Developing a Data Driven Strategy and Guideline to Increase Per Capita Open Space and Relative Accessibility in Chittagong City

Maharina Jafrin ()
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Maharina Jafrin: School of Architecture & Built Environment, Deakin University, Geelong, VIC 3220, Australia

Sustainability, 2022, vol. 14, issue 16, 1-25

Abstract: The population density in Chittagong City Corporation (CCC) area was 242.28 per square meter in 2019, and Bulmer suggests that, due to the high birth rate in Asia, cities such as Chittagong can be considered high density. Contextually, this ‘high-density’ element is a determining factor that potentially allows one to address the city’s open space standard, which “should compensate and complement the physical and social context of the [urban] surrounding environment”. The research in this paper is focused on the urban setting, defined in the CCC area of 168 square kilometres. The literature review and case study analysis found that per capita open space in Chittagong is far lower than the WHO recommendation (nine square meters per person). Additionally, the UN stated that “47% of [the city’s] population live within 400 m walking distance to open public spaces”, whereas, according to the previous study, in Chittagong City only 19% of residents live within this distance. Observing these issues, the aim of the paper is to develop an innovative way to obtain per capita open space in Chittagong city. To achieve the aim, the researchers analysed the data from surveys and interviews conducted by using SPSS and NVivo. These tools produced data that were, for example, used to develop themes of open space in Chittagong. This investigation and analysis of material allowed for the generation of strategies and planning recommendations to improve the open space situation in the city. Beyond these strategies, the research team produced new insights to promote sustainability in this area.

Keywords: open space; sustainability; SPSS; NVivo; survey and interview analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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