream GIS applications that handle population data 24

25 Grid modelling framework Transfer population information onto a high resolution spatial grid, preserving volume and allowing unpopulated areas Variety of methods available for transferring counts from one set of geographical features to another areal interpolation, dasymetric mapping variants. Adaptive kernel estimation to generate gridded population estimates from input points ( centroids ) A key advantage of gridded models is continuity of spatial units through time (i.e. no boundary changes) 25

26 Centroids, boundaries and grids Centroid locations and boundaries Centroid populations redistributed onto grid 26

27 Grid from centroids Gridded population: census counts allocated to postcode locations and redistributed

28 Photos: David Martin, Sam Cockings 28

29 Census 2011: a close-up view

30 What have we learned since 2001? Challenges of using existing address lists Complex household structures (gated communities and buildings) Second homes, split households, complex movement patterns, differential response rates Westminster, Manchester and elsewhere: enumeration problems tend to be geographically concentrated These issues at heart of 2001 response difficulties 30

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32 2011 census summary Census day 27 March: broadly conventional census, with internet completion channel Mail-out and mail-back reliant on bespoke census National Address Register from Mastermap AL2 and NLPG + Flexible enumeration effort focused on most difficult areas Extended imputation methodology Overall cost ~ 482m First data July 2012: basic demographic statistics for local authorities; detailed geographical data autumn

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36 What about 2011 data? Broadly comparable questionnaire content to 2001, with additional questions on citizenship, place of residence, second addresses Broadly comparable set of data outputs planned, but more population bases possible 95% output area boundary stability, based on 2001 with only hierarchical changes 36

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39 Workplace zones Very different geographies of residence and workplace (output area place of work populations 0-80,000!) Increased value from workplace statistics 2001 disclosure control severely limited published data Re-apply output area design techniques in order to create a set of workplace zones Only merge or split whole output areas so that the two sets of data can be readily recombined 39

40 Southampton 2001 OAs (730) >625 Workers (Split to form WPZ) Workers (Acceptable as WPZ) <100 Workers (Merge to form WPZ)

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43 Two timelines revisited

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45 After the census? France rolling census since 1999 USA short form + community survey since 2000 Canada voluntary survey (last minute decision!) Belgium, Switzerland recent shifts towards use of linked administrative datasets UK? ONS programme of work to investigate Beyond 2011 census alternatives Importance of address-based and small area georeferencing in implementation of any such system 45

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47 Probable trajectory? Cost effectiveness 100% Census alternative Census Census Census Time 47

48 Need for better time-space distributions Conventional population mapping whether area-based or gridded focused on residential night-time populations But we need more realistic population distributions for other times of day/week/year Especially where population exposure is concerned: emergency planning, exposure to risk, services to dynamic populations, etc. 48

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51 Space-time population modelling Where tried, the general approach is to start with nighttime population model/map and transfer population subgroups to specific daytime locations, e.g. schools, workplaces Various recent application examples, particularly driven by emergency planning and modelling of population exposure to hazards In reality, many different timescales to be modelled, not just simple daytime and night-time Longstanding difficulty of obtaining data with sufficient space/time resolution for the non-residential addresses

52 Herzog and Hofstetter, 3D visualization of day time population, Zurich 52

53 Home Residence Office Work Outdoors Work All Employment Other Work Education by Stage All Education Others Roads Transport Hubs Population Distribution (%) 100% 80% Conventional Census GIS interpreted over time 60% 40% 20% 0% 00:00 22:00 20:00 18:00 16:00 14:00 12:00 10:00 08:00 06:00 04:00 02:00 00:00 Time (Hour) 53

54 Locations Data Sources Residential Private dwellings Communal ests. - Census, Mid-Year Population Estimates (MYEs) - Census, Mid-Year Population Estimates (MYEs) Total population +/- external visitors Nonresidential Employment Education Temp accomm. Healthcare Family/social Retail Leisure Tourism - Census, Annual Business Inquiry, QLFS - EduBase, DCSF school performance tables, HESA - VisitBritain, Annual Business Inquiry - Hospital Episode Statistics - VisitBritain - Annual Business Inquiry, commercial sources - ALVA Visitor Statistics, DCMS - ALVA Visitor Statistics, DCMS Generalised local - Transport Road Rail Metro/subway Air Water - DfT Road Statistics, Annual Average Daily Flow - National Rail station usage data - DfT Light Rail Statistics, TfL Tube customer metrics - CAA UK Airport Statistics - DfT Sea Passenger Statistics, London River Services Acronyms: QLFS Quarterly Labour Force; DCSF Department for Children, Schools and Families; HESA Higher Education Statistics Agency; Survey; DCMS Department for Culture, Media and Sport; ALVA Association for Leading Visitor Attractions; DfT Department for Transport; TfL Transport for London; CAA Civil Aviation Authority

55 Time profile example school Population In transit Present Time of day 55

56 Home Residence Office Work Outdoors Work Retail Work Other Work School Education Higher Education Others Roads Transport Hubs Population Distribution (% ). 100% 80% 60% Integrated multi-source datasets interpreted over time 40% 20% 0% 00:00 22:00 20:00 18:00 16:00 14:00 12:00 10:00 08:00 06:00 04:00 02:00 00:00 Time (Hour) 56

57 Next steps Already have a method for building gridded population models Already had high-quality georeferenced night-time population dataset Now have a rich range of georeferenced, time-specific population data sources (collected at specific dates, relevant to specific times of day/week/year) First steps to operationalise a spatiotemporal population modelling system 57

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59 Southampton, 200m cells 02:00 Residential night-time model; but includes some traffic and employment 59

60 Southampton, 200m cells 16:00 Workplaces, FE & HE institutions still open, schools closed; low residential; very high central densities 60

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68 GIS and the census Up to 1991 in UK essentially a non-gis census 2001 used GIS in major new ways for enumeration district design and new output area creation 2011 builds on 2001 but the broader trends are towards new data linkages and technologies, multiple timescales Beyond 2011 there is a good chance that a richer data system may supersede the census itself to be continued Plenty of new challenges in post-census population GIS! 68

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70 Acknowledgements Samantha Cockings and Samuel Leung Economic and Social Research Council award number RES Employee data from the Annual Business Inquiry Service, National Online Manpower Information Service, licence NTC/ABI07-P3020. Office for National Statistics 2001 Census: Standard Area Statistics (England and Wales): ESRC Census Programme, Census Dissemination Unit, Mimas (University of Manchester). National Statistics Postcode Directory Data: Office for National Statistics, Postcode Directories: ESRC Census Programme, Census Geography Data Unit (UKBORDERS), EDINA (University of Edinburgh). Quarterly Labour Force Survey, Economic and Social Data Service, usage number Mastermap ITN layer: Crown Copyright/database right 2009, an Ordnance Survey/EDINA supplied service. 70

71 Thank you