Towards an Automated Comparison of OpenStreetMap with Authoritative Road Datasets

OpenStreetMap (OSM) is an extraordinarily large and diverse spatial database of the world. Road networks are amongst the most frequently occurring spatial content within the OSM database. These road network representations are usable in many applications. However the quality of these representations can vary between locations. Comparing OSM road networks with authoritative road datasets for a given area or region is an important task in assessing OSM’s fitness for use for applications like routing and navigation. Such comparisons can be technically challenging and no software implementation exists which facilitates them easily and automatically. In this article we develop and propose a flexible methodology for comparing the geometry of OSM road network data with other road datasets. Quantitative measures for the completeness and spatial accuracy of OSM are computed, including the compatibility of OSM road data with other map databases. Our methodology provides users with significant flexibility in how they can adjust the parameterization to suit their needs. This software implementation is exclusively built on open source software and a significant degree of automation is provided for these comparisons. This software can subsequently be extended and adapted for comparison between OSM and other external road datasets

An open source procedure to assess the quality of the OpenStreetMap road network

OpenStreetMap (OSM) is the largest, most complete and most up-to-date geospatial database of the world. One of the most frequently occurring elements within this database is the road network, whose quality is crucial for a number of applications such as routing and navigation. Several methods have been proposed for the assessment of OSM road network quality based on the comparison with corresponding authoritative datasets. However, these methods are often tightly coupled to the characteristics of the authoritative dataset involved in the comparison and this makes it hard to replicate or extend them. This study presents an automated procedure for the comparison of OSM and authoritative road network datasets, based on spatial analysis and driven by the choice of parameters made by the user. The procedure returns measures of the positional accuracy and completeness of the OSM road network

Volunteered Geographic Information and OpenStreetMap: Experimentations and Perspectives

Volunteered Geographic Information (VGI) is the most successful term to mark the shift (happened almost a decade ago) according to which citizens, in addition to being data consumers, have also become precious providers of geographic information. The increasingly large volumes of datasets generated by VGI projects have attracted a huge academic interest in a number of topics, ranging from data quality assessment to data mining and data conflation, societal studies as well as ethical and privacy issues. The most popular VGI project, OpenStreetMap (OSM), which aims at the generation of a crowdsourced map of the world, can be nowadays considered as a research topic on its own. In the poster a wide range of the author's current research works on VGI and OSM is shown. These works partially derive from the author’s involvement in three (current or just ended) EU COST Actions: TD1202 "Mapping and the Citizen Sensor", IC1203 “ENERGIC”, and CA15212 “Citizen Science to promote creativity, scientific literacy, and innovation throughout Europe”

Database-supported change analysis and quality evaluation of OpenStreetMap Data

A significant advantage of OpenStreetMap data is its up-to-dateness. However, for rural and city planning, it is also of importance to access historical data and to compare the changes between new and old versions of the same area. This paper first introduces into a differentiated classification of changes on OpenStreetMap data sets. Then a methodology for an automated database-supported analysis of changes is presented. Beyond the information already provided from the OpenStreetMap server, we present a more detailed analysis with derived information. Based on this approach it is possible to identify objects with attributive or geometric changes and to find out how they exactly differ from their previous versions. The analysis shows in which regions mappers were active during a certain time interval. Furthermore, a time based approach based on various parameters to determine the quality of the data is presented. It provides a guideline of data quality and works without any reference data. Therefore, an indication about the development of OpenStreetMap in terms of completeness and correctness of the data in different regions is given. Finally, a conclusion and an outlook on open research questions are presented

Positional accuracy assessment of the OpenStreetMap buildings layer through automatic homologous pairs detection: the method and a case study

OpenStreetMap (OSM) is currently the largest openly licensed collection of geospatial data. Being OSM increasingly exploited in a variety of applications, research has placed great attention on the assessment of its quality. This work focuses on assessing the quality of OSM buildings. While most of the studies available in literature are limited to the evaluation of OSM building completeness, this work proposes an original approach to assess the positional accuracy of OSM buildings based on comparison with a reference dataset. The comparison relies on a quasi-automated detection of homologous pairs on the two datasets. Based on the homologous pairs found, warping algorithms like e.g. affine transformations and multi-resolution splines can be applied to the OSM buildings to generate a new version having an optimal local match to the reference layer. A quality assessment of the OSM buildings of Milan Municipality (Northern Italy), having an area of about 180 km2, is then presented. After computing some measures of completeness, the algorithm based on homologous points is run using the building layer of the official vector cartography of Milan Municipality as the reference dataset. Approximately 100000 homologous points are found, which show a systematic translation of about 0.4 m on both the X and Y directions and a mean distance of about 0.8 m between the datasets. Besides its efficiency and high degree of automation, the algorithm generates a warped version of OSM buildings which, having by definition a closest match to the reference buildings, can be eventually integrated in the OSM database

