Contributions to a quality description of areal objects in spatial data sets |
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| Affiliation: | 1. Institute of Photogrammetry, University of Bonn, Nußallee 15, D-53115 Bonn, Germany;2. Department of Geoinformation, TU Vienna, Gusshausstr. 27-29, A-1040 Vienna, Austria;1. Department of Critical Care Medicine and Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada;2. Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada;3. Center for Health Evaluation and Outcome Sciences and Division of Critical Care Medicine, St. Paul''s Hospital and University of British Columbia, Vancouver, British Columbia, Canada;4. Departments of Medicine, and Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada;5. BC Center for Palliative Care, Division of Palliative Care, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada;6. Fraser Health Authority, Surrey, British Columbia, Canada;7. Divisions of Critical Care and Palliative Care, Department of Medicine, University of Toronto, Toronto, Ontario, Canada;8. Divisions of Critical Care and Palliative Medicine, Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada;9. Division of Geriatric Medicine, Department of Medicine, Queen''s University, Kingston, Ontario, Canada;10. Department of Critical Care Medicine, Institute for Public Health, University of Calgary, Calgary, and Alberta Health Services-Calgary Zone, Calgary, Alberta, Canada;11. Department of Medicine, Queen''s University, Kingston, Ontario, Canada;1. Chemical and Biological Engineering Department, Montana State University, Bozeman, MT 59717, USA;2. Earth Sciences Department, Montana State University, Bozeman, MT 59717, USA;3. Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA;4. Mechanical and Industrial Engineering Department, Montana State University, Bozeman, MT 59717, USA;5. Center for Biofilm Engineering, Montana State University, Bozeman, MT 59717, USA |
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| Abstract: | In this paper, we present a quality evaluation of two-dimensional building acquisition. We propose methods for identification and quantification of differences between independently acquired regions, and we present a systematic classification of those differences. Differences between acquired sets Rj={ri}j of region rij depend on the context of observation, on the technique of observation, etc. We distinguish topological and geometrical differences. Topological differences refer to the interior structure of a set of regions as well as to the structure of the boundary of a single region. Geometrical differences refer to the location of the boundary of a single region or of a set of regions, independent of their representation and of the structure of the boundaries.Identification of differences requires a matching of two data sets R1 and R2, which is done here by weighted topological relationships. For the identification of topological differences between two sets R1 and R2 of regions, we use the two region adjacency graphs (RAGs). For an identification of geometrical differences, we use the zone skeleton between two matched subsets rp1 and rq2 of the given sets. The zone skeleton is labeled with the local distances of the corresponding boundaries of the subsets; especially, we investigate its density function. An example based on two real data sets of acquired ground plans of buildings, shows the feasibility of the approach. |
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