Skip to main content

Integrating and Generalising Volunteered Geographic Information

  • Chapter
  • First Online:
Abstracting Geographic Information in a Data Rich World

Abstract

The availability of spatial data on the web has greatly increased through the availability of user-generated community data and geosensor networks. The integration of such multi-source data is providing promising opportunities, as integrated information is richer than can be found in only one data source, but also poses new challenges due to the heterogeneity of the data, the differences in quality and in respect of tag-based semantic modelling. The chapter describes approaches for the integration of official and informal sources, and discusses the impact of integrating user-generated data on automated generalisation and visualisation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    www.maps4debugs.openstreetmap.de

  2. 2.

    Note that the notion of aggregation is used here to describe the grouping of similar instances of the same feature class to a new, combined representative object.

  3. 3.

    http://wiki.openstreetmap.org/wiki/Tag:boundary%3Dadministrative#10_admin_level_values_for_specific_countries

  4. 4.

    http://wiki.openstreetmap.org/wiki/Maps

  5. 5.

    http://wiki.openstreetmap.org/wiki/Renderers_feature_list

  6. 6.

    http://wiki.openstreetmap.org/wiki/Main_Page

  7. 7.

    http://www.osmfoundation.org/wiki/Main_Page

  8. 8.

    See Footnote 7

  9. 9.

    http://munin.openstreetmap.org/openstreetmap/yevaud.openstreetmap/renderd_queue.html

  10. 10.

    https://help.openstreetmap.org/questions/178/how-often-does-the-main-mapnik-map-get-updated

  11. 11.

    http://wiki.openstreetmap.org/wiki/Map_Features

  12. 12.

    http://wiki.openstreetmap.org/wiki/Proposed_features

  13. 13.

    http://wiki.openstreetmap.org/wiki/Tag:medical%3Daed

  14. 14.

    http://www.geofabrik.de/en/index.html

  15. 15.

    http://blog.geofabrik.de/de/?p=75

  16. 16.

    http://wiki.openstreetmap.org/wiki/API

  17. 17.

    http://overpass-api.de/

  18. 18.

    http://wiki.openstreetmap.org/wiki/QuadTiles

  19. 19.

    http://mapnik.org/

References

  • Alt H, Efrat A, Rote G, Wenk C (2003) Matching planar maps. In: Proceedings of the fourteenth annual ACM-SIAM symposium on discrete algorithms (SODA '03). Society for industrial and applied mathematics. Philadelphia, PA, USA, pp 589–598

    Google Scholar 

  • Atkinson GM, Wald DJ (2007) “Did you feel it?” intensity data: a surprisingly good measure of earthquake ground motion. Seismol Res Lett 78(3):362–368

    Article  Google Scholar 

  • Balley S, Parent C, Spaccapietra S (2004) Modelling geographic data with multiple representations. Int J Geogr Inf Sci 18(4):327–352

    Article  Google Scholar 

  • Bereuter P, Weibel R and Burghardt D (2012) Content zooming and exploration for mobile maps. In: Proceedings 15th AGILE international conference on geographic information science, Avignon, France

    Google Scholar 

  • Bobzien M, Petzold I, Burghardt D (2007) Automated derivation of a 1:300,000 topographic map from swiss dlm vector 200. In: Proceedings of the international cartographic congress, Moscow, Russia, International cartographic association

    Google Scholar 

  • Brassel KE, Weibel R (1988) A review and conceptional framework of automated map generalization. Int J Geogr Inf Syst 2(3):224–229

    Google Scholar 

  • Bröring A, Echterhoff J, Jirka S, Simonis I, Everding T, Stasch C, Liang S, Lemmens R (2011) New generation sensor web enablement. Sens Open Access J 11(3):2652–2699

    Google Scholar 

  • Cao L, Krumm J (2009) From GPS traces to a routable road map. In: 17th ACM SIGSPATIAL International conference on advances in geographic information systems (ACM SIGSPATIAL GIS 2009), November 4-6, 2009. Seattle, WA, pp 3–12

    Google Scholar 

  • Carver S (2001) Public participation using web-based GIS. Environ Plan B: Plan Des 28(6):803–804. doi:10.1068/b2806ed

  • Chen Y, Krumm J (2010) Probabilistic modeling of traffic lanes from GPS traces. In: 18th ACM SIGSPATIAL international conference on advances in geographic information systems (ACM SIGSPATIAL GIS 2010), November 2-5, 2010. San Jose, CA

