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Application Of Geographical Information System And Smart Growth Modelling For Identification Of Ineffective Quarters In Bandar Abbas, Iran


Citation

Dadras, Mohsen (2009) Application Of Geographical Information System And Smart Growth Modelling For Identification Of Ineffective Quarters In Bandar Abbas, Iran. Masters thesis, Universiti Putra Malaysia.

Abstract

During recent decades, planning and management of urban land use has had an important role in development of social and economy of countries. On the other hand expansion of land use can be managed by using geospatial data and development patterns. In Bandar Abbas city, the management of urban development are by trial and error urban land policies as compared to other cities due lack to the of accurate and complete geospatial data. It has been caused by the overgrowing population and migration towards the city without planning. In addition, the inefficiency and very old buildings had also contributed and became the main reason for low quality of urban life in District 1. The aim of this research was to recognize and identify the development patterns for inefficient quarters in District 1 with an inclination towards the use of AHP and Smart Growth models. To achieve appropriate patterns for managing and identifying the utilization of land in quarters, a spatial and attribute database in the GIS environment was used. The relationship between effective factors namely land use, population, density and construction of the development were considered in the analytical process. The investigation was carried out to locate capable region for urban development in the inefficient areas of District 1 in the Region 3 of Bandar Abbas. The use of AHP and Smart Growth model in GIS environment were implemented to the collected geospatial database. The collected information includes the land use of the present condition, the procedure of urban development and the effective factors over inefficient land use. The procedure of this research started with the reconnaissance of effective parameters upon land development in the surveyed region. Having identified the effective factors, layer classification was generated according to their degree of importance and criteria through the use of AHP model. It was implemented to identify suitable site for developing urban users in District 1. Then the Smart Growth model was used to generate zones under the surveyed region according to the kind of operation in inefficient patterns and land use. In Smart Growth model on the basis of divisions of land use it has been designed into three zones of Regional Center Development (RCD), Traditional Neighborhood Development (TND), and Special District (SD). Finally by investigating the relationships and their effects towards each other, and by determining smart code for each zone, the development pattern and inefficient control in District 1 were identified.The results achieved from this research have successfully identified the suitable lands for urban uses development and identify patterns of user control and land development in inefficient quarters of District 1. According to the results obtained from AHP model central and western portion are appropriate for development. Based on the results obtained from zoning in District 1 and also the Smart Growth model, a major part of the inefficiency of available textures in the quarters of District 1 is due to existing incompatible land uses, being old and obsolete residential and non residential textures, poor management, lack of supervision regulations and comprehensive lack of administrative laws.


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Additional Metadata

Item Type: Thesis (Masters)
Subject: Geographic information systems - Iran.
Subject: Cities and towns - Growth - Iran
Subject: Land use, Urban - Iran.
Call Number: ITMA 2009 6
Chairman Supervisor: Ahmad Rodzi Mahmud, PhD
Divisions: Institute of Advanced Technology
Depositing User: Mohd Nezeri Mohamad
Date Deposited: 11 Jul 2011 07:31
Last Modified: 27 May 2013 07:52
URI: http://psasir.upm.edu.my/id/eprint/12447
Statistic Details: View Download Statistic

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