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NSIs and geostatistics
Introduction to geo-statistical units
ESTP course on Geographic Information Systems (GIS):
Use of GIS for making statistics in a production environment
Statistics Norway, Oslo, 26th to 30th of March 2012
Attribution (by) Licensees may copy, distribute, display and perform the work and make derivative
works based on it only if they give the author or licensor the credits in the manner specified by these.
Mr Oliver Heiden
Master
Eurostat, European Commission
Unit E4, Regional Statistics and GI,
Section of Regional and urban statistics
BECH A3/049, L-2920 LUXEMBOURG
Oliver.Heiden@ec.europa.eu
Tel: +352 4301 31961
Mob. +352 621 594545
http://creativecommons.org/licenses/by/3.0/
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Sense of geo-statistical units
geo
statistical
unit
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Sense of geo-statistical units
• geo: Geospatial/Geography
– Human geography (patterns, processes in human society)
 Culture, e.g. Linguistic geography
 Development, e.g. Standard of living, Quality of life measurement
 Economics, e.g. Marketing geography and Transportation geography
 Health
 History, e.g. changes of places or regions changes through time
 Politics, e.g. interdependency: space ↔ politics, e.g. Electoral
geography, Geopolitics
 Population
 Settlement
– Physical geography (study of the solid earth, the atmosphere,
hydrosphere, oceans and biosphere)
 Geomorphology, Hydrology, Glaciology, Biogeography, Climatology,
Meteorology, Coastal geography, Oceanography, Geomatics,
Environmental geography
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Sense of geo-statistical units
• statistical: Statistics (science of data)
– Data:
 Quantitative or Qualitative
 Exhaustive or Sample
 Synchronic or Diachronic
– Methods:
 Observational or Experimental
 Descriptive or Inferential
– Numerous fields of application
 Actuarial science, Biostatistics, Business Analytics, Chemometrics,
Demography, Econometrics, Environmental statistics, Epidemiology,
Geostatistics, Operations research, Population ecology, Quantitative
psychology, Psychometrics, Quality control, Social statistics, Statistical
finance, Statistical mechanics, Statistical physics, Statistical
thermodynamics, etc.
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Sense of geo-statistical units
• unit:
– Hierarchical component:
 Entity regarded as an elementary structural or functional constituent of a
whole.
– Comparability component:
 Determinate amount or quantity (as of length, time, heat, value) adopted
as a standard of measurement for other amounts or quantities of the
same kind.
– In geo-statistical concepts refers mainly to area (2D) or points (0D,
coordinates, addresses)
– Other units: persons
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Typology of geo-statistical units
• geo-statistical units:
– Shape:
 Random
 Standardised
– Origin:
 Natural
 Historical
 Administrative
 Analytical, functional
– Comparability
 Homogeneous
 Heterogeneous
– Coverage
 Comprehensive
 Selective
– Contiguity
 Single territory
 Divided territory
– Partition
 Exclusive
 Overlapping
– Stability
 Dynamic
 Semi-dynamic
 Stable
– Size:
 Physiographic regions,
Continents
 Supranational entities
 Countries
 Regions
 Municipalities, Communes
 Districts, Neighbourhoods
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Typology of geo-statistical units
Shape Origin
Kommuner (NO)
Larger Urban Zones
(Urban Audit, EU)
NUTS and
Statistical Regions
Population Grid
(1 km2)
Wine growing
regions
COROP (NL)
TTWA (UK)
Postcode districts
(EU)
Comparability Coverage Contiguity Partition Stability
Size
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Typology of geo-statistical units
Shape Origin
Kommuner (NO)
Comparability Coverage Contiguity Partition Stability
Random Historical
Heterogeneous
Administrative
Larger Urban Zones Random Administrative Heterogeneous
Analytical
(Urban Audit, EU)
Size
Comprehen- Single
sive
territory
Exclusive Dynamic
3
Selective
Single
territory
Exclusive Semidynamic
5
NUTS and
Statistical Regions
Random Historical
Heterogeneous
Administrative
Analytical
Comprehen- Divided
sive
territory
Exclusive Semidynamic
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Population Grid
(1 km2)
Standar Analytical
-dised
Homogeneous
Comprehen- Single
sive
territory
Exclusive Stable
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Wine growing
regions
Random Natural
Historical
Heterogeneous
Selective
Divided
territory
Exclusive Semidynamic
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COROP (NL)
Random Administrative Heterogeneous
Analytical
Comprehen- Single
sive
territory
Exclusive Semidynamic
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TTWA (UK)
Random Analytical
Heterogeneous
Comprehen- Single
sive
territory
Exclusive Semidynamic
4
Postcode districts
(EU)
Random Functional
Heterogeneous
Comprehen- Single
sive
territory
Overlapping
2
Dynamic
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Ideal of geo-statistical units
Shape Origin
Comparability Coverage Contiguity Partition Stability
Standar Administrative Homogeneous
-dised
Comprehen- Single
sive
territory
Exclusive Stable
Size
Small
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Main concepts of geo-statistical units
• Administrative units:
–
–
–
–
–
Based on real-world phenomena
Commonly accepted, variety of implementation
Analysed area = policy target
Hierarchical structure
Subject to changes (external stimulus)
• Functional units:
– Defined according to analytical requirements using
 geographical criteria (e.g. altitude, type of soil etc.)
