ArticlePDF Available

New Applications based on collaborative geodata–the case of Routing

Authors:

Abstract and Figures

Setting the scene The successful collection of information by masses of volunteering individuals enabled by Web technology (otherwise referred to as Web 2.0) does not halt before the realm of geographic information. Information resources available for instance in the online-encyclopedia Wikipedia or the photo-sharing platform flickr are currently being extended with geographic information or geotags at an impressive rate. 1 Even more remarkable in the given context, several projects concentrating solely on the collection of geographic information have formed. Goodchild (2007) gives an overview of these global collaborations and calls the phenomenon Voluntary Geographic Information (VGI). One of the most striking and sophisticated examples of VGI is the OpenStreetMap (OSM) project started in 2004. It aims at creating and collecting free vector geodata covering the whole planet. Its means are ordinary citizens vested with GPS-devices logging coordinates, out-of-copyright maps and aerial imagery provided by OSM-friendly companies (like Yahoo! Inc.). Deriving from these data sources geodata is then created. At the time of writing OSM counts ~60000 registered users: ~7000 of which have created or updated nodes and ~3000 have uploaded GPX tracks. Altogether the OSM dataset currently consists of roughly 270 Mio. nodes partly constituting 30 Mio. ways. 2 Haklay (2008) analysed the data quality of OSM data in England. One outcome of his analysis is the fact that against common expectation only very little quality assurance is being carried out upon the OSM data: Dividing England into grid cells of 1 km 2 , it turns out that 50% of the area of England has been mapped by individual persons and 89.5% by only up to three individuals. Due to this and also due to its lack of completeness the dataset would not (yet) be suitable for more sophisticated purposes than 'cartographic products that display central areas of cities' (p.24).
Content may be subject to copyright.
New Applications based on collaborative geodata – the case of Routing
Sebastian Schmitz
1
, Alexander Zipf
1
, Pascal Neis
1
1Chair of Cartography, Department of Geography, University of Bonn, Germany
Tel. (+49-228-73-3527) Fax (+49-228-73-5607)
{schmitz, zipf, neis}@geographie.uni-bonn.de
http://www.geographie.uni-bonn.de/karto/ http://www.openrouteservice.org/
Setting the scene
The successful collection of information by masses of volunteering individuals enabled by Web
technology (otherwise referred to as Web 2.0) does not halt before the realm of geographic
information. Information resources available for instance in the online-encyclopedia Wikipedia or the
photo-sharing platform flickr are currently being extended with geographic information or geotags at
an impressive rate.
1
Even more remarkable in the given context, several projects concentrating
solely on the collection of geographic information have formed. Goodchild (2007) gives an overview
of these global collaborations and calls the phenomenon Voluntary Geographic Information (VGI).
One of the most striking and sophisticated examples of VGI is the OpenStreetMap (OSM) project
started in 2004. It aims at creating and collecting free vector geodata covering the whole planet. Its
means are ordinary citizens vested with GPS-devices logging coordinates, out-of-copyright maps and
aerial imagery provided by OSM-friendly companies (like Yahoo! Inc.). Deriving from these data
sources geodata is then created. At the time of writing OSM counts ~60000 registered users: ~7000
of which have created or updated nodes and ~3000 have uploaded GPX tracks. Altogether the OSM
dataset currently consists of roughly 270 Mio. nodes partly constituting 30 Mio. ways.
2
Haklay
(2008) analysed the data quality of OSM data in England. One outcome of his analysis is the fact
that against common expectation only very little quality assurance is being carried out upon the
OSM data: Dividing England into grid cells of 1 km
2
, it turns out that 50% of the area of England has
been mapped by individual persons and 89.5% by only up to three individuals. Due to this and also
due to its lack of completeness the dataset would not (yet) be suitable for more sophisticated
purposes than ‘cartographic products that display central areas of cities’ (p.24).
However, in this paper we present an example of utilizing OSM data for a more sophisticated
purpose. OpenRouteService (ORS) is a route service operating on OSM data (Neis 2008).