    Google Scholar 

  • Codescu M, Horsinka G, Kutz O, Mossakowski T, Rau R (2011) OSMonto—an ontology of OpenStreetMap tags. http://www.informatik.uni-bremen.de/~okutz/osmonto.pdf. Accessed 27 Feb 2013

  • Coleman DJ, Geogiadou Y, Labonte J (2009) Volunteered geographic information: the nature and motivation of producers. Int J Spat Data Infrastruct Res 4:332–358

    Google Scholar 

  • Dahinden T, Sester M (2009) Categorization of linear objects for map generalization using geocoded articles of a knowledge repository. In: Proceedings of the international workshop presenting spatial information: granularity, relevance, and integration, held in conjunction with the conference on spatial information theory, COSIT

    Google Scholar 

  • Davies JJ, Beresford AR, Hopper A (2006) Scalable, distributed, real-time map generation. IEEE Pervasive Comput 5(4):47–54

    Article  Google Scholar 

  • Dalyot S, Dahinden T, Schulze, MJ, Boljen, J, Sester, M (2012) Geometrical adjustment towards the alignment of vector databases. In: ISPRS annals of photogrammetry, remote sensing and spatial information sciences, vol. I–4, pp. 13–18

    Google Scholar 

  • Devillers R, Jeansoulin R (2006) Fundamentals of spatial data quality. ISTE, London

    Book  Google Scholar 

  • Devillers R, Bédard Y, Jeansoulin R, Moulin B (2007) Towards spatial data quality information analysis tools for experts assessing the fitness for use of spatial data. IJGIS 21(3):261–282

    Google Scholar 

  • Devogele T, Trevisan J, Raynal L (1996) Building a multiscale database with scale-transition relationships. In: Proceedings of the 7th international symposium on spatial data handling, advances in GIS research II. Delft, The Netherlands, pp 6.19–6.33

    Google Scholar 

  • Duckham M (2012) Decentralized spatial computing: foundations of geosensor networks. Springer, Berlin

    Google Scholar 

  • Fink M, Haunert JH, Schulz A, Spoerhase J, Wolff A (2012) Algorithms for labeling focus regions. Vis Comput Graph IEEE Trans 18(12):2583–2592

    Article  Google Scholar 

  • Fritz S, McCallum I, Schill C, Perger C, See L, Schepaschenko D, Van der Velde M, Kraxner F, Obersteiner M (2012) Geo-Wiki: an online platform for improving global land cover. Environ Model Softw 31:110–123

    Article  Google Scholar 

  • Gartner G (2012) openemotionmap.org—emotional response to space as an additional concept in cartography, international archives of the photogrammetry, remote sensing and spatial information sciences, vol XXXIX-B4

    Google Scholar 

  • Gervais M, Bedard Y, Levesque M, Bernier E, Devillers R (2009) Data quality issues and geographic knowledge discovery, pp 99–116

    Google Scholar 

  • Girres JF, Touya G (2010) Quality assessment of the French OpenStreetMap dataset. Trans GIS 14(4):435–459

    Article  Google Scholar 

  • Goodchild MF (2007) Citizens as sensors: the world of volunteered geography. GeoJournal 69:211–221

    Article  Google Scholar 

  • Goodchild MF, Li L (2012) Assuring the quality of volunteered geographic information. Spat Stat 1:110–120

    Article  Google Scholar 

  • Grünreich D (1992) ATKIS—a topographic information system as a basis for GIS and digital cartography in Germany. In: Vinken R (ed) From digital map series in geosciences to geo-information systems. Geologisches Jahrbuch, Federal institute of geosciences and resources, Hannover, vol A(122), pp 207–216

    Google Scholar 

  • Guptill SC, Morrison J (1995) Elements of spatial data quality. Elsevier Science, New York

    Google Scholar 

  • Hahmann S, Burghardt D (2010) Linked data—a multiple representation database at web scale? In: Proceedings of the 13th ICA workshop on generalisation and multiple representation, Zurich, Switzerland

    Google Scholar 

  • Haklay M (2010) How good is volunteered geographical information? A comparative study of OpenStreetMap and ordnance survey datasets. Environ Plann B: Plann Des 37(4):682–703

    Article  Google Scholar 

  • Haklay M, Basiouka S, Antoniou V, Ather A (2010) How many volunteers does it take to map an area well? The validity of Linus’ law to volunteered geographic information. Cartographic J 47(4):315–322

    Article  Google Scholar 

  • Hampe M, Sester M, Harrie L (2004) Multiple representation databases to support visualisation on mobile devices, international archives of photogrammetry and remote sensing, vol 35. Istanbul, Turkey

