Skip to main content
Book cover

AGILE 2015 pp 181–197Cite as

Towards a Qualitative Assessment of Changes in Geographic Vector Datasets

  • 974 Accesses

Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Changes are immanent to digital geographic vector datasets. While the majority of changes nowadays are quantitatively detectable by the use of geographic information systems their classification and impact assessment on a qualitative level with respect to specific data usage scenarios is often neglected. To close this gap, this work proposes a classification approach consisting of three parts: (1) a taxonomy for classifying quantitatively detectable edits in digital feature datasets (e.g. attribute or geometry changes), (2) a taxonomy for classifying edits into qualitative and therefore meaningful change types (e.g. feature revision or identity change) and (3) a mapping scheme providing the link from quantitative to qualitative classifications. In the context of a case study with OpenStreetMap history data the proposed classification approach is used to automatically detect and classify feature changes with respect to two feature types, namely streets and buildings, leading to a refined mapping scheme for two selected data usage scenarios, namely vehicle routing and map rendering. Results show the applicability of the approach, especially for assessing the impact of feature changes on different data usage scenarios, and provide a useful foundation for any change detection task in the context of geographic vector datasets.

Keywords

  • Geographic vector data
  • Change detection
  • Qualitative assessment

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-16787-9_11
  • Chapter length: 17 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   119.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-16787-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book
USD   179.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  • Abd El-Kawy, O. R., et al. (2011). Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data. Applied Geography, 31(2), 483–494.

    CrossRef  Google Scholar 

  • Blaschke, T., et al. (2014). Geographic object-based image analysis—towards a new paradigm. ISPRS Journal of Photogrammetry and Remote Sensing (official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS)), 87(100), 180–191.

    CrossRef  Google Scholar 

  • Chawathe, S. S., et al. (1996). Change detection in hierarchically structured information. ACM SIGMOD Record, 25(2), 493–504.

    CrossRef  Google Scholar 

  • Chawathe, S. S., & Garcia-Molina, H. (1997). Meaningful change detection in structured data. ACM SIGMOD Record, 26(2), 26–37.

    CrossRef  Google Scholar 

  • Chen, G., et al. (2012). Object-based change detection. International Journal of Remote Sensing, 33(14), 4434–4457.

    CrossRef  Google Scholar 

  • Fonseca, F., et al. (2002). Semantic granularity in ontology-driven geographic information systems. AMAI Annals of Mathematics and Artificial Intelligence, 36(Special Issue on Spatial and Temporal Granularity), 121–151.

    CrossRef  Google Scholar 

  • Frontiera, P., Larson, R., & Radke, J. (2008). A comparison of geometric approaches to assessing spatial similarity for GIR. International Journal of Geographical Information Science, 22(3), 337–360.

    CrossRef  Google Scholar 

  • Goesseln, G., & Sester, M. (2005). Change detection and integration of topographic updates from ATKIS to geoscientific data sets. Next generation geospatial information (pp. 85–100).

    Google Scholar 

  • Gomes, J., & Velho, L. (1995). Abstraction paradigms for computer graphics. The Visual Computer, 11(5), 227–239.

    CrossRef  Google Scholar 

  • Hussain, M., et al. (2013). Change detection from remotely sensed images: From pixel-based to object-based approaches. ISPRS Journal of Photogrammetry and Remote Sensing, 80, 91–106.

    CrossRef  Google Scholar 

  • ISO. (2002). ISO 19101:2002 Geographic information—Reference model.

    Google Scholar 

  • Janowicz, K., Scheider, S., & Adams, B. (2013). A geo-semantics flyby. Reasoning web. Semantic technologies for intelligent data access. Lecture Notes in Computer Science (vol 8067, pp. 230–250).

    Google Scholar 

  • Klein, I., Gessner, U., & Kuenzer, C. (2012). Regional land cover mapping and change detection in Central Asia using MODIS time-series. Applied Geography, 35(1–2), 219–234.

    CrossRef  Google Scholar 

  • Kottman, C., & Reed, C. (2009). The OpenGIS abstract specification, topic 5: Features.

    Google Scholar 

  • Mooney, P., & Corcoran, P. (2012). Characteristics of heavily edited objects in OpenStreetMap. Future Internet, 4(1), 285–305.

    CrossRef  Google Scholar 

  • Qi, H. B., et al. (2010). Automated change detection for updating settlements at smaller-scale maps from updated larger-scale maps. Journal of Spatial Science, 55(1), 127–140.

    CrossRef  Google Scholar 

  • Redweik, R., & Becker, T. (2015). Change detection in CityGML documents. In 3D Geoinformation science. Lecture Notes in Geoinformation and Cartography 2015 (pp. 107–121). Springer International Publishing. .

    Google Scholar 

  • Reed, C. (2005). The OpenGIS abstract specifications, Topic 0—Overview.

    Google Scholar 

  • Rehrl, K., & et al. (2013). A conceptual model for analyzing contribution patterns in the context of VGI. In J. Krisp (Ed.), Progress in location-based services. Lecture Notes in Geoinformation and Cartography (pp. 373–388). Springer, Berlin.

    Google Scholar 

  • Singh, A. (1989). Review article digital change detection techniques using remotely-sensed data. International Journal of Remote Sensing, 10(6), 989–1003.

    CrossRef  Google Scholar 

  • Zielstra, D., et al. (2014). Areal delineation of home regions from contribution and editing patterns in OpenStreetMap. ISPRS International Journal of Geo-Information, 3(4), 1211–1233.

    CrossRef  Google Scholar 

Download references

Acknowledgments

This work was partly funded by the Austrian Federal Ministry for Transport, Innovation and Technology.

Author information

Authors and Affiliations

  1. Salzburg Research Forschungsgesellschaft mbH, Jakob-Haringer-Straße 5, 5020, Salzburg, Austria

    Karl Rehrl, Richard Brunauer & Simon Gröchenig

Authors
  1. Karl Rehrl
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Richard Brunauer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Simon Gröchenig
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Karl Rehrl .

Editor information

Editors and Affiliations

  1. NOVA IMS, Universidade Nova de Lisboa, Lisboa, Portugal

    Fernando Bacao

  2. School of Engineering, University of Minho, Guimarães, Portugal

    Maribel Yasmina Santos

  3. NOVA IMS, Universidade Nova de Lisboa, Lisboa, Portugal

    Marco Painho

Rights and permissions

Reprints and Permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Rehrl, K., Brunauer, R., Gröchenig, S. (2015). Towards a Qualitative Assessment of Changes in Geographic Vector Datasets. In: Bacao, F., Santos, M., Painho, M. (eds) AGILE 2015. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-16787-9_11

Download citation