Research Article Open Access

An Investigation of Sustainable Development in Urban Neighborhoods Using Statistical Models

Sedigheh Lotfi

Abstract

Problem statement: Sustainable has a close relation to the quality of life in the different parts of each city. While the level of sustainability is studied in many urban areas world wide but it has been less considered in the Iranian cities. The city of Babolsar is selected to investigate the level of development by detail study of its 16 neighborhoods. Approach: The quantitative models such as Human Development Index (HDI), standard deviation, variable coefficient, factor analysis and the composed multiple regression (Enter) were used to assessing the level of sustainability, analyzing disparities and then to prioritize development by selecting of 30 socio-economic and physical variables. Results: The results from integrated indicators revealed that the sustainability coefficient was different in 16 neighborhoods of the city. The level of sustainability was classified in five categories, which only three neighborhoods were sustainable while others remained unbalanced. Also the research showed that there was a sharp disparity among the different neighborhoods of the city. The disparity mainly was evident in the environmental and social indicators with 0.98 and had been lower in the infrastructure with 0.32. Conclusion: By analyzing the results it could be concluded that there was a strong need for implementing long and short term planning strategies through taking different action to decrease the social and economic gap among the different neighborhoods of the city.

American Journal of Environmental Sciences
Volume 5 No. 3, 2009, 427-433

DOI: https://doi.org/10.3844/ajessp.2009.427.433

Submitted On: 6 June 2009 Published On: 30 June 2009

How to Cite: Lotfi, S. (2009). An Investigation of Sustainable Development in Urban Neighborhoods Using Statistical Models. American Journal of Environmental Sciences, 5(3), 427-433. https://doi.org/10.3844/ajessp.2009.427.433

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Keywords

  • sustainable development
  • multiple regression model
  • neighborhood
  • factor analysis