    Google Scholar 

  • Haunert JH, Budig B (2012) An algorithm for map matching given incomplete road data. In: Proceedings of the 20th ACM SIGSPATIAL international conference on advances in geographic information systems (ACM-GIS’12), pp 510–513

    Google Scholar 

  • Heipke C (2010) Crowdsourcing geospatial data. ISPRS J Photogrammetry Remote Sens 65(6):550–557. doi:10.1016/j.isprsjprs.2010.06.005

    Google Scholar 

  • Helbich M, Amelunxen C, Neis P (2012) Comparative spatial analysis of positional accuracy of openstreetmap and proprietary geodata. Int. GI_Forum 2012. Salzburg, Austria

    Google Scholar 

  • Henson C, Pschorr J, Sheth A, Thirunarayan K (2009) SemSOS semantic sensor observation service. International symposium on collaborative technologies and systems

    Google Scholar 

  • Hollenstein L, Purves R (2010) Exploring place through user-generated content: using Flickr tags to describe city cores. J Spat Inf Sci 1(2010):21–48

    Google Scholar 

  • Jaara K, Duchêne C, Ruas A (2011) Toward the generalisation of cartographic mashups: taking into account the dependency between the thematic data and the reference data throughout the process of automatic generalisation, 14th ICA workshop on generalisation and multiple representation, Paris, France, 30 June–1 July 2011

    Google Scholar 

  • Jokar Arsanjani J, Barron C, Bakillah M, Helbich M (2013a) Assessing the quality of OpenStreetMap contributors together with their contributions. In: Proceedings of the 16th AGILE conference, Leuven, Belgium

    Google Scholar 

  • Jokar Arsanjani J, Helbich M, Bakillah M, Hagenauer J, Zipf A (2013b) Towards mapping land use patterns from volunteered geographic information. Int J Geogr Inf Sci. doi:10.1080/13658816.2013.800871

    Google Scholar 

  • Jones CB, Purves P, Clough D, Joho H (2008) Modelling vague places with knowledge from the web. Int J Geogr Inf Sci 22(10):1045–1065

    Article  Google Scholar 

  • Kieler B, Huang W, Haunert JH, Jiang J (2009) Matching river datasets of different scales. Advances in GIScience. In: Proceedings of 12th AGILE conference on GIScience, lecture notes in Geoinformation and cartography, Springer, Berlin, pp 135–154

    Google Scholar 

  • Kilpeläinen T (1992) Multiple representations and knowledge-based generalization of topographical data. In: Waugh TC, Healey RG (eds) Advances in GIS research. In: Proceedings of the 6th international symposium on spatial data handling, IGU commission on GIS and association for geographic information, Edinburgh, GB, pp 882–893

    Google Scholar 

  • Kinkeldey C, Schiewe J (2012) Visualisierung thematischer Unsicherheiten mit “noise annotation lines”. Kartographische Nachrichten 62(5):241–249

    Google Scholar 

  • Lüscher P, Weibel R (2013) Exploiting empirical knowledge for automatic delineation of city centres from large-scale topographic databases. Comput Environ Urban Syst 37:18–34. doi:10.1016/j.compenvurbsys.2012.07.001

    Article  Google Scholar 

  • MacEachren AM (1992) Visualizing uncertain information. In: cartographic perspectives, vol 13, p 10

    Google Scholar 

  • Mackaness W, Ruas A, Sarjakoski T (2007) Generalisation of geographic information: cartographic modelling and applications. Oxford, Elsevier

    Google Scholar 

  • Mackaness WA, Chaudhry O (2013) Assessing the veracity of TF-IDF for extracting place semantics from Flickr tags transactions in GIS (in press)

    Google Scholar 

  • McMaster RB, Shea KS (1992) Generalization in digital cartography. Association of American Geographers, Washington

    Google Scholar 

  • Mondzech J, Sester M (2011) Quality analysis of OpenStreetMap data based on application needs. Cartographica 46(2):115–125

    Article  Google Scholar 

  • Mustière S, Devogele T (2008) Matching networks with different levels of detail. GeoInformatica 12(4):435–453

    Article  Google Scholar 

  • Neis P, Zielstra D, Zipf A (2012) The street network evolution of crowdsourced maps: OpenStreetMap in Germany 2007–2011. Future Internet 4(1):1–21

    Google Scholar 

  • Newson P and Krumm J (2009) Hidden markov map matching through noise and sparseness. In: Proceedings of the 17th ACM SIGSPATIAL international conference on advances in geographic information systems (GIS ‘09), pp 336–343

