1. How geospatial information adds value to existing sub-national data and territorial typologies
Valeriya Angelova-Tosheva, Eurostat,
28/06/2018
Session 9

2. C O N T E N T S Context and motivation
Use case one: Emerging data needs from DG Agriculture and Rural Development met by using geolocation and alternative data sources
Use case two: DG Maritime Affairs and Fisheries' data request for a customised territorial typology C O N T E N T S

3. Context and motivation
The mission of Eurostat: to provide high-quality statistics for understanding Europe and enabling better decisions to be made
Eurostat's database contains 750 sub-national datasets (NUTS 2 and 3, cities and Functional Urban Areas, Degree of Urbanisation, urban, rural, intermediate regions, coastal-non-coastal regions, coastal areas and metropolitan regions + border, island, outermost and mountain regions
The territorial typologies legally recognised in the TERCET Regulation
New emerging data needs, requests for unusual sub-national indicators of interest that are outwit the scope of the existing data collections at Eurostat and the NSIs; customised typologies

4. European institution using sub-national data for taking decisions are spending billions of Euro

5. Use case one: Emerging data needs from DG Agriculture and Rural Development met by using geolocation and alternative data sources
DG AGRI makes extensive use of Eurostat's data by Degree of Urbanisation (LAU based typology) and by Urban-rural regions (NUTS 3 based typology)
Political analysts from AGRI made the hypothesis that people living in rural regions lack access to social meeting points which leads to isolation, or drives people to search for different services in a neighbouring, larger residential area; an impact on the quality of life
Request to Eurostat: number of schools, kindergartens, post offices, sport clubs and bars in rural regions

6. The solution of Eurostat
Input data
geodata available from volunteered geographic information on the OpenStreetMap (OSM)
Methodology
the GIS object's categories of interest all over Europe were selected from the OSM and exported in a GIS environment as a resulting layer
the resulting point features layer were overlaid by geolocation with the layer containing the NUTS 3 boundaries and aggregated by individual NUTS regions
the data obtained were matched with the latest urban-rural classification of the NUTS 3 regions and normalized by of inhabitants living in every single NUTS 3 region

7. Results
Distribution of the NUTS 3 regions by category of access to post offices

8. Results Number of post offices per 100 000 inhabitants
From zero in several Outermost regions to 108 post offices per inhabitants in the Shetland Islands
The phenomenon is rather country defined than rural-urban
A 'rural' paradox in the north of the UK and in Central Europe

9. Results Number of post offices per 100 000 inhabitants
A future topic for more sophisticated geospatial analysis at Eurostat could be an estimation of the access of people living in rural grid cells to social meeting points, measured by distance

10. Use case two: DG Maritime Affairs and Fisheries' data request for a customised territorial typology
From 2018 onwards, DG MARE will regularly monitor the progress and developments in the EU Blue Economy and will produce an Annual economic report on the subject
The Blue Economy encompasses all the sectoral and cross-sectoral economic activities related to oceans, seas and coasts

11. Use case two: DG Maritime Affairs and Fisheries' data request for a customised territorial typology
Ports, as multi-activity nodes, play a crucial role in the development of the established and emerging maritime sectors
Eurostat provided data on all ports in a country, main ports, top twenty or top five ports
Request to Eurostat: more detailed data on maritime ports/coastal cities

12. Problem statement
A new specific data collection on ports is not foreseen then as the existing one is well established with a legal basis
No specific provisions for coastal cities in the TERCET Regulation
Eurostat maintained a list of ports, published in an Official Journal which also includes inland water ports - no firm definition of a "maritime port"
A geodataset 'Ports, 2013 – Transport Networks', containing a point feature class with the location of pan-European ports available at GISCO; only geographical information was available in this dataset and it was unable to distinguish in a systematic way between maritime and inland ports

13. The case of Hamburg – coastal or non-coastal city?

14. The solution of Eurostat
Input data
the geographical layer of the cities (as defined in TERCET)
the geographical layer of the coastal areas (LAU-2s)
data on more than 900 cities on 197 different variables in the domains of demography, social aspects, economic aspects, training and education, environment, tourism and culture are available in EuroBase
Methodology
selection of cities having at least 50% of their surface area in a zone covered by coastal areas
export of the resulting layer of coastal cities containing the same geo code used in the city statistics database

15. Results 255 coastal cities in Europe
For 2015 for the 204 coastal cities reported currently in the database, we observe more than 46 million people which is around 9% of the European population
All other datasets available in the city database could be assigned to the list of the coastal cities/maritime ports

16. Conclusion
The two examples show how the combination of inside knowledge of statistical methodology and geospatial information can:
Enable data reengineering
and reliable estimates
Be used for production of customised territorial typologies
Address emerging data needs where new data collections aren't foreseen
Save resources
Support better policy decisions

17. Thank you for your attention!
How geospatial information adds value to existing sub-national data and territorial typologies
Thank you for your attention!
Valeriya Angelova-Tosheva, Eurostat, Valeriya.ANGELOVA-