3
It has
been launched in April 2008. The initial coverage of Germany has recently been extended to large
parts of Europe including England (Figure 1). In this contribution we will first discuss ORS in further
detail. This includes a brief evaluation of data fitness for routing as well as strength and problems of
OSM data. Then we will detail a use case of ORS usage in an emergency management context
followed by some key insights. Finally, future work and perspectives are presented.
OpenRouteService.org
The services available through the above URL implement open standards of the Open Geospatial
Consortium (OGC), namely those defined in OpenGIS Location Services 1.1 (OGC 2005). Several
Location-based Services are implemented. However, we focus on the Route Service implementation
within this paper. ORS has been the first national route planner for pedestrian or bicycle routes
making that option available even before companies like Google. Extending spatial coverage of the
service is work in progress.
1
2,7 million photos with geotags have been uploaded to http://flickr.com in the month of September 2008
2
http://wiki.openstreetmap.org/index.php/Statistics
3
http://www.openrouteservice.org
Figure 1: The OpenRouteService website with a route from Berlin to Rome. The light green overlay indicates coverage at the
time of writing
Evaluation of data fitness for routing
Table
1
gives an overview of hits, total number of calculated routes and the number of failed route
requests due to errors in street network since the service went online in April 2008. The percentage
of failed route requests compiled from server log files gives a first indication of OSM data quality for
routing. The decreasing percentage of failed route requests shows data quality has improved over
time. Through the extension in service coverage to less well-mapped areas, this obvious trend is
however somewhat obscured. The reduction of failed route requests can be ascribed to the use of
ORS not only as a route planner, but also as a tool for data validation. Having noted this general
trend of increasing data quality for routing, we discuss this issue in more detail. What are problems
and strengths of the OSM dataset for a routing application?
Table 1: ORS hits, route requests and failures due to errors in street network over the course of time
Month/2008 Hits Route Requests Failures Percentage failed
April ca. 800 ca. 1.500
1
ca. 150
1
10%
June ca. 4.200 ca. 5.700
1
ca. 120
1
2%
September ca. 5.600 ca. 14.500
2
ca. 650
2
4,5%
1
Routing in Germany
2
Routing in Germany, Switzerland, Austria, Italy, Denmark, Liechtenstein, UK and Ireland
Problems and Strengths of the OSM dataset
At the core of each routing application is the routing graph. The routing graph represents the street
network as a model of nodes and edges. It is critical that the graph is built from a topologically
correct dataset: junctions are represented as nodes and streets are represented as edges between
them. Junctions are only recognized as such, if the crossing streets have a common node at their
intersection. Fehler! Verweisquelle konnte nicht gefunden werden. illustrates cases of
unrecognized junctions.
During collection and maintenance of OSM data, topology is already considered an important aspect
by the voluntary mappers. Tests have shown that the above cases are only rarely encountered in
the dataset. Thus, they have been neglected during the completion of the mandatory and decisive
task of building the routing graph from OSM data. Here, the existing topology of OSM data is
examined regarding the occurrence of street intersections with common nodes, i.e. junctions. At
those common nodes, streets are divided into individual edges (ways). The number of edges in the
routing graph is usually higher than the number of streets in the original dataset (Figure 3).
Figure 3: Building the routing graph from OSM data
Another challenge is inconsistencies in the OSM dataset with regard to attribution of the geometries.
This is particularly true for street names and poses a problem for the generation of useful route
descriptions. For instance, abbreviations are used or spelling differs for the same street. Those
problems were solved in a pre-processing step that harmonized inconsistent street naming. A
comprehensive list of street types used for the different types of routing is available in the OSM
Wiki.
4
While attribution inconsistencies and topological omissions can be regarded as problems of
the OSM dataset that needed special treatment, it also offers some unique strength. One is the
enormous data richness that in places even beats commercial providers. This allows for new
applications that due to a lack of data were not easily possible before. Examples are national
pedestrian and bicycle routing as well as routing in formerly uncommon domains (Figure 4).