    Google Scholar 

  • Noy N (2004) Semantic integration: a survey of ontology based approaches. SIGMOD Rec 33:65–70

    Google Scholar 

  • Paelke V, Dahinden T, Eggert D, Mondzech J (2012) Location based context awareness through tag‐cloud visualizations. Adv Geo‐Spatial Inf Sci (CRC Press)

    Google Scholar 

  • Poser K, Dransch D (2010) Volunteered geographic information for disaster management with application to rapid flood damage estimation. Geomatica 64(1):89–98

    Google Scholar 

  • Quddus MA, Ochieng WY, Noland RB (2007) Current map-matching algorithms for transport applications: state-of-the art and future research directions. Transp Res Part C: Emerg Technol 15(5):312–328

    Article  Google Scholar 

  • Rabiner LR, Juang BH (1986) An introduction to hidden Markov models. IEEE ASSP Mag 3(1):4–15

    Article  Google Scholar 

  • Rak A, Coleman D, Nichols S (2012) Legal liability concerns surrounding volunteered geographic information applicable to Canada. In: Rajabifard, A, Coleman D (eds) Spatially enabling government, industry and citizens, USA: GSDI Association Press, pp 125–143. http://www.gsdi.org/gsdiconf/gsdi13/papers/256.pdf

  • Rambaldi G, Mccall M, Weiner D, Mbile P, Kyem P (2004) Participatory GIS. http://www.iapad.org/participatory_gis.htm

  • Ramm F (2012) Am Puls der Zeit—Minütliche updates bei OpenStreetMap. Paper presented at the FOSSGIS 2012, Dessau

    Google Scholar 

  • Ramm F, Topf J, Chilton S (eds) (2010) OpenStreetMap: using and enhancing the free map of the world. UIT Cambridge, Cambridge

    Google Scholar 

  • Roick O, Heuser S (2013) Location based social networks—definition, current state of the art and research agenda. Trans GIS. doi:10.1111/tgis.12032

    Google Scholar 

  • Rouse LJ, Bergeron SJ, Harris TM (2007) Participating in the geospatial web: collaborative mapping, social networks and participatory GIS. In: Scharl A, Tochtermann K (eds) The Geospatial Web. Springer, London, pp 153–158. Retrieved from http://dx.doi.org/10.1007/978-1-84628-827-2_14

  • Safra E, Doytsher Y (2006) Integration of multiple geo-spatial datasets. ASPRS 2006 annual conference, Reno, Nevada

    Google Scholar 

  • Samet H (eds) (2005) Foundations of multidimensional and metric data structures. The Morgan Kaufmann series in computer graphics and geometric modeling. Morgan Kaufmann Publishers Inc. San Francisco, CA, USA

    Google Scholar 

  • Sayda F (2005) Involving LBS users in data acquisition and update. In: Proceedings of the AGILE, Portugal

    Google Scholar 

  • Schroedl S, Wagstaff K, Rogers S, Langley P, Wilson C (2004) Mining GPS traces for map refinement. Data Min Knowl Disc 9(1):59–87

    Article  Google Scholar 

  • Scofield RP, Christie D, Sagar PM, Sullivan B (2012) eBird and avifaunal monitoring by the ornithological society of New Zealand. NZ J Ecol 36:279–286

    Google Scholar 

  • Senaratne H, Gerharz L (2011) An assessment and categorisation of quantitative uncertainty visualisation methods. The 14th AGILE international conference on geographic information science, Utrecht, Netherlands, 18–21 April 2011

    Google Scholar 

  • Sengstock C, Gertz M (2012) Latent geographic feature extraction from social media. In: Proceedings of the 20th ACM SIGSPATIAL international conference on advances in geographic information systems, Redondo Beach

    Google Scholar 

  • Sheeren D, Mustière S, Zucker JD (2009) A data-mining approach for assessing consistency between multiple representations in spatial databases. Int J Geogr Inf Sci 23(8):961–992

    Article  Google Scholar 

  • Siebritz L, Sithole G, Zlatanova S (2012) Assessment of the homogeneity of volunteered geographic information in South Africa. In: international archives of the photogrammetry, remote sensing and spatial information sciences, vol 39-B4. XXII ISPRS Congress, Melbourne, Australia

    Google Scholar 

  • Siriba DN, Dalyot S, Sester M (2012) Geometric quality enhancement of legacy graphical cadastral datasets through thin plate splines transformation. Surv Revi 44(325):91–101

