ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-4-2021
https://doi.org/10.5194/isprs-annals-V-4-2021-33-2021
https://doi.org/10.5194/isprs-annals-V-4-2021-33-2021
17 Jun 2021
 | 17 Jun 2021

GEOMETRIC ENHANCEMENT OF THE OPENSTREETMAP ROAD NETWORK

F. Z. Belhouari, I. Boukerch, and K. Si youcef

Keywords: OpenStreetMap, geometric correction, Delaunay triangulation, road network, geospatial, geometric accuracy

Abstract. OpenStreetMap (OSM) is a collaborative project to create a free and editable map of the world. You can think of OSM as the 'Wikipedia' of cartography. An important geospatial component of this database is the road network quality, which is important for applications such as routing and navigation.

The objective of this work is the geometric enhancement of the OSM road network using a standard national map as a reference. We use two transformation methods, the global transformation and the local transformation (Delaunay triangulation).

This study aims to present a new approach to improve the OSM road network geometrically. To this end, we present a three-step approach based on two techniques that leads to the enhancement of the geometric accuracy of the OSM road network. The first step is the global transformation of the OSM road network. The second step consists of applying the local transformation (Delaunay triangulation) on the OSM road network. In the last step, a comparison between the two methods is examined by calculating the mean and the standard deviation of the checkpoints in order to justify which is the best technique for the geometric enhancement of the OSM road network. We will be particularly interested in the application of this approach in the geometric enhancement / correction where each node of the OSM network will have a newly calculated position. Both approaches have been tested in the region of Oran in Algeria as testing example. The reference data is a city map produced by the National Institute of Cartography and Remote Sensing (INCT) in 2006. The proposed techniques show a clear improvement in geometric accuracy.