Furthermore, the quick response time for data corrections should be mentioned as unrivaled also
among commercial data providers.
Use case Disaster Management
Weeks after hurricane „Ike“– that killed over a hundred people and left tens of thousands homeless
- has devastated Haiti the situation is still tense. Because of flooded and destroyed streets and
bridges the humanitarian operations lead by the US for the over 650.000 affected people the
situation remains difficult. In order to avoid famine and epidemics the people need to be supplied
by food, medicine and other goods and the rebuilding of the infrastructure needs to be organized.
4
http://wiki.openstreetmap.org/index.php/OpenRouteService
(a) Original OSM Data
(b) Modified OSM data
Figure 2: Examples of unrecognized junctions: No intersection node present (left, a), intersection node not
(a)
(b)
Figure 4: Pedestrian routing with ORS through Hyde Park, London
The UN Joint Logistics Center (UNJLC) – a unity hosted by the World Food Program (WFP) –
organizes the logistics for the UN operations for the humanitarian and disaster management
operations after hurricane Ike. The UNJLC defines and implements the UN SDI-T which constitutes
the transport-related branch of the United Nations Spatial Data Infrastructure (UNSDI) under
development. For the current operation is information about the actual condition of the streets very
important, as well as information about hindrances, danger areas and the situation of the
infrastructure at large. In that context we were asked by UNJLC to support the implementation of a
route planning service for Haiti that takes the actual street condition into account. An important
feature of OpenRouteService.org for the disaster management operation was to consider blocked
areas or streets when routing. This means that streets inside those regions a not used for routing.
The OGC standard implemented in ORS, the Open Location Services Route Service, defines so called
„AvoidAreas“, which can be used to realize such a functionality.
OpenRouteService.org offers two alternatives for using this: The first one is available through the
GUI of OpenRouteService.org, where a user can draw those AvoidAreas interactively on the map.
Those areas are avoided when this user calculates a route. But as the polygons are only available on
the client side other users do not have access to them. Therefore a second option was realized that
allows staff from the organizations involved to upload spatial data sets that represent those
AvoidAreas into the geodatabase of ORS-Haiti though the Web-interface. Those areas then are
available for any users of the site. They can be activated for routing through clicking an option on
the web page. A similar approach is used for considering information about traffic jams or
construction works based on RDS-TMC data in Germany (Mayer et al. 2008). While a lot of
improvements regarding functionality and usability seem sensible first feedback from users in Haiti
has confirmed that the service is a valuable help for the disaster management work in Haiti even in
such a quickly released first prototype.
Insights
OSM data can be used for such sophisticated purposes as routing. The increasing interest in the
website shows the service provides useful results to the general European public that uses ORS. The
decreased percentage of failed route requests implies an increase in OSM data quality.
In the context of the highly dynamic and still quickly growing OSM dataset, a rather obvious and
simple principle seems well worth mentioning: given a working routing algorithm implementation,
routing quality and future possibilities scale with data quality and richness. Apparently, the more
complete and up-to-date the dataset, the better routing results will be. On the other hand, the more
attributes contained in the dataset, i.e. the richer it is, the more possibilities for domain-specific
route calculation arise. Clearly, the dataset is the limiting factor. In the case of OSM this dataset is
collected by a ‘horde’ of 60.000 volunteers. The question as to what limits them remains open.
Haklay (2008) gives one possible direction: a lack of quality assurance among OSM mappers had
been a surprising result of his study. To our minds, this is where a service like ORS comes into play.
To a certain degree, its availability and implementation details regulates OSM collaborative mapping
in the context of routing. Tags that are used in ORS will prevalently be mapped. As ORS allows for
simple, easy and satisfying testing of OSM data in terms of routing, it can be considered a means of
quality assurance. The specialized version of OpenRouteService for the Haiti UN disaster
management operation shows that open data and open standards offer a sensible approach for
realizing geographical applications in particular in the case of disaster management.
