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Regional Coverage Maximization: Alternative Geographical Space Abstraction and Modeling.
- Source :
-
Geographical Analysis . Apr2017, Vol. 49 Issue 2, p125-142. 18p. - Publication Year :
- 2017
-
Abstract
- Analysis results are often found to vary with the way we abstract geographical space. When continuous geographic phenomena are abstracted, processed, and stored in a digital environment, some level of discretization is often employed. Information loss in a discretization process brings about uncertainty/error, and as a result research findings may be highly dependent on the particular discretization method used. This article examines one spatial problem concerning how to achieve the maximal regional coverage given a limited number of service facilities. Two widely used geographical space abstraction approaches are examined, the point-based representation and the area-based representation, and issues associated with each representation scheme are analyzed. To accommodate the limitations of the existing representation schemes, a mixed representation strategy is proposed along with a new maximal covering model. Experiments are conducted to site warning sirens in Dublin, Ohio. Results demonstrate the effectiveness of the mixed representation scheme in finding high-quality solutions when the regional coverage level is medium or high. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00167363
- Volume :
- 49
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Geographical Analysis
- Publication Type :
- Academic Journal
- Accession number :
- 122403962
- Full Text :
- https://doi.org/10.1111/gean.12121