The Role of Spatial Management Institutions in Area Resiliency with an Emphasis on Climatic Fluctuation Risks (A Case Study of Bonab)

Subject Areas :

javad Hajializadeh ¹ , asgar rashidi ebrahimhesari ²

1 - assistant professor of educational sciences department, Farhangian University, Tehran, Iran
2 - A PhD of geography and urban planning, Kharazmi University, Tehran, Iran

Received: 2017-07-16 Accepted : 2017-12-17 Published : 2020-08-22

Keywords: resiliency, Climatic factors, Bonab, urban- regional management,

Abstract :

We witness cities high risk taking in recent years as a result of climate changes. Climate changes result in higher temperatures, rising sea levels, severe storms and increased droughts. However, reduced risk and vulnerability were ignored.  The research method is survey and its logic is inductive and its most important advantage is interoperability of the obtained results. The SPSS and Lisrel Software are used for data analysis and statistical tests and Arc GIS software were used in order to display spatial maps. In this study, spatial management institutions variable including institutions and stakeholders of Bonab city and surrounding villages management was considered as dependent and endogenous variable was measured and analyzed in thirteen dimensions based on Hyogo vision and Framework. The reduced risks of climate fluctuations were measured and analyzed in six dimensions in order to increase the region's resiliency as exogenous variable. Output calculations based on single-sample t-test (T) indicated that urban- regional management principles were unfavorable in the study area and generally in spatial management dimension. The casual network that is determined by structural equations is 2.32 based on X2 / DF value and since the obtained value is smaller than 3, it shows that the model fitness is appropriate. The root mean square error of approximation (RMSEA) must be less than 0.08 that is equal to 0.063 in the proposed model. GFI (goodness of fit index) and (adjusted goodness of fit index) AGFI indices are equal to 0.91 and 0.90 respectively that must be greater than 0.80. The results of five indices are presented including increased comparative fit, relative fitness, Bentle Bonett normative fit, and Tucker-Lewis fit and comparative fit index based on data goodness of fit and structural model.

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