Perspectives & Future work
Future possibilities can be split into two categories. First, the currently available service can be
further refined by mashing-up OSM data with other (proprietary) geodata. This already happens
with the inclusion of Shuttle Radar Topography Mission (SRTM) data for the generation of route
altitude profiles of ORS routes (Schilling et al. 2008). The use of SRTM could be extended by
allowing steepness as a request criterion for routes. Another example for this category is the
inclusion of near real-time traffic jam data from the Traffic Message Channel (TMC) (Meyer 2008)
and very similarly the consideration of impassable roads when calculating routes in the Haiti Use
Case described. The second category of future possibilities subsumes all cases where the existing,
rich OSM dataset is further utilized to develop routing for specific user-groups. Depending on the
attributes that already are and possibly will be contained in the dataset, those user-groups can be
manifold. Imagine special routing for hiking, skiing, indoor navigation, public transport or heavy
trucks. Or think of routing especially targeted at disabled people (wheelchair, blind). Classical car
routing can be enhanced by the consideration of turn restrictions that are partly contained in the
OSM dataset. As outlined above, this is expected to boost their capture by OSM mappers. It has
been argued above that services operating on OSM have a regulative and quality assuring effect. It
remains future work to statistically prove their mutual dependency by correlating considered tags in
ORS and their capture in OSM. Quality assurance of OSM data calls for another future work item.
Being a project based on collaboration, it lives of accessing the knowledge of its community. In
order to optimize this, the OSM dataset and thus ORS would strongly benefit from an efficient
routing error reporting tool embedded onto the ORS website as an extra layer. This assumption is
based on the general Open Source mantra that ‘given enough eyeballs, all bugs are shallow’
(Raymond 2000, p.8). A similar application exists for OSM in general, but not yet directly connected
to routing.
5
Apparently, ORS is one among many other services offering routing on the web. In order
to provide additional motivation to map even more exact and capture even more attributes, it seems
promising to build a routing comparison tool that lets a user easily request routes against different
(commercial) services and compare the results.
Potential of Extending OpenStreetMap to 3D
Schilling et al. (2008) show how to integrate free OSM data with the open source Shuttle Radar
Topography Mission (SRTM)1 data to construct a digital elevation model for Germany. That can be
used for 3D visualizations through Web Services such as the OGC Web 3D Service draft specification
5
http://www.openstreetbugs.org
as realized in Schiling et al. (2007) and also 3D routing similar to Neis et al. (2007). The result is a
3D application for a whole country (first case: Germany) based completely on collaboratively
collected free geodata and open standards using several OGC services from routing to geocoding
and directory services (POI search). The service will be available soon at www.gdi-3d.de. Figure 5
gives a first example on what can be reached with such an approach.
Figure 5: Web based 3D service based on open data (OSM & SRTM) and open services
References
Goodchild, M.F. (2007): Citizens as sensors: the world of volunteered geography, In: GeoJournal,
Vol. 69. Issue 4, pp. 211-221
Haklay, M. (2008): How good is OpenStreetMap information? A comparative study of
OpenStreetMap and Ordnance Survey datasets for London and the rest of England, in:
Environment & Planning (under review)
Mayer, C. (2008). Nutzung von Verkehrsfunkdaten des Traffic Message Channel über OGC Sensor
Web. Unpublished diploma thesis, University of applied science Mainz,
Mayer, C., Stollberg, B., Zipf, A. (2008, submitted): Providing near Real-time Traffic Information
within Spatial Data Infrastructures. Submitted for GEOWS 2009, The International Conference
on Advanced Geographic Information Systems & Web Services. Cancun. Mexico.
Neis, P., A. Schilling, A. Zipf (2007): 3D Emergency Route Service (3D-ERS) based on OpenLS
Specifications. GI4DM 2007. 3rd Int. Symp. on Geoinformation for Disaster Management.
Toronto, Canada.