An automated GRASS-based procedure to assess the geometrical accuracy of the OpenStreetMap Paris road network

OpenStreetMap (OSM) is the largest spatial database of the world. One of the most frequently occurring geospatial elements within this database is the road network, whose quality is crucial for applications such as routing and navigation. Several methods have been proposed for the assessment of OSM road network quality, however they are often tightly coupled to the characteristics of the authoritative dataset involved in the comparison. This makes it hard to replicate and extend these methods. This study relies on an automated procedure which was recently developed for comparing OSM with any road network dataset. It is based on three Python modules for the open source GRASS GIS software and provides measures of OSM road network spatial accuracy and completeness. Provided that the user is familiar with the authoritative dataset used, he can adjust the values of the parameters involved thanks to the flexibility of the procedure. The method is applied to assess the quality of the Paris OSM road network dataset through a comparison against the French official dataset provided by the French National Institute of Geographic and Forest Information (IGN). The results show that the Paris OSM road network has both a high completeness and spatial accuracy. It has a greater length than the IGN road network, and is found to be suitable for applications requiring spatial accuracies up to 5-6 m. Also, the results confirm the flexibility of the procedure for supporting users in carrying out their own comparisons between OSM and reference road datasets

DATABASE-SUPPORTED CHANGE ANALYSIS AND QUALITY EVALUATION OF OPENSTREETMAP DATA

A significant advantage of OpenStreetMap data is its up-to-dateness. However, for rural and city planning, it is also of importance to access historical data and to compare the changes between new and old versions of the same area. This paper first introduces into a differentiated classification of changes on OpenStreetMap data sets. Then a methodology for an automated database-supported analysis of changes is presented. Beyond the information already provided from the OpenStreetMap server, we present a more detailed analysis with derived information. Based on this approach it is possible to identify objects with attributive or geometric changes and to find out how they exactly differ from their previous versions. The analysis shows in which regions mappers were active during a certain time interval. Furthermore, a time based approach based on various parameters to determine the quality of the data is presented. It provides a guideline of data quality and works without any reference data. Therefore, an indication about the development of OpenStreetMap in terms of completeness and correctness of the data in different regions is given. Finally, a conclusion and an outlook on open research questions are presented

Database-supported change analysis and quality evaluation of OpenStreetMap Data

Abstract. A significant advantage of OpenStreetMap data is its up-to-dateness. However, for rural and city planning, it is also of importance to access historical data and to compare the changes between new and old versions of the same area. This paper first introduces into a differentiated classification of changes on OpenStreetMap data sets. Then a methodology for an automated database-supported analysis of changes is presented. Beyond the information already provided from the OpenStreetMap server, we present a more detailed analysis with derived information. Based on this approach it is possible to identify objects with attributive or geometric changes and to find out how they exactly differ from their previous versions. The analysis shows in which regions mappers were active during a certain time interval. Furthermore, a time based approach based on various parameters to determine the quality of the data is presented. It provides a guideline of data quality and works without any reference data. Therefore, an indication about the development of OpenStreetMap in terms of completeness and correctness of the data in different regions is given. Finally, a conclusion and an outlook on open research questions are presented. Document type: Articl

An open source approach for the intrinsic assessment of the temporal accuracy, up-to-dateness and lineage of OpenStreetMap

Abstract. OpenStreetMap (OSM) is the most popular crowdsourced geographic information project. The main factor that still limits the practical use of OSM is the lack of quality assurance. OSM quality assessment is thus a well-studied topic in literature, with most of the studies evaluating the quality by comparison against reference datasets. In contrast to these extrinsic approaches, OSM intrinsic assessment evaluates the quality by only analysing OSM itself. This study contributes to OSM intrinsic assessment by introducing an open source procedure to evaluate the temporal accuracy, up-to-dateness and lineage of OSM. Two workflows are presented: the first allows accessing the historical evolution of single OSM objects through an interactive web application, while the second aggregates and stores results on a user-defined grid to enable further GIS processing. The methodology is applied on the OSM nodes in the city of Dar es Salaam, Tanzania, by computing the following measures on the cells of an hexagonal grid: total number of nodes, average date of creation and last edit of nodes, average update frequency of nodes, average number of versions of nodes, average and total number of different contributors on nodes. Results highlight the mapping dynamics driven by the Dar Ramani Huria project, focused on increasing flood preparedness and resilience. When moving from the peripheral areas to the city centre, OSM is characterized by a progressively higher density of nodes, created earlier in time and updated by a higher number of contributors, which are all indexes of a general higher data quality. Document type: Articl