    Google Scholar 

  • Slingsby A, Dykes J, Wood J, Clarke K (2007) Mashup cartography: cartographic issues of using Google earth for tag maps. ICA commission on maps and the internet, ICA, Warsaw, Poland, pp 79–93

    Google Scholar 

  • Smart PD, Quinn JA, Jones CB (2011) City model enrichment. ISPRS J Photogram Remote Sens 6(2):223–234

    Article  Google Scholar 

  • Stefanidis A, Nittel S (2004) Geosensor networks. CRC Press, Boca Raton

    Google Scholar 

  • Stigmar H (2005) Matching route data and topographic data in a real-time environment. In: Hauska H, Tveite H (eds) ScanGIS’2005—proceedings of the 10th scandinavian research conference on geographical information sciences, Stockholm, Sweden, pp 89–107

    Google Scholar 

  • Stoter JE, Meijers M, van Oosterom P, Grünreich D, Kraak MJ (2010) Applying DLM and DCM concepts in a multi—scale data environment. Paper presented at GDI 2010: a symposium on generalization and data integration, Boulder, USA, 20–22 June 2010

    Google Scholar 

  • Sullivan BL, Wood CL, Iliff MJ, Bonney RE, Fink D, Kelling S (2009) eBird: a citizen-based bird observation network in the biological sciences. Biol Conserv 142(10):2282–2292

    Article  Google Scholar 

  • Surowiecki J (ed) (2004) The wisdom of crowds: why the many are smarter than the few and how collective wisdom shapes business, economies. Societies and Nations Little, Doubleday

    Google Scholar 

  • Tauscher S, Neumann K (2012) Combining web map services and opinion mining to generate sentiment maps of touristic locations, symposium on service oriented mapping, Wien, JOBSTMedia Präsentation Management Verlag, pp 277–286, 11/2012

    Google Scholar 

  • Touya G (2012) What is the level of detail of OpenStreetMap? Role of volunteered geographic information in advancing science: quality and credibility. In: conjunction with GIScience 2012, 18 Sept 2012

    Google Scholar 

  • van Oort P (2006) Spatial data quality: from description to application. PhD Thesis, Wageningen University, The Netherlands

    Google Scholar 

  • Volz S (2005) Data-driven Matching of Geospatial Schemas. In: Cohn AG, Mark DM (eds) Spatial information theory. Proceedings of the international conference on spatial information theory (COSIT '05), Ellicottville, NY. Lecture Notes in Computer Science 3693, pp. 115–132

    Google Scholar 

  • Walter V, Fritsch D (1999) Matching spatial data sets: a statistical approach. Int J Geogr Inf Sci 13(5): 445–473

    Google Scholar 

  • Warneke H, Schäfers M, Lipeck U, Bobrich J (2011) Matching-based map generalization by transferring geometric representations. In: Proceedings Geoinformatik 2011, Münster, pp 71–77

    Google Scholar 

  • Weibel R, Dutton G (2005) Generalizing spatial data and dealing with multiple representations. In: Longley P, Goodchild MF, Maguire DJ, Rhind DW (eds) Geographical information systems: principles, techniques, management and applications, 2nd edn (Abridged Edition). Wiley

    Google Scholar 

  • Yates D, Paquette S (2011) Emergency knowledge management and social media technologies: a case study of the 2010 Haitian earthquake. Int J Inf Manage 31(1):6–13

    Article  Google Scholar 

  • Yuan S, Tao C (1999) Development of conflation components. In: Proceedings of the international conference on geoinformatics and socioinformatics. Ann Arbor, MI, pp 1–12. http://www.umich.edu/yiinet/chinadata/geoim99/Proceedings/yuan_shuxin.pdf

  • Zhang Y, Yang B, Luan X (2012) Automated matching crowdsourcing road networks using probabilistic relaxation. In: ISPRS annals of photogrammetry, remote sensing and spatial information sciences, vol 1–4

    Google Scholar 

  • Zook M, Graham M, Shelton T, Gorman S (2010) Volunteered geographic information and crowdsourcing disaster relief: a case study of the haitian earthquake. World Med Health Policy 2:7–33. doi:10.2202/1948-4682.1069

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Monika Sester .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Sester, M., Jokar Arsanjani, J., Klammer, R., Burghardt, D., Haunert, JH. (2014). Integrating and Generalising Volunteered Geographic Information. In: Burghardt, D., Duchêne, C., Mackaness, W. (eds) Abstracting Geographic Information in a Data Rich World. Lecture Notes in Geoinformation and Cartography(). Springer, Cham. https://doi.org/10.1007/978-3-319-00203-3_5

Download citation

Publish with us

Policies and ethics