Abstract
Abstract. OpenStreetMap (OSM) uses the Open Database License, it is a collaborative project that collects a rich set of vector data provided by volunteers. It is a global collection of mapping data that can be used for a wide variety of purposes. Many third-party online maps are based on OpenStreetMap data. Currently, more and more large organizations are choosing OSM for their maps. In addition, the analysis of the spatial quality of the OSM data shows that particular care must be taken. However, there are several methods for assessing the quality of the OSM data by comparing the OSM to an authoritative dataset. In this context, it is essential to develop an automatic procedure to improve its spatial quality. This work proposes a quantitative method for comparing the quality of the OSM and an authoritative data set on urban networks in the city of Oran (Algeria). The procedure is based on python modules in a GIS environment and provides measurements of the spatial accuracy and completeness of the OSM road network. The method is applied to assess the quality of the Oran OSM road network data set through a comparison with the official Algerian dataset. The results show that the OSM's Algerian road network is very complete, but with low spatial accuracy.
Highlights
1.1 General backgroundThe frequency of natural disasters around the world has increased steadily in recent decades
The data quality indicators identified by TC211(Husen 2018) for the assessment of spatial data are completeness, logical or topological consistency, positional accuracy, semantic accuracy, attribute accuracy, temporal accuracy and lineage, which have been used in various studies A methodology is applied to geometrically correct the OSM data, based on the variable radius buffering technique
The OSM data are available under an Open Data Commons Open Database license (ODbL) for reuse, which allows for sharing, creation and adapting of the data unless reuse is attributed (Brassel 1995)
Summary
The frequency of natural disasters around the world has increased steadily in recent decades These disasters are damaging social and economic infrastructure in all countries, but their long-term consequences are severe for developing countries. The availability of high-resolution satellite images has enabled a large participation of people around the world who are not necessarily GIS specialists to produce spatial data that is increasingly being used in several sectors under open source license. This type of information was termedVolunteered Geographical Information' (VGI) by Goodchild, 2007. The OSM data are available under an Open Data Commons Open Database license (ODbL) for reuse, which allows for sharing, creation and adapting of the data unless reuse is attributed (Brassel 1995)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
