Spatial analysis of the infrastructural components of learning city based on spatial heterogeneities between Zanjan urban neighbohoods

Document Type : Research Article (Applied - Development)

Authors

1 MSc of Geography & Urban Planning, Zanjan University, Zanjan, Iran

2 Associate Professor of Geography & Urban Planning, University of Shahid Beheshti, Tehran, Iran

3 Assistant Professor of Geography & Urban Planning, Zanjan University, Zanjan, Iran

4 PhD Candidate of Geography and Urban Planning, Shahid Beheshti University, Tehran, Iran

10.22103/JUSG.2020.2029

Abstract

Objective:With the advent of the information age and the growth of new communication technologies, the idea for the learning society has affected all human social relations and provided public learning for all people regardless of any differences. Therefore, in order to increase the efficiency of learning activities in urban spaces, it is necessary to pay attention to the location of these services and the benefit of all citizens from them. Accordingly, the present study, with the aim of spatial analysis relationships between demographic and physical factors as basic principles in the realization of learning city has examined spatial heterogeneities in urban neighborhoods of Zanjan.
Methods: The present study is applied in terms of purpose and is descriptive-analytical in terms of nature. The method of data collecting is documentary-library. To analyze the findings, Moran's self-correlation technique and geographical weight regression model were used.
Results:The results of the use of Moran statistics show that the spatial self-correlation between all the indicators measured is positive and follows the cluster pattern. Following the existence of such a pattern, the assessments made using the GWR model show that the population index required for education with 13.5% has the highest impact factor on the transformation of Zanjan into a learning city. Also, considering the adjusted R2 values equal to 43 and 32%, the GWR modeled the spatial relationships between the variables with acceptable accuracy and was able to predict spatial inequalities and optimal deployment ranges of the centers in the coming years.
Conclusion: The findings show that most of the neighborhoods of Zanjan suffer from spatial imbalances in terms of the appropriateness between the learning land uses and their population. This is much more severe in the case of the Bisim, Islamabad and Trans neighborhoods with an illiterate population of 40.6%. Therefore, urban management should prevent gaps and social-spatial inequalities between urban areas and neighborhoods through proper planning in the fair distribution of learning services and make it possible to achieve learning city in Zanjan neighborhoods by determining the optimal location of learning land uses

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