GIS-Based Analysis to Identify the Distribution and Accessibility of Urban Green Space in Dhaka Metropolitan City, Bangladesh

  • Khan M
  • Hossain M
  • Alam M
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Abstract

Urban Green Space (UGS) plays an important role in minimizing the negative effects of urbanization on city dwellers, which is predominantly factored into the accessibility to UGS. This study elucidated the distribution and accessibility of UGS in Dhaka, Bangladesh considering the paucity of such important scientific studies in the given area. The methodological structure of this study employed a multispectral Landsat satellite image from 2020 for identifying the logically defined UGSs, as well as a minimum proxy distance being the parameter to estimate accessibility to the UGS through a primary survey scheme and literature review. Considering UGS as a public area, we adopted a hybrid (combination of supervised and unsupervised classification) method followed by post-classification for UGS distribution assessment. The unsupervised classification identified the overall distribution of green spaces, whereas the anomalies of generated classes were rectified during the post-classification. Following the study findings, UGS in Dhaka metropolitan city accounts for only 602 ha or 1.9% of the total geographical space, with Ramna thana ranked as the highest contributor of 111 ha. However, in terms of accessibility to the UGS by city residents, 19.9% of the buildings in Dhaka metropolitan city were computed to be within the determined proxy distance of 500 m around the UGS. Also, parallel to UGS distribution, green space in