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 Page 1

2. Introduction Page 2

3. Page 3  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 Introduction to Session 1

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

5. Austrian national grid – partial view: 10km Page 5

6. Austrian national grid – partial view: 1km Page 6

7. Austrian national grid – partial view: 125m Page 7

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

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

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

11. Page 11  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 Introduction to Session 1

12. Population density by municipalities Page 12

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

14. Countries with coordinate based data

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

16.  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 Introduction to Session 1 Page 16

17. Page 17 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) Introduction to Session 1

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

19. Summary of contributions/discussion Page 19

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 Content Page 20 Production and dissemination of grid data since the 1970 Census in Finland 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 Discussion Production and dissemination of grid data since the 1970 Census in Finland Page 21

22. Page 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? Question 1 Production and dissemination of grid data since the 1970 Census in Finland Page 22

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

24. Page 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 ? Question 3 Production and dissemination of grid data since the 1970 Census in Finland Page 24

25. Page 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. Page 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 Discussion Establishing of a national hierarchical grid system in Slovenia – lessons learned and future challenges Page 26

27. Page 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? Question 1 Establishing of a national hierarchical grid system in Slovenia – lessons learned and future challenges Page 27

28. Page28 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? Question 2 Establishing of a national hierarchical grid system in Slovenia – lessons learned and future challenges

29. Page 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? Question 3 Establishing of a national hierarchical grid system in Slovenia – lessons learned and future challenges Page 29

30. Page 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. Page 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. Discussion Combining Variable Spatial Data with grids to Improve Data Visualization: Case Studies Page 31

32. Page 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? Question 1 Combining Variable Spatial Data with grids to Improve Data Visualization: Case Studies Page 32

33. Page 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? Question 2 Combining Variable Spatial Data with grids to Improve Data Visualization: Case Studies Page 33

34. Page 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. Page 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.atnorbert.rainer@statistik.gv.at Tel.: +43-1-71128-7703