The Categorization of Urban Districts in Mashhad according to the Integrated Indicators of Smart Urban Growth

جغرافیاوتوسعه ناحیه ای

Article 2, Volume 13, Issue 2 - Serial Number 25, March 2016, Pages 29-44   

Document Type: scientific-research article

DOI: 10.22067/geography.v13i2.18701

Authors

Ezzatollah Mafi; Shahrzad Gholizade Sarabi^*

Ferdowsi University of Mashhad

Abstract

Extended Abstract
1. Introduction
Today the irregular growth of the population and its illogical distribution across natural and cultural environments of different communities has necessitated sustainable development in response to the unstable conditions of cities. Mashhad is a city with fast growth and development but with no clear plan, especially after land reform program. In this sense, the city is now extremely under the influence of dangerous outcomes of this ill fast growth, having a large number of environmental, social, and economic implications. So far, several designs of development have been developed for the city; however, despite taking such decisions, disperse urban growth and its implications still exist due to lack of scientific attention to urban growth and lack of proper theoretical patterns. Therefore, it seems that urban smart growth strategy, as a response to the sprawl, could improve the quality of the urban environment in Mashhad. The aim of this paper is to determine the rank and smart urban growth indices of the twelve districts of Mashhad based on the use of fuzzy logic. In this article, we will answer two main questions: 1) How does each district in Mashhad enjoy the indices of smart urban growth indicators? 2) Is there inequality between different districts of Mashhad regarding the integrated indicators of smart urban growth?

2. Theoretical Framework
Promoting the idea of smart urban growth is attributed to growth management in the 1970s and 1980s (Gabriel et al., 2006). The late 1990s witnessed smart urban growth as a new approach to urban planning in the United States of America and the urban growth has been used widely as a compressed pattern regardless of dispersion since then (Batisani & Yarnal, 2011; Danielsen & et al., 1999). The major theories of urban development focus on the relationship between the urban form and life quality. Such theories provide a framework for decision making with the goal of having a dynamic, diverse, pedestrian-oriented, environmentally friendly and economically sound society through the proper use of land and effective transport planning (Arku, 2009; Durand et al., 2011; Pyatt, 1999). Concerning the ten principles of smart urban growth, items such as the mixed land, the use of compact design in the construction, creating a variety of opportunities and housing options, creating neighborhoods suitable for pedestrians, creating a distinctive and attractive communities with a strong sense of place, protecting open spaces, farmland, natural beauty and environmentally vulnerable areas, strengthening and directing development of existing communities, providing a variety of transportation options, encouraging local communities, and the beneficiaries to participate in the development of decisions along with the predictable and fair and cost-effective development of decisions are all taken into consideration (Smart growth network, 2010).

3. Method
This research was a cross sectional descriptive study. The research was carried out in Mashhad, and the population included 12 different districts in Mashhad according to the divisions published by the municipality in 2006. The examined indicators included 35 factors such as population, economic, physical indices as well as land use, transportation and environmental protection. The initial data needed for this research was obtained through the study of documents and General Population and Housing Census (2006), Mashhad Statistic Report (2010), Mashhad Transport Statistics (2010) and the related organizations. Then the data were analyzed using fuzzy cluster analysis in Excel and SPSS software.

4. Discussion and Findings
According to the results of the twelve districts of Mashhad, district 8 with a fuzzy score of 0.517 and District 5 with a score of 0.207 were respectively the first and the last city based on integrated smart growth indices. The mean of integrated smart growth indices for urban areas in Mashhad were estimated as 30%. . Districts 1, 2, 7, 8, 9 and 11 had indices higher than the mean, and Districts 3, 4, 5, 6, 10, and Samen had indices below the mean. Based on the fuzzy values and critical values, Districts 1, 2, 3, and 4 were lower than the critical value respectively in 77.2, 71.9, 81.2, and 79% of urban smart growth indices. District 5 was higher than the critical value only in 2.14% of urban smart growth indices. Districts 6, 7, 8, 9, 10, 11 and Samen were in critical conditions in 93.3, 82.9, 57.8, 64.5, 79.4, 72, and 76.2% of the selected indicators respectively. According to fuzzy values of each index, the critical value of smart growth indices was estimated as 70%. All Districts in Mashhad were below this value and thus in critical conditions. The findings also showed that the greatest difference among Mashhad urban Districts concerned environmental and transportation factors. Therefore, according to the results of the cluster analysis, Mashhad urban areas were divided into two main groups in terms of smart urban growth indices. The first group included the north and west of Mashhad; this group was consisted of regions with an acceptable level of smart urban growth indices. The second group included the east of Mashhad with a poor level of smart urban growth indices.

5. Conclusion and Suggestions
The results of this study indicate the unsustainable growth model of Mashhad as a metropolis. Hence, to achieve sustainable urban development, it is necessary that urban smart growth strategy be used as the dominant strategy in Mashhad urban development. For this purpose, given the differences of various Districts of Mashhad with respect to the level of smart urban growth indices, it is necessary to give priority to Districts with poor indices, such as Districts 4, 5 and 6.

Keywords

Smart Growth; Mashhad; Fuzzy analysis

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