Neis, P. (2008): Location Based Services mit OpenStreetMap Daten. Master Thesis. University of
applied sciences Mainz, Department of Geoinformatics and Surveying
Neis, P. and Zipf, A. (2008): OpenRouteService.org – Combining Open Standards and Open
Geodata. The State of the Map. 2nd Open Street Maps Conference, Limerik. Ireland.
Open Geospatial Consortium (OGC) (eds.) (2005): OpenGIS Location Service Implementation
Specification: Core Services, OpenGIS document OGC 05-016
Raymond, E.S. (1999): The Cathedral & the Bazaar. Musings on Linux and Open Source by an
Accidental Revolutionary, Chapter 2: The Cathedral & the Bazaar, citation refers to online
version available at http://www.catb.org/~esr/writings/cathedral-bazaar/cathedral-bazaar/
Schilling, A., Lanig, S., Neis, P. & Zipf, A. (2008). DEM Processing and 3D Navigation using open
standards and free geo data. In: 3rd Int.Workshop on 3D Geo-Information. Seoul, South Korea.
Schilling, A., Basanow, J., Zipf, A. (2007): VECTOR BASED MAPPING OF POLYGONS ON IRREGULAR
TERRAIN MESHES FOR WEB 3D MAP SERVICES. 3rd International Conference on Web
Information Systems and Technologies (WEBIST). Barcelona, Spain. March 2007.
... OSM aims at creating open geodata where users can actively contribute and edit geographic information [31], which can be used by other services. Two primary benefits of the OSM dataset are that it contains a vast amount of semantic information that often surpasses that provided by commercial suppliers and the data can be quickly updated in response to errors [32]. ...
... Several services have made use of OSM data, including the OpenRouteService (ORS) (http://openrouteservice.org) and Wheelmap (http://wheelmap.org). The ORS [32,33] uses the road network data from OSM within routing algorithms and provides an open API supporting the OpenLS framework [34]. In the past, attempts were made to add landmark-based navigation directly into the OpenLS framework and ORS, though selection processes were limited based on a limited source of properties about potential landmark candidates [35]. ...
Article
Full-text available
With the advent of location-aware smartphones, the desire for pedestrian-based navigation services has increased. Unlike car-based services where instructions generally are comprised of distance and road names, pedestrian instructions should instead focus on the delivery of landmarks to aid in navigation. OpenStreetMap (OSM) contains a vast amount of geospatial information that can be tapped into for identifying these landmark features. This paper presents a prototype navigation service that extracts landmarks suitable for navigation instructions from the OSM dataset based on several metrics. This is coupled with a short comparison of landmark availability within OSM, differences in routes between locations with different levels of OSM completeness and a short evaluation of the suitability of the landmarks provided by the prototype. Landmark extraction is performed on a server-side service, with the instructions being delivered to a pedestrian navigation application running on an Android mobile device.
... Despite its completeness and quality issues, OSM has been widely used for several applications: e.g., validation of land cover maps [16]; land cover/land use classification [17], [18], [19]; navigation and routing applications like traffic estimation [20] and pedestrian, bicycle, and wheelchair routing [21], [22]; detection of buildings and roads in aerial imagery [23], [24]; 3D city modelling [25]; indoor mapping [26]; and location-based map services [27]. ...
Article
OpenStreetMap (OSM) is a community-based, freely available, editable map service created as an alternative to authoritative sources. Given that it is edited mainly by volunteers with different mapping skills, the completeness and quality of its annotations are heterogeneous across different geographical locations. Despite that, OSM has been widely used in several applications in geosciences, Earth observation, and environmental sciences. In this article, we review recent methods based on machine learning to improve and use OSM data. Such methods aim to either 1) improve the coverage and quality of OSM layers, typically by using geographic information systems (GISs) and remote sensing technologies, or 2) use the existing OSM layers to train models based on image data to serve applications such as navigation and land use classification. We believe that OSM (as well as other sources of open land maps) can change the way we interpret remote sensing data and that the synergy with machine learning can scale participatory mapmaking and its quality to the level needed for global and up-to-date land mapping. A preliminary version of this manuscript was presented in [120].
... Section 2.2 discusses the completeness of OSM with respect to street networks being generally very good, but with poor Non Quantitative Attribute Completeness. In addition, OSM data have generally poor quality for routing, with the exception of a few regions, primarily in Europe (Schmitz et al., 2008;Neis et al., 2012). We therefore aimed at designing MIA with the least amount of data reliance as possible. ...
Article
Full-text available
Missing data in Volunteered Geographic Information (VGI) are an unavoidable consequence of the data collection by non-experts, guided by only vague and informal mapping guidelines. While various Missing Value Imputation (MVI) techniques have been proposed as data cleansing strategies, they have primarily targeted numerical data attributes in non-spatial databases. There remains a significant gap in methods for imputing nominal attribute values (e.g., Street name) in map databases. Here, we present an imputation algorithm named Membership Imputation Algorithm (MIA), targeting spatial databases and enabling to impute nominal values in spatially referenced records. Targeting membership classes of spatial objects, MIA harnesses spatio-temporal characteristics of data and proposes efficient heuristics to impute the class name (i.e., a membership). Experimental results show that the proposed algorithm is able to impute the membership with high levels of accuracy (over 94\%) when assigning Street Names, across highly diverse regional contexts. MIA is effective in challenging spatial contexts such as street intersections. Our research serves as a first step in highlighting the effectiveness of spatio-temporal measures as a key driver for nominal imputation techniques.
... OSM has received considerable attention in the last decade as it provides an alternative to commercial and authoritative data (Arsanjani et al. 2015). OSM datasets have been used in various domains such as disaster relief in Haiti (Zook et al. 2010;Soden and Palen 2014), fine resolution population estimations (Bakillah et al. 2014), updating of Digital Elevation Models combining up-to-date OSM data with high-resolution provided by the Airborne Laser Scanning (Klonner et al. 2015), and routing (Schmitz et al. 2008;Goetz and Zipf 2012;Neis 2015). ...
Article
Online mapping providers offer unprecedented access to spatial data and analytical tools; however, the number of analytical queries that can be requested is usually limited. As such, Volunteered Geographic Information (VGI) services offer a viable alternative, provided that the quality of the underlying spatialtheir data is adequate. In this paper, we evaluate the agreement in travel impedance between estimates from MapQuest Open, which embraces OpenStreetMap (OSM) data–a is based on VGI datasetfrom OpenStreetMap (OSM), and estimates from two other popular commercial providers, namely Google Maps™ and ArcGIS™ Online. Our framework is articulated around three components, which simulates potentialcalculates shortest routes, estimates their travel impedance using a routing service Application Program Interface (API), and extracts the average number of contributors for each route. We develop an experimental setup with a simulated dataset for the state of North Carolina. Our results suggest a strong correlation of travel impedance among all three road network providers. and that travel impedanceThe agreement is the greatest in areas with a denser road network and the smallest for routes of shorter distances. Most importantly, tTravel estimates from MapQuest Open are nearly identical to both commercial providers when the average number of OSM contributors along the route is larger. The latter finding contributes to a growing body of literature on Linus’s law, recognizing that a larger group of contributors holds the potential to validate and correct inherent errors to the source dataset.
... Recently, a Visibility algorithm has been implemented into a new version of the route planning service OpenRouteService (www.openrouteservice.org) (Schmitz et al. 2008), since this optimization is particularly useful for the pedestrian and wheelchair route planning profiles (Neis and Another possible use case of open space algorithms could also be to enhance a road data-set itself with additional edges, which would be an option to easily integrate the presented approach into a variety of different routing engines, without the need for re-implementation of the algorithms in each engine. ...
Article
Full-text available
Finding the shortest path through open spaces is a well-known challenge for pedestrian routing engines. A common solution is routing on the open space boundary, which causes in most cases an unnecessarily long route. A possible alternative is to create a subgraph within the open space. This paper assesses this approach and investigates its implications for routing engines. A number of algorithms (Grid, Spider-Grid, Visibility, Delaunay, Voronoi, Skeleton) have been evaluated by four different criteria: (i) Number of additional created graph edges, (ii) additional graph creation time, (iii) route computation time, (iv) routing quality. We show that each algorithm has advantages and disadvantages depending on the use case. We identify the algorithms Visibility with a reduced number of edges in the subgraph and Spider-Grid with a large grid size to be a good compromise in many scenarios.
Article
Full-text available
Effective functioning of sewer systems is critical for the everyday life of people in the urban environment. This is achieved, among other things, by the means of regular, planned maintenance of these systems. A large water utility would normally have several maintenance teams (or crews) at their disposal who can perform related jobs at different locations in the company area and with different levels of priority. This paper presents a new methodology for the optimisation of related maintenance schedules resulting in clear prioritisation of the ordering of maintenance tasks for crews. The scheduling problem is formulated as a multi-objective optimisation problem with the following three objectives, namely the minimisation of the total maintenance cost, the minimisation of travel times of maintenance teams and the maximisation of the job's priority score, all over a pre-defined scheduling horizon. The optimisation problem is solved using the Nondominated Sorting Genetic Algorithm-II (NSGA-II) optimisation method. The results obtained from a real-life UK case study demonstrate that the new methodology can determine optimal, low-cost maintenance schedules in a computationally efficient manner when compared to the corresponding existing company schedules. Daily productivity of maintenance teams in terms of number of jobs completed improved by 26% when the methodology was applied to scheduling in the case study. Given this, the method has the potential to be applied within water utilities and the water utility Welsh Water (Dŵr Cymru Welsh Water (DCWW)) is currently implementing it into their systems. HIGHLIGHTS A new methodology for optimised scheduling of maintenance activities in sewer systems is presented.; The new methodology is capable of determining optimal, low-cost maintenance schedules that are superior to the existing ones.; When compared to existing company schedules, the new methodology has increased the daily productivity of maintenance teams in terms of jobs completed daily per crew.;
Article
Full-text available
OpenStreetMap (OSM) is currently the largest collection of volunteered geographic data, widely used in many projects as an alternative to or integrated with authoritative data. However, the quality of this data has been one of the obstacles to the widely use of this data. In this article, from among the elements related to the quality of volunteered geographic data, we have tried to examine the completeness of building block data in the OSM for Tehran metropolis. As completeness measures we apply two object-based and unit-based approaches that are frequently applied in similar studies. The findings of this study demonstrate that the estimation of OSM building completeness strongly differ between the approaches. The results demonstrate the high speed of evaluation of the unit-based approach and the higher accuracy of object-based methods. Moreover, the results for the unit-based method indicate that a unit-based comparison of the total number or area of buildings is highly sensitive to disparities in modeling. While the object-based methods have lower sensitive than disparities in modeling and if data have the appropriate positional accuracy, they will provide more accurate results for the completeness parameter. Therefore, the recommendation of this paper is to use an object-based method in quality assessment studies. In the end, based on the object-based approach, the parameter of completeness in the whole study area was calculated as 2.7%, which shows a low rate of completeness. When evaluating the results in closer detail it shows that the northern, central and eastern parts of Tehran are more complete than other parts. Also, in most regions of Tehran, more than 80% of the official data is not in the OSM dataset, which indicates that the official dataset is more complete than the OSM dataset.
Chapter
Today’s routing services provide routes that meet different needs and preferences of different users. To compute desired (optimal) routes, these services must support databases that contain accurate origin and destination locations, a high accuracy road network database, and an optimization algorithm. Origin and destination (O/D) locations are commonly collected by professional, commercial, and crowd sources via manual or automatic (geocoding) approaches. The routes computed for the same pairs of locations (O/D) obtained from different sources may be different. Considering the increased interest in collecting points of interest (POIs) through crowdsourcing, in this chapter, we address this research question: Are the routes computed using crowdsourced POIs (as O/D) reliable? To address this question, we conducted experiments where routes (shortest and fastest) computed using crowdsourced POIs (e.g., through OpenStreetMap) were compared with the routes computed using POIs obtained from professional and commercial sources. Metrics including route length, travel time, Euclidian distance, and number of road segments were used in the comparisons. The results reveal that, in general, though there are no significant differences between the routes, differences usually occur at or near origins and destinations.
Article
Full-text available
Die OpenFloodRiskMap (OFRM) ist ein Entscheidungsunterstützungssystem, welches Entscheidungsträger in der Alarm- und Einsatzplanung und im Hochwasserfall in der Identifi- zierung Kritischer Infrastrukturen (KI) und Navigation zu KI unterstützt. Durch die Zusammenarbeit mit verschiedenen Kommunen wurde die OFRM an deren Bedürfnisse im Hochwassermanagement angepasst, zudem wurden die frei verfügbaren OpenStreetMap-Daten als allgemein zugängliche Da- tengrundlage integriert. Im Praxisbericht wird der Beitrag der OFRM zu Hochwassermanagement an- hand des Fallbeispiels Evakuierung veranschaulicht.
Article
Full-text available
With the ubiquity of advanced web technologies and location-sensing hand held devices, citizens regardless of their knowledge or expertise, are able to produce spatial information. This phenomenon is known as volunteered geographic information (VGI). During the past decade VGI has been used as a data source supporting a wide range of services, such as environmental monitoring, events reporting, human movement analysis, disaster management, etc. However, these volunteer-contributed data also come with varying quality. Reasons for this are: data is produced by heterogeneous contributors, using various technologies and tools, having different level of details and precision, serving heterogeneous purposes, and a lack of gatekeepers. Crowd-sourcing, social, and geographic approaches have been proposed and later followed to develop appropriate methods to assess the quality measures and indicators of VGI. In this article, we review various quality measures and indicators for selected types of VGI and existing quality assessment methods. As an outcome, the article presents a classification of VGI with current methods utilized to assess the quality of selected types of VGI. Through these findings, we introduce data mining as an additional approach for quality handling in VGI.
Article
Full-text available
In this paper we show how to efficiently integrate traditional GIS data into terrain models in order to generate complete 3D maps with little overhead for textures. The results meet the requirements for the Web 3D Service (W3DS), a proposal for the standardization for delivering 3D web maps. Our approach is designed to create fully vectorized 3D scenes that deliver the best possible quality and do not require dynamic texture generation and handling. We describe the mesh operations for integrating polygonal GIS data like forests, parks, buildings blocks, or streets into the terrain mesh and compare the results with a texture based approach.
Article
In recent months there has been an explosion of interest in using the Web to create, assemble, and disseminate geographic information provided voluntarily by individuals. Sites such as Wikimapia and OpenStreetMap are empowering citizens to create a global patchwork of geographic information, while Google Earth and other virtual globes are encouraging volunteers to develop interesting applications using their own data. I review this phenomenon, and examine associated issues: what drives people to do this, how accurate are the results, will they threaten individual privacy, and how can they augment more conventional sources? I compare this new phenomenon to more traditional citizen science and the role of the amateur in geographic observation.
DEM Processing and 3D Navigation using open standards and free geo data
  • A Schilling
  • S Lanig
  • P Neis
  • A Zipf
Schilling, A., Lanig, S., Neis, P. & Zipf, A. (2008). DEM Processing and 3D Navigation using open standards and free geo data. In: 3rd Int.Workshop on 3D Geo-Information. Seoul, South Korea.
Location Based Services mit OpenStreetMap Daten
  • P P Neis
  • A Zipf
Neis, P. (2008): Location Based Services mit OpenStreetMap Daten. Master Thesis. University of applied sciences Mainz, Department of Geoinformatics and Surveying Neis, P. and Zipf, A. (2008): OpenRouteService.org – Combining Open Standards and Open Geodata. The State of the Map. 2nd Open Street Maps Conference, Limerik. Ireland.