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Conflation of Geospatial Data

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Synonyms

Computer cartography; Geospatial data alignment; Geospatial data reconciliation; Imagery conflation

Definition

Geospatial data conflation is the compilation or reconciliation of two different geospatial datasets covering overlapping regions (Saalfeld, 1988). In general, the goal of conflation is to combine the best quality elements of both datasets to create a composite dataset that is better than either of them. The consolidated dataset can then provide additional information that cannot be gathered from any single dataset.

Based on the types of geospatial datasets dealt with, the conflation technologies can be categorized into the following three groups:

  • Vector to vector data conflation: A typical example is the conflation of two road networks of different accuracy levels. Figure 1shows a concrete example to produce a superior dataset by integrating two road vector datasets: road network from US Census TIGER/Line files, and road network from the department of...

Keywords

  • Voronoi Diagram
  • Vector Data
  • Delaunay Triangulation
  • Geospatial Data
  • Raster Dataset

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Conflation of Geospatial Data, Fig. 1
Conflation of Geospatial Data, Fig. 2
Conflation of Geospatial Data, Fig. 3
Conflation of Geospatial Data, Fig. 4
Conflation of Geospatial Data, Fig. 5

References

  • Agouris P, Stefanidis A, Gyftakis S (2001) Differential snakes for change detection in road segments. Photogramm Eng Remote Sens 67(12):1391–1399

    Google Scholar 

  • Chen C-C, Knoblock CA, Shahabi C, Chiang Y-Y, Thakkar S (2004a) Automatically and accurately conflating orthoimagery and street maps. In: Proceedings of the 12th ACM international symposium on advances in geographic information systems, Washington, DC

    Google Scholar 

  • Chen C-C, Shahabi C, Knoblock CA (2004b) Utilizing road network data for automatic identification of road intersections from high resolution color orthoimagery. In: Proceedings of the second workshop on spatiotemporal database management (co-located with VLDB2004), Toronto

    Google Scholar 

  • Chen C-C, Knoblock CA, Shahabi C (2006a) Automatically conflating road vector data with orthoimagery. Geoinformatica 10(4):495–530

    CrossRef  Google Scholar 

  • Chen C-C, Shahabi C, Knoblock CA, Kolahdouzan M (2006b) Automatically and efficiently matching road networks with spatial attributes in unknown geometry systems. In: Proceedings of the third workshop on spatiotemporal database management (co-located with VLDB2006), Seoul

    Google Scholar 

  • Cobb M, Chung MJ, Miller V, Foley H III, Petry FE, Shaw KB (1998) A rule-based approach for the conflation of attributed vector data. GeoInformatica 2(1):7–35

    CrossRef  Google Scholar 

  • Dare P, Dowman I (2000) A new approach to automatic feature based registration of SAR and SPOT images. Int Arch Photogramm Remote Sens 33(B2):125–130

    Google Scholar 

  • Eidenbenz C, Kaser C, Baltsavias E (2000) ATOMI – automated reconstruction of topographic objects from aerial images using vectorized map information. Int Arch Photogramm Remote Sens 33(Part 3/1):462–471

    Google Scholar 

  • Filin S, Doytsher Y (2000) A linear conflation approach for the integration of photogrammetric information and GIS data. Int Arch Photogramm Remote Sens 33:282–288

    Google Scholar 

  • Flavie M, Fortier A, Ziou D, Armenakis C, Wang S (2000) Automated updating of road information from aerial images. In: Proceedings of American society photogrammetry and remote sensing conference, Amsterdam

    Google Scholar 

  • Kass M, Witkin A, Terzopoulos D (1987) Snakes: active contour models. Int J Comput Vis 1(4):321– 331

    CrossRef  Google Scholar 

  • Saalfeld A (1988) Conflation: automated map compilation. Int J Geogr Inf Sci 2(3):217–228

    CrossRef  Google Scholar 

  • Seedahmed G, Martucci L (2002) Automated image registration using geometrical invariant parameter space clustering (GIPSC). In: Proceedings of the photogrammetric computer vision, Graz

    Google Scholar 

  • Walter V, Fritsch D (1999) Matching spatial data sets: a statistical approach. Int J Geogr Inf Sci 5(1):445–473

    CrossRef  Google Scholar 

  • Ware JM, Jones CB (1998) Matching and aligning features in overlayed coverages. In: Proceedings of the 6th ACM symposium on geographic information systems, Washington, DC

    Google Scholar 

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© 2016 Springer International Publishing Switzerland

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Chen, CC., Knoblock, C.C. (2016). Conflation of Geospatial Data. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-23519-6_182-2

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  • DOI: https://doi.org/10.1007/978-3-319-23519-6_182-2

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  • Publisher Name: Springer, Cham

  • Online ISBN: 978-3-319-23519-6

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