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Experiences from the geocoding in the 2005 Norwegian Person Travel Survey

Experiences from the geocoding in the 2005 Norwegian Person Travel Survey. Jon Martin Denstadli Institute of Transport Economics (TOI) Oslo. In rural areas, the wards covers large areas, but the settlement is usually relatively concentrated. N.B different scales.

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Experiences from the geocoding in the 2005 Norwegian Person Travel Survey

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  1. Experiences from the geocoding in the2005 Norwegian Person Travel Survey Jon Martin Denstadli Institute of Transport Economics (TOI) Oslo

  2. In rural areas, the wards covers large areas, but the settlement is usually relatively concentrated. N.B different scales Basic statistical units (statistical wards) Smallest geographical area for presenting statistics Norway is divided into approximately 14,500 wards - areas as uniform as possible with respect to population size, communication and building structure. In Oslo, Bergen, and Trondheim (about 2,000 wards) the area covered by a ward is less than 1 sq. km, the mean population 400-600 (max 3,500).

  3. ”GEO Plug In” in the 2005 NPTS • Geo. databases: • GAB register • Register of cities, urban settlements, and places

  4. ”GEO Plug In” in the 2005 NPTS

  5. ”GEO Plug In” in the 2005 NTPS

  6. Quality of geocoding in the 2005 NPTS Combined start/end point: 88 %

  7. Enriching travel data Distance matrix and level of service matrix For every pair of statistical wards: - distance - travel time and cost (car) - vehicle time, waiting time, frequency, cost, etc. (public transport)

  8. Population data • Age (1 year interval) • Gender • Average income • Occupation • Etc. Statistical ward • Aggregates • Urban regions • Transport services • Etc Other information Enriching travel data • Employment data • No. of employees • Industry • Etc • Employment data • No. of employees • Industry • Etc • Buildings (office and private) • Type • Size • No. of storages • Etc.

  9. Car use in Oslo by place of residence (trips starting at home)

  10. Transport mode by destination (motorized modes) (Trips with endpoint home not included)

  11. Oslo - inner city

  12. Conclusions • People are capable of recalling addresses or provide other adequate information, and share this with the interviewer • Lower location rate for people living in sparsely populated areas • Additional data bases enriches travel data • Detailed geoinformation combined with GIS provides new opportunities for presenting travel data

  13. Oslo - Land use 1980 Residentialbuildings Businessbuildings Businesses; manufacturing, storehouses, commercial and administrative, hospitals, schools etc.

  14. Oslo - Land use 1980 + new businesses 1985-2004. New business buildings (including hospitals) with at least 500 square metres of floor space built 1985- 2004. Square metres floor space. Oslo.

  15. Car trips in the greater Oslo area Public transport an alternative only on trips with endpoint in the inner city. 70-80 percent of destinations are in outside the inner city (not including trips that ends in home).

  16. Effect of accessibility by public transport and access to parking - travel to work in Oslo. Access to parking is defined as free parking at the workplace.

  17. Processing information Geocoding: Information on where trips start and end: Wards in Bergen • Possible to integrate other information connected with the wards. • Possible to use GIS.

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