Positioning localities based on spatial assertions
Authors:
Y. Liu ab;
Q. H. Guo b;
J. Wieczorek c;
M. F. Goodchild d
| Affiliations: | a Institute of Remote Sensing and Geographic Information Systems, Peking University, Beijing 100871, China |
| b School of Engineering and Sierra Nevada Research Institute, University of California, Merced, CA 95344, USA | |
| c Museum of Vertebrate Zoology, 3101 Valley Life Sciences Building, University of California, Berkeley, CA 94720, USA | |
| d National Center for Geographic Information and Analysis, and Department of Geography, University of California, Santa Barbara, CA 93106-4060, USA |
DOI:
10.1080/13658810802247114
Publication Frequency:
12 issues per year
Published in:
International Journal of Geographical Information Science,
Volume
23,
Issue
11
November
2009
, pages 1471
- 1501
First Published:
November
2009
Subjects:
Cartography;
Computer Science (General);
Earth Sciences;
Geographic Information Systems;
Location Based Services;
Navigation;
Systems & Computer Architecture of Databases;
Topography;
Transport Geography;
Formats available:
HTML
(English)
:
PDF
(English)
Previously published as:
International journal of geographical information systems
(0269-3798,
1362-3087)
until 1996
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Abstract
In practice, descriptive localities are often communicated using named places and spatial relationships. Uncertainty associated with such descriptions of localities is inevitable, and knowledge of such uncertainty is normally not explicit. When translating descriptive localities into spatially explicit ones, it is critical to circumscribe locations and to estimate the associated uncertainty based on a set of appropriate spatial relationships. In conventional research on qualitative spatial reasoning (QSR), spatial relationships are modeled using formal logic. Unfortunately, QSR cannot deal with the uncertainty of a position. In this paper, based on the conceptual model of spatial assertions, we introduce the uncertainty field model to represent the probability distribution of a point locality. Using probability operations, we can combine a set of assertions to position a locality. Conflicts among assertions for a single locality can be detected based on the resulting field. Since spatial relationships play an important role in the uncertainty of target objects, we investigate conceptually the uncertainty fields associated with various types of spatial relationships (for example, topological, directional and metric). In a concrete application, these uncertainty fields can be customized and used without altering the proposed framework.
|
| Keywords: Geographic information system; Spatial positioning; Probability; Uncertainty field; Spatial relationship |
| view references (63) |

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