Seminar on “Spatial statistics” Session 1: Use of statistical grids in official statistics

1. Seminar on “Spatial statistics” Session 1: Use of statistical grids in official statistics Conference of European Statisticians, Paris, Fifty-eighth plenary session, 8-10 June 2010

2. Introduction

3. Introduction to Session 1 • In focus: geo-referenced data: statistical data that are related to geographical coordinates, rather than just to an given region, or administrative regional unit • Geo-referenced data means a system change in the elaboration of spatial or regional statistics  highest flexibility in delineating regional areas according to functional/statistical criteria • Statistical grids: function as a spatial reference system that can serve as the smallest statistical area unit for which – respecting statistical confidentiality – data may be provided to the user • Statistical grids are also an instrument for delineating functional/thematic areas independently from administrative boundaries

4. Austrian national grid (Lambert projection): 10km

5. Austrian national grid – partial view: 10km

6. Austrian national grid – partial view: 1km

7. Austrian national grid – partial view: 125m

8. Austrian national grid – partial view: 125m; land structure

9. Austrian national grid – partial view: 125m; land structure, buildings and geo-reference points

10. Austrian national Grid – partial view: 125m; visualized by orthophoto

11. Introduction to Session 1 • Sources and unit of the geo-reference • Coverage of statistical domains and data suited for statistical grids • Grids as instruments for cartographic maps • National versus European grids: the need for harmonisation

12. Population density by municipalities

13. Population density by statistical grids (2,5km)

14. Countries with coordinate based data

15. Comparison national – European grids MGI-Lambert ETRS-LAEA Projektion MGI-Lambert

16. Introduction to Session 1 • Aim of the session: exchange of experience and best practices in using statistical grids in official statistics • Session should cover: creation, use and provision of statistical grids and grid based data, with special emphasis on • grids as a tool for providing data to the user • grids as a tool for delineating functional/thematic areas • Session does not intend to deal with methodological/ technical issues • Three invited papers from Finland, Slovenia and the United States of America

17. Introduction to Session 1 Finland Production and dissemination of grid data since the 1970 Census in Finland (Marja Tammilehto-Luode, Statistics Finland) United States of America Combining Variable Spatial Data with Grids to Improve Data Visualization: Case Studies (Tim Trainor, U.S. Census Bureau) Slovenia Establishing of a national hierarchical grid system in Slovenia – lessons learned and future challenges (Igor Kuzma, Statistical Office of the Republic of Slovenia)

18. Programme 11.20 – 11.35 Introduction to session Introducing the papers General themes Key statements 11.35 – 11.50 Replies by authors 11.50 – 12.20 General discussion 12.20 – 12.30 Short summary Introduction to Session 1 Page 18

19. Summary of contributions/discussion

20. Preconditions of statistical grid data: Map coordinates of all buildings Register-based system that allows to link persons, enterprises and buildings and dwellings National grid nets, with two grid cell sizes: 1 km and 250 m Grid data are used once in five years for the delimitation of localities and urban settlements, including urban/rural distinction Dissemination: ready-made packages and custom-made services Data confidentiality Data quality Production and dissemination of grid data since the 1970 Census in Finland Content Page 20

21. Grid data are mainly census-type data, regularly updated with data from administrative registers Development also driven by the objective to increase visualisation by maps to all kinds of regional statistics on the internet Further advantages of grid data are seen: Potential for comparable territorial statistics and statistical time series, when administrative boundaries/structures were changed Potential for cross-border analysis Planned switch from a national coordinate system to the European Terrestrial Reference System (ETRS) 89 Production and dissemination of grid data since the 1970 Census in Finland Discussion

22. The change from the national grid system to the European Terrestrial Reference System (ETRS) 89 requires the compilation at the level of the original data before aggregation into grids. This may increase confidentiality problem in case a user has acquired data by both coordinate systems. What is the policy of Statistics Finland with regard to this change of grid system? Production and dissemination of grid data since the 1970 Census in Finland Question 1 Page 22

23. Grid data are census-type data (population, employment, housing, building, local units, and the like). Where are the limits of grid-based data? Production and dissemination of grid data since the 1970 Census in Finland Question 2 Page 23

