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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
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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
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Introduction
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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
Austrian national grid (Lambert projection): 10km
13°20' östl. von Greenw.47°30' nördl. Breite
47°30'
13°20' östl. von Greenw.Rasternetz auf der Basis des Meridians 13°20' derLAMBERT'SCHEN Abbildung
Netzmaschengröße = 10 km
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Austrian national grid – partial view: 10km
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Austrian national grid – partial view: 1km
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Austrian national grid – partial view: 125m
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Austrian national grid – partial view: 125m; land structure
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Austrian national grid – partial view: 125m; land structure, buildings and geo-reference points
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Austrian national Grid – partial view: 125m; visualized by orthophoto
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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
Population density by municipalities
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Population density by statistical grids (2,5km)
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Countries with coordinate based data
Comparison national – European grids
MGI-Lambert
ETRS-LAEA
Projektion MGI-Lambert
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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 ongrids 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
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FinlandProduction and dissemination of grid data since the 1970 Census in Finland (Marja Tammilehto-Luode, Statistics Finland)
United States of AmericaCombining Variable Spatial Data with Grids to Improve Data Visualization: Case Studies (Tim Trainor, U.S. Census Bureau)
SloveniaEstablishing 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
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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
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Summary of contributions/discussion
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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
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Production and dissemination of grid data since the 1970 Census in Finland
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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 needsCustomers of grid data; kinds of use of grid data; relevant grid size classes; etc.
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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
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