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Development of an automated matching algorithm to assess the quality of the OpenStreetMap road network : a case study in Göteborg, Sweden

Will, Julian LU (2014) In Student thesis series INES NGEM01 20141
Dept of Physical Geography and Ecosystem Science
Abstract
In the last decade a new and alternative source of geospatial data has become available, so called Volunteered Geographic Information (VGI). Private individuals voluntarily collect large amount of geographic data for a joint project. This data are usually free under certain licence restrictions.
One of the most well known examples of VGI is the OpenStreetMap (OSM) project. Due to its increasing popularity it has developed in less than 10 years to a useful data source. Private, scientific and commercial users are wondering how good is these voluntarily collected data and can it be an alternative to expensive authority and commercial datasets.
This study presents a quality assessment of the OSM road network against a reference dataset... (More)
In the last decade a new and alternative source of geospatial data has become available, so called Volunteered Geographic Information (VGI). Private individuals voluntarily collect large amount of geographic data for a joint project. This data are usually free under certain licence restrictions.
One of the most well known examples of VGI is the OpenStreetMap (OSM) project. Due to its increasing popularity it has developed in less than 10 years to a useful data source. Private, scientific and commercial users are wondering how good is these voluntarily collected data and can it be an alternative to expensive authority and commercial datasets.
This study presents a quality assessment of the OSM road network against a reference dataset from Lantmäteriet (Swedish National Mapping Agency). In order to allow a meaningful evaluation, corresponding features in both datasets have to be identified. This process is commonly referred as matching. Difficulties of automatic matching occur due to the different geometric representations of the two datasets.
An automated matching algorithm is developed to match road network data from OpenStreetMap and Lantmäteriet. The method is adopted from Koukoletsos et al. (2012) and developed further to incorporate feature correspondence. The matching is based mainly on geometric and attribute (road name) constraints. Besides minor pre-processing steps the algorithm works completely automated and can be applied to any region with data coverage in Sweden.
The matching is performed in a case study covering the area of Göteborg, the second largest city Sweden. The created feature correspondence is then used to calculate the quality elements completeness, positional accuracy and thematic accuracy.
The matching algorithm returned good results with an acceptable matching error. The quality assessment revealed that OSM can be seen as a proper data source which has some reservation regarding the attribute accuracy. (Less)
Please use this url to cite or link to this publication:
author
Will, Julian LU
supervisor
organization
alternative title
How good is volunteered geographic information?
course
NGEM01 20141
year
type
H2 - Master's Degree (Two Years)
subject
keywords
OpenStreetMap, automated matching, quality assessment, volunteered geographic data, linear features, Physical Geography and Ecosystem analysis
publication/series
Student thesis series INES
report number
317
language
English
additional info
External supervisor Daniel Garcia, Kartena AB, Göteborg
id
4464336
date added to LUP
2014-06-16 10:14:28
date last changed
2014-06-16 10:14:28
@misc{4464336,
  abstract     = {{In the last decade a new and alternative source of geospatial data has become available, so called Volunteered Geographic Information (VGI). Private individuals voluntarily collect large amount of geographic data for a joint project. This data are usually free under certain licence restrictions. 
One of the most well known examples of VGI is the OpenStreetMap (OSM) project. Due to its increasing popularity it has developed in less than 10 years to a useful data source. Private, scientific and commercial users are wondering how good is these voluntarily collected data and can it be an alternative to expensive authority and commercial datasets. 
This study presents a quality assessment of the OSM road network against a reference dataset from Lantmäteriet (Swedish National Mapping Agency). In order to allow a meaningful evaluation, corresponding features in both datasets have to be identified. This process is commonly referred as matching. Difficulties of automatic matching occur due to the different geometric representations of the two datasets.
An automated matching algorithm is developed to match road network data from OpenStreetMap and Lantmäteriet. The method is adopted from Koukoletsos et al. (2012) and developed further to incorporate feature correspondence. The matching is based mainly on geometric and attribute (road name) constraints. Besides minor pre-processing steps the algorithm works completely automated and can be applied to any region with data coverage in Sweden.
The matching is performed in a case study covering the area of Göteborg, the second largest city Sweden. The created feature correspondence is then used to calculate the quality elements completeness, positional accuracy and thematic accuracy. 
The matching algorithm returned good results with an acceptable matching error. The quality assessment revealed that OSM can be seen as a proper data source which has some reservation regarding the attribute accuracy.}},
  author       = {{Will, Julian}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Student thesis series INES}},
  title        = {{Development of an automated matching algorithm to assess the quality of the OpenStreetMap road network : a case study in Göteborg, Sweden}},
  year         = {{2014}},
}