Spatial Analysis Using the National Pupil Database

This is a talk I gave for the 2011 PLUG conference: http://www.bris.ac.uk/cmpo/events/2011/plug/index.html

Transcript

1. Dr Alex D Singleton Spatial Analysis using the School of Environmental Sciences Spatial Analysis using the National Pupil Database
2. Content • Geographic referencing and the NPD • Indicators and Geodemographics • Catchment models • Mapping and the Geoweb • Mapping and the Geoweb
3. GEOGRAPHIC REFERENCING Putting people and schools on the map... % Level 4-5 Qualifications (2001 Census)
4. Households Building Blocks Pupils Postcodes ~15-25 addresses in a postcode
5. Building Blocks • School locations – Derived from postcode + Edubase • Caveats – Postcodes come from PLASC – state schools – Postcodes come from PLASC – state schools • Independent pupils lack spatial reference – Spatial Resolution • LSOA • OA if you are nice to DfE!
7. Min: 40 households &100 people
8. Min: 1,000 residents; 400 households. Av 1,500 residents
9. Min size of 5,000 residents, 2,000 households
10. Min size of 5,000 residents, 2,000 households
11. INDICATORS AND GEODEMOGRAPHICS Social and spatial characteristics Output Area Classification
12. Indicators and Geodemographics • Linked to NPD – Composite Measures: • Income Deprivation Affecting Children Index – LSOA; Part of IMD – LSOA; Part of IMD • Geodemographics – Output Area Classification (Output Area) – ACORN (Postcode) – Raw variables • Council Tax bands; JSA etc... plus lots more..
14. Example: GCSE Grade Profiles 2009 GCSE Grade A* 15 20 25 30 % E Wealthy Achievers Hard Pressed 0 5 10 E Entries A*
15. Students Achieving 5 A*-C Grades at GCSE in 2009 75% 35%
17. Data Link DCSF HESA (0) HESA (+1) ~20% Direct Entry Gap Year Key Stage 5 HESA (+1) HESA (+2) Gap Year Gap Years National Targets = 18-30 Age Range
18. 40 50 60 70 80 HE Progression Rate with 95% Confidence Intervals (%) Wealthy Achievers Urban Prosperity Comfortably Off Moderate Means Hard Pressed Inner City Adversity Asian Communities Home owning Asian family areas 0 10 20 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 HE Progression Rate with 95% Confidence Intervals (%) Low income, singles, small rented flats Low income, singles, small rented flats Flows – KS4
19. 1.0 2.0 3.0 4.0 5.0 6.0 1A:Wealthy Executives 1B:Affluent Greys 1C:Flourishing Families 2A:Prosperous Professionals 2B:Educated Urbanites 5A:Struggling Families 5B:Burdened Singles 5C:High-Rise Hardship 5D:Inner City Adversity Subject Profiles 0.0 2B:Educated Urbanites 2C:Aspiring Singles 3A:Starting Out 3B:Secure Families 3C:Settled Suburbia 3D:Prudent Pensioners 4A:Asian Communities 4B:Post-Industrial Families 4C:Blue-Collar Roots 5A:Struggling Families Medicine and Dentistry
20. 2.0 4.0 6.0 8.0 10.0 12.0 14.0 1A:Wealthy Executives 1B:Affluent Greys 1C:Flourishing Families 2A:Prosperous Professionals 2B:Educated Urbanites 5A:Struggling Families 5B:Burdened Singles 5C:High-Rise Hardship 5D:Inner City Adversity Subject Profiles 0.0 2B:Educated Urbanites 2C:Aspiring Singles 3A:Starting Out 3B:Secure Families 3C:Settled Suburbia 3D:Prudent Pensioners 4A:Asian Communities 4B:Post-Industrial Families 4C:Blue-Collar Roots 5A:Struggling Families Mathematical and Computer Sciences
21. Blue Collar Communities Legend Legend 20 students 50 students 100 students 200+ students
22. Prospering Suburbs Legend Legend 20 students 50 students 100 students 200+ students
23. CATCHMENT MODELS Where can I go to school? Catchment Map of E Leeds
24. http://www.udel.edu/johnmack/frec480/cholera/cholera2.html
34. MAPPING AND THE GEOWEB Profiling for the public Target Schools for University Oxford
35. OpenStreetMap Data great_britain.osm (.xml) PostgreSQL DB with PostGIS osm2pgsql NASA’s SRTM DEMs GDAL Tools UKBorders English MSOAs and Postcodes PLASC/NPD OAC Shapefiles ArcGIS Color Brewer PerryGeo Hillshading OSM Tiles Tiles PLASC/NPD mySQL DB Schools Atlas IDACI OpenLayers (.js) HEFCE POLAR Mapnik OSM Tiling Script (.py) Stylesheets(.x ml) AJAX Requests PVC (.kml) OAC R Google Chart API Tiles Chart Cache
46. www.alex-singleton.com www.alex-singleton.com