 socio-economic criteria (e.g. homogeneity, complementarity of regions)
–
–
–
–
Not widespread, variety of methodologies
Analysed area ≠ policy target
Mainly one-level
Subject to changes (internal stimulus)
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Main concepts of geo-statistical units
• Grids:
–
–
–
–
–
Standardised breakdown (100m2, 1km2, 4km2)
Intuitive, standard entity
Analysed area ≠ policy target
Ad-hoc hierarchical structure
Stable
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Main concepts of geo-statistical units
Classifications
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Main concepts of geo-statistical units
Policy
making
↔
Business
Statistics
Research
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Main concepts of geo-statistical units
•
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Main concepts of geo-statistical units
• Examples → Administrative units:
– Municipalities
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Main concepts of geo-statistical units
• Examples →
Administrative units:
– Municipalities
 Degree of
Urbanisation
(DEGURBA)
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Main concepts of geo-statistical units
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Main concepts of geo-statistical units
• Examples → Administrative units:
– NUTS
 3-level, full coverage, mixed: administrative/non-administrative
 Based on administrative breakdown in Member States, EFTA and
Candidate countries
 Managed by Eurostat
 Size (population) comparable across countries
 Stable for at least three years: NUTS2003, NUTS2006, NUTS2010
NUTS-1
NUTS-2
NUTS-3
MAX Population
DEA
18 Mill. FR10
11 Mill. ES300
6 Mill.
MIN Population
FI2
27 000
FI20
27 000
ES703
10 000
MAX Area (km2)
FI1
337 000
FI1D
227 000 SE332
106 000
MIN Area (km2)
BE100
13 ES640
13
161
ES640
http://epp.eurostat.ec.europa.eu/portal/page/portal/nuts_nomenclature/introduction
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Main concepts of geo-statistical units
• Examples →
Administrative
units:
– NUTS
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Main concepts of geo-statistical units
• Examples → Administrative units:
– Urban-Rural Typology
 Revision of a distorted method
– Different size of LAU2s
– Different size of NUTS3s
 Population grid (1 km²): registered population when available, otherwise
disaggregation grid (JRC)
 Identify population living in urban areas:
– Selection of grid cells with density > 300 inh./km²
– Only groups of grid cells, representing a total population of > 5000
inhabitants
– Contiguity is evaluated including diagonals
 Principle: three categories of regions, based on the population share in
rural raster cells
– Predominantly urban: population share of rural raster cells < 20%
– Intermediate: population share of rural raster cells between 20% and 50%
– Predominantly rural: population share of rural raster cells > 50%
 Combining small NUTS3 regions
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Main concepts of geo-statistical units
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Main concepts of geo-statistical units
• Examples → Administrative units:
– Metropolitan Regions
 Groupings of NUTS-3
 Based on LUZ
http://epp.eurostat.ec.europa.eu/portal/page/portal/region_cities/metropolitan_regio
ns
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Main concepts of geo-statistical units
• Examples → Administrative units:
– Urban Audit
 Major revision
– OLD:
– 300 variables every 3 years, 38 variables annually, 369 core cities
– Spatial definition without standards
–
–
–
–
NEW:
330 variables every 5 years, 40 variables annually
Common concept for definition of units
(Revision of LUZ based on commuting flows)
http://epp.eurostat.ec.europa.eu/portal/page/portal/region_cities/city_urban
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Main concepts of geo-statistical units
• Examples → Administrative units:
– Urban Audit
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Main concepts of geo-statistical units
• Examples → Functional units:
– Labour Market Areas
 one-level
 Defined by NSIs or Departments of Economy, Universities etc.
 Comparable within countries, dissimilar across countries
 Stable for at least three years: NUTS2003, NUTS2006, NUTS2010
 EU classification: LAU (Local Administrative Units)
 Eurostat project 2012:
– Assessment of feasibility of EU-wide LMAs
– Assessment of (potential) value-added of EU-wide LMAs
– Proposal for best practices
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Main concepts of geo-statistical units
• Examples → Functional units:
– Labour Market Areas
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Main concepts of geo-statistical units
• Examples →
Functional units:
– Labour Market Areas
Key for color classification
A
A & B overlap
B
A & C overlap
C
B & C overlap
D
C & D overlap
Other
Vacant areas.
Very few residents, not engaging in paid work. No commuters.
Areas under Turkish occupation.
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Main concepts of geo-statistical units
• Examples → Grids
Policy
making
↔
Statistics
Confidentiality
Business
Research
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Thanks!