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Measuring Arrangement Similarity Between Thematic Raster Databases Using a QuadTree-Based Approach

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GeoSpatial Semantics (GeoS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3799))

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Abstract

Measuring the degree of similarity between thematic raster databases is a common task widely used in remote sensing accuracy assessment, spatial model validation, and many other geospatial tasks. However, conventional similarity measures look only at point-to-point similarity; they are not designed to evaluate the similarity of shapes and arrangements of features within the databases being compared. This study proposes a technique of assessing arrangement similarity based on a comparison of quadtree representations of the maps being evaluated. Empirical assessment shows that the technique produces results that agree strongly with subjective evaluations of the similarity of artificial raster databases produced by a survey of map users.

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Author information

Authors and Affiliations

  1. Remote Sensing/GIS Program, Colorado State University, 113 Forestry Building, Fort Collins, Colorado, 80523-1472

    Denis J. Dean

Authors
  1. Denis J. Dean
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Editor information

Editors and Affiliations

  1. Center for Web Research, Chile

    M. Andrea Rodríguez

  2. Department of Computer Science, University of Illinois at Chicago, 851 South Morgan Street (M/C 152), 60607, Chicago, IL, USA

    Isabel Cruz

  3. National Polytechnic, Institute, Mexico, Centro de Investigacion en Computacion, Mexico

    Sergei Levashkin

  4. National Center for Geographic Information and Analysis and Department of Spatial Information Science and Engineering, University of Maine, Boardman Hall, 04469-5711, Orono, ME, USA

    Max J. Egenhofer

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© 2005 Springer-Verlag Berlin Heidelberg

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Dean, D.J. (2005). Measuring Arrangement Similarity Between Thematic Raster Databases Using a QuadTree-Based Approach. In: Rodríguez, M.A., Cruz, I., Levashkin, S., Egenhofer, M.J. (eds) GeoSpatial Semantics. GeoS 2005. Lecture Notes in Computer Science, vol 3799. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11586180_9

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  • DOI: https://doi.org/10.1007/11586180_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30288-9

  • Online ISBN: 978-3-540-32283-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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