24. It is mentioned that there are two types of grid data disseminations: ready-made packages and custom-made services. Are custom made services only specific data provisions or does Statistics Finland also provide analyses or other forms of studies ? Production and dissemination of grid data since the 1970 Census in Finland Question 3 Page 24

25. Establishing of a national hierarchical grid system in Slovenia – lessons learned and future challenges First geo-referencing experience: 1971 Census 2008: initiative of the Statistical Office of the Republic of Slovenia to establish a national hierarchical grid system Seven grid sizes: 100m, 200m, 500m, 1 000m, 2 500m, 5 000m and 10 000m Data sources for grid data: register-based data and census data Grid data protection policy Content Page 25

26. Additional advantages of grid statistics: Valuable for micro and macro analysis Enable better sampling Not all earlier census data were available as geo-referenced data:  variable grid sizes Confidentiality: demographic data (number of population, sex, five-year age groups) are not suppressed Adding more variables to the grid dissemination data set requires suppression of less sensitive data Grid cell aggregations in case necessary data protection Establishing of a national hierarchical grid system in Slovenia – lessons learned and future challenges Discussion Page 26

27. Slovenia being a country with geo-referenced data from decades of censuses, introduced a national grid system just recently. What was the users’ feedback with respect to this new dissemination offer? Establishing of a national hierarchical grid system in Slovenia – lessons learned and future challenges Question 1 Page 27

28. What is the position of the Statistical Office of the Republic of Slovenia with respect to the introduction of a harmonised European grid system and its application at national level? Establishing of a national hierarchical grid system in Slovenia – lessons learned and future challenges Question 2 Page28

29. It is mentioned that the Data Protection Committee of Slovenia is preparing a new data protection policy for the Census 2011, covering also all non-census spatial statistics. Could you already give some indications? Establishing of a national hierarchical grid system in Slovenia – lessons learned and future challenges Question 3 Page 29

30. Combining Variable Spatial Data with grids to Improve Data Visualization: Case Studies Topic: legal, statistical and administrative geography used by the US Census Bureau compared to the characteristics of geometric grids Choice between statistical grids and administrative polygons, or both approaches integrated Similarities and differences between spatial data and statistical grids Census block level: census blocks are the smallest atomic geographical area Census blocks are irregularly shaped Hierarchy: Counties > census tracks > block groups > census blocks Content Page 30

31. Key statements of the paper: The small size and utility of census blocks makes them good candidates to serve as a unit for acquiring, managing and using spatial statistics Use of grids to substitute for this finite level of geography likely offers less capability and more complexity than that available with blocks In general, the smaller the level of census geography, the greater the expectation is for greater precision. Combining Variable Spatial Data with grids to Improve Data Visualization: Case Studies Discussion Page 31

32. It is understood that the census block as the smallest geographic area fulfils the requirements for the census preparation as well as for the dissemination of the census data. The use of statistical grids may improve the data quality; however, it is not seen as a replacement for the blocks. Thus, there are no plans to introduce statistical grids? Combining Variable Spatial Data with grids to Improve Data Visualization: Case Studies Question 1 Page 32

33. In the cited case study on the 1992 Agricultural Atlas a combination of grids and administrative geography were used to more accurately display the locations of data instances. Could you a bit more elaborate on this, how grids were used? Combining Variable Spatial Data with grids to Improve Data Visualization: Case Studies Question 2 Page 33

34. General questions / themes Role of statistical grids in the dissemination policy of national statistical institutes Ready-made data packages, custom-made packages; data coverage of grid data; pricing policy Role of statistical grids as well as of GIS as instruments to delineate functional/thematic areas Examples: settlement areas, urban areas, etc. Experience with user needs Customers of grid data; kinds of use of grid data; relevant grid size classes; etc. Page 34

35. National versus European grid systems Change-over policy from national to European grids; parallel systems ? INSPIRE Directive Development of European grid, geo-referenced databases; etc. Data protection and confidentiality issues/policies Specific confidentiality rules for grid data, higher sensitivity, harmonisation of confidentiality rules, etc. ? General questions / themes Page 35

36. Thank you for your attention ! Norbert RAINER mailto: norbert.rainer@statistik.gv.at Tel.: +43-1-71128-7703