Development of distance statistics in the Netherlands

1. Development of distance statistics in the Netherlands results using Euclidean and network distances Niek van Leeuwen, Statistics Netherlands. nlwe@cbs.nl Bled, Slovenia, 3 october 2008

2. Short overview • Methods • address backbone • street network • future developments • Examples • Euclidean distance • point in polygon • distance along a network

3. Questions using distances • How far away is the nearest public transport facility • Are there enough primary school in the neighbourhood • How many people suffer from noise • Does the ambulance arrive within acceptable time.

4. Ad dres sb a c k b o n e Stages in assembling distance statistics • Register database connecting geographical location clustering

5. Stage 2: Address backbone • connects addresses from different sources • is a method • adds x- and y-coordinate to addresses (source Cadaster) • operational since late 2006 (AML or SPSS syntax)

6. Address backbone (2)

7. Address backbone (3)Future developments • Address and building register • In use 2009 - 2011 • Entity: the smallest unit of living or working, unique number • Contains address and geographical location (contour or point) • Changes avaiable within 4 working days. • Only addresses in this register are to be used and are obligatory or all governmental institutes and agencies

8. Address backbone (4)National registers Development of interelated national registers Register of persons Topography Address and building register Business register Register of Cadaster

9. Address backbone (5)National registers

10. Stage 3: Geographical location • X- and y-coordinate • Cadaster, later on from national register buildings and addresses • Address and an x- and y-coordinate • Street network • Ministry of Transport, Public works and Watermanagement • updated 4 times a year • Paved roads, one way direction for highways and State roads.

11. Street networkCalculating distances Address point projected into network Matching between streetname of points and network. Nearby points are clustered. Distance between projected points are calculatedOne way direction taken into account Projection distance of address point onto network is added Network contains 2,2 million clusterpoints for a total of 7.8 million addresses Network is build up once a year. Future: Bicycle lanes

12. Street network (2) highways and State roads

13. Statistics using distancesnearest distance to highways (Euclidean distance) Average distance primary schools to highways Distance 300m from highways (light red area) and 50m from State roads (blue area)

14. Statistics using distancesExceeding ceiling values small particle (PM10) (point in polygon) Number of inhabitants exceeding EU ceiling values of small particles (PM10) Contour derived from model

15. Travelling distance to closest primary school, travelling along paved roads (network distances) Statistics usingdistancestravelling along a street network

16. Statistics usingdistancestravelling along a street network • Topics • Distance to • Health care • Schools • - Shopping centres, Retail trade • Cultural facilities (Libraries, Theatre) • Sport facilities

17. Questions?