Dealing with the Uncertainty of Having Incomplete Sources of Geo-Information in Spatial Planning
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- 作者：L. A. E. Vullings (1)
C. A. Blok (2)
C. G. A. M. Wessels (3)
J. D. Bulens (1) - 关键词：Uncertainty ; Spatial planning ; Geo ; information ; Fuzzy set theory ; Visualisation
- 刊名：Applied Spatial Analysis and Policy
- 出版年：2013
- 出版时间：March 2013
- 年：2013
- 卷：6
- 期：1
- 页码：25-45
- 全文大小：960KB
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C. A. Blok (2)
C. G. A. M. Wessels (3)
J. D. Bulens (1)
1. Alterra, Wageningen University and Research Centre, P.O. Box 47, 6700, AA, Wageningen, The Netherlands
2. Geo-Information Processing Department, Faculty of Geo-Information Science and Earth Observation (ITC) of the University of Twente, P.O.Box 217, 7500, AE, Enschede, The Netherlands
3. Nexpri V.O.F., Ondiep Zuidzijde 6, 3551, BW, Utrecht, The Netherlands - ISSN：1874-4621
文摘
The Dutch spatial planning legal act of 2008 was aimed at improving efficiency and effectiveness in the development, evaluation and monitoring of spatial planning policy (Ministry of VROM, 2006a). One of the main effects of this legal act was the widespread availability and use of digital spatial plans (Ministry of VROM 2006a, b). This reform led to the expectation that all digital spatial plans would be exchangeable and comparable. In practice, this exchange and comparison required carrying out complex procedures due to uncertainty caused by differences in the scope of spatial plans as well as their intended use. Furthermore the uncertainty resulted in a lack of confidence in spatial plans by policymakers and supporting GIS staff. Our overarching research question was: how can uncertainty caused by incomplete geo-information sources be dealt with? We proposed two techniques—fuzzy logic and visualisation—for policy makers to deal with uncertainty resulting from incomplete geo-information sources in spatial planning at the regional and national planning levels. We used two case studies in the Netherlands to illustrate the results of applying these techniques. The fuzzy set theory provides extra information by converting the discrete borders of continuous objects into fuzzy borders that improve the resemblance to the real object and thus make it more realistic. As shown in the second case study, visualisation also improves the degree of realism and thus provides additional information. Both case studies showed that providing additional information reduces the uncertainty felt by policymakers.