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Volume 31, Issue 3 (2016)                   GeoRes 2016, 31(3): 144-156 | Back to browse issues page
Article Type:
Original Research |
Subject:
GIS

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Mohammad Pour A, Rahmati A, Teimouri H. Spatial Organization of Urban Districts based on REDCAP Algorithm (Case Study: Regionalization of Tehran Metropolis). GeoRes 2016; 31 (3) :144-156
URL: http://georesearch.ir/article-1-48-en.html
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1- Department Of Political Geography Tehran University
2- Department Of Remote Sensing & GIS ,Tehran University,Tehran ,Iran , rahmaty_a685@ut.ac.ir
3- Department Of Remote Sensing & GIS ,Tehran University,Tehran ,Iran
Abstract   (5253 Views)

Increasing urban population and organizations have introduced many problems in urban life. In a city there are a lot of organizations like municipalities, Roads and Urban Development organizations, etc. Which have made their own segmentations for servicing their customers. All of these configurations have been made for responding to specific requirements and reaching specific goals. But Most of the time these segmentations have functional overlap and in many cases are in conflict with each other.This has caused inefficiency, and dissatisfaction of people, because they have to go to lots of organizations to get their work done. Therefore all the organizations in a city must clearly specify their responsibilities and territories.To do this, we aim to suggest a new system of regionalization using REDCAP algorithms in Tehran City. Research type is descriptive/analytical and the data has been collected from different organization. We designed 22 indexes to reshape new regions. These indices have been generated by aggregating raw data in primary spatial units. Primary spatial units have been designed by converting road network of Tehran city to polygons.After that we applied REDCAP algorithm by defining three parameters (number of regions, minimum population and REDCAP algorithms) to generate new regions. Then to prove our new regions are superior to formal regions of Tehran municipality we utilized Moran’s I index by measuring homogeneity of new regions in comparison with formal regions. Results showed us that new regions best fit our aims and are more homogenous than formal regions.

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