Optimal Positioning of Synoptic Stations Through Fuzzy Logic and Analytical Hierarchy Process (AHP), Case Study: Tonekabon City

Document Type : Science - Research

Authors

1 Assistant Professor of Geography Department in Islamic Azad University of Chalus

2 PhD Student in Geography and Rural Planning University of Payame Noor Tehran

3 PhD Student in Climate at the University of Karaj Kharazmi

Abstract

Tonekabon has 13 pluviometry stations as well as one climatological station which is inactive. Due to the distance of the city with existing synoptic stations and with regard to the area of the city, it is attempted to position a new synoptic station so as to both resolve the problem with the distance between the stations available and also to use the new station data for climate studies as well as urban planning and construction. This research was practical with an analysis-combination approach. In order to analyze the data , graphic-based software’s  ARC GIS10  and  statistical -besd PASW & Choise Expert, is used. Additionally, in order to integrate and extract effective weights in the positioning operation, the models of analytic hierarchy process (AHP), weighted overlap, and fuzzy logic were used. The results of the study showed that due to the combination of seven factors with weighted overlap model as well as using the AHP model, 81/6 square kilometers of the area under study had great potential to be suitable for the construction of synoptic stations, which was mainly concentrated in the north part of the city. Moreover, about%38 of the city area had such capability. The results obtained from the combination of factor maps with the fuzzy model introduced that half square kilometers of the city area had the right capabilities to construct synoptic stations. Regarding the comparison of the two final maps, the fuzzy model due to its higher flexibility than the weighted overlap model was introduced as the optimum model for prioritizing the city to build synoptic stations.

Keywords

References

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History

  • Receive Date: 07 September 2012
  • Revise Date: 02 November 2014
  • Accept Date: 12 January 2015

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