Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
OSM Wiki “Elements”: http://wiki.openstreetmap.org/wiki/Elements
- 2.
OSM Wiki “Routing”: http://wiki.openstreetmap.org/wiki/Routing
- 3.
BGN Website: http://geonames.usgs.gov/domestic/index.html
- 4.
Geofabrik North America: http://download.geofabrik.de/north-america.html
- 5.
osmosis tool: http://wiki.openstreetmap.org/wiki/Osmosis
- 6.
OSM History Viewer site: http://osmhv.openstreetmap.de/index.jsp
References
Benner JG, Karimi HA (2013) Geo-crowdsourcing. In: Karimi HA (ed) Advanced location-based technologies and services. CRC Press, Boca Raton, pp 1–28
Beeri C, Kanza Y, Safra E, Sagiv Y (2004, August) Object fusion in geographic information systems. In: Proceedings of the thirtieth international conference on very large data bases, vol 30. VLDB Endowment, pp 816–827
Frizzelle BG, Evenson KR, Rodriguez DA, Laraia BA (2009) The importance of accurate road data for spatial applications in public health: customizing a road network. Int J Health Geogr 8(1)1
Girres JF, Touya G (2010) Quality assessment of the French openstreetmap dataset. Transactions in GIS 14(4):435–459
Goetz M Zipf A (2012) Openstreetmap in 3D – detailed insights on the current situation in Germany. In: Gensel J, Josselin D, Vandenbroucke D (eds) Multidisciplinary research on geographical information in Europe and beyond
Gyford P (2004) Euro Foo camp: steve coast – opentextbook & openstreetmap. In: Blog of Phil Gyford. http://www.gyford.com/phil/writing/2004/08/21/euro_foo_camp_st.php
Haklay M (2010) How good is volunteered geographical information? A comparative study of openstreetmap and ordinance survey datasets. Environ Plann B: Plann Des 37:682–703
Hochmair H, Zielstra D (2013) Development and completeness of points of interest in free and proprietary data sets: a Florida case study. GI Forum, 1–10 Salzburg, Austria, 3–5 July 2013.
Jokar Arsanjani J, Mooney P, Zipf A, Schauss A (2015) Quality assessment of the contributed land use information from OpenStreetMap versus authoritative datasets. In: Jokar Arsanjani J, Zipf A, Mooney P, Helbich M (eds) OpenStreetMap in GIScience: experiences, research, applications. Springer, Cham, pp 37–58. ISBN:978-3-319-14279-1
Kang H, Sehgal V, Getoor L (2007) GeoDDupe: a novel interface for interactive entity resolution in geospatial data. In: 2007 11th international conference information visualization (IV ‘07), July. Ieee 489–496 doi:10.1109/IV.2007.55
Karimi HA, Durcik M, Rasdorf W (2004) Evaluation of uncertainties associated with geocoding techniques. J Comput Aided Civ Infrastruct Eng 19(3)170–185
Karimi HA, Sharker MH, Roongpiboonsopit D (2011) Geocoding recommender: an algorithm to recommend optimal online geocoding services for applications. Trans GIS 15(6)869–886
NAVTEQ (2012) NAVSTREETS street data reference manual v4.4 1 April 2012 Nokia Location & Commerce, NAVTEQ, Chicago, Illinois, 1702 pp
Neis P, Zielstra D, Zipf A (2012) The street network evolution of crowdsourced maps: openStreetMap in Germany 2007–2011. Future Internet 4:1–21
Roongpiboonsopit D, Karimi HA (2010a) Comparative evaluation and analysis of online geocoding services. Int J Geogr Inf Sci 24(7)1081–1110
Roongpiboonsopit D, Karimi HA (2010b) Quality assessment of online street and rooftop geocoding services. Cartogr Geogr Inf Sci (CaGIS) J 37(4)
Schmitz S, Zipf A, Neis P (2008) New applications based on collaborative geodata – the case of routing. In: XXVIII INCA international congress on collaborative mapping and SpaceTechnology. Gandhinagar, Gujarat, India
Sehgal V, Getoor L, Viechnicki PD (2006) Entity resolution in geospatial data integration. In: Proceedings of the 14th annual ACM international symposium on advances in geographic information systems – GIS ‘06, vol 4. ACM Press, Arlington, p 83. doi:10.1145/1183471.1183486
Sharker M, Karimi HA (2014) Computing least air pollution exposure routes. Int J Geogr Inf Sci 28(2)343–362
USGS (United States Geological Survey). (1999). National map accuracy standards, USGS Fact Sheet 171–99, November 1999, Available: https://pubs.usgs.gov/fs/1999/0171/report.pdf
Zielstra D, Zipf A (2010) A comparative study of proprietary geodata and volunteered geographic information for Germany. AGILE 2010. Guimarães, Portugal
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Sharker, M.H., Benner, J.G., Karimi, H.A. (2017). On Reliability of Routes Computed Based on Crowdsourced Points of Interest. In: Leitner, M., Jokar Arsanjani, J. (eds) Citizen Empowered Mapping. Geotechnologies and the Environment, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-319-51629-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-51629-5_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-51628-8
Online ISBN: 978-3-319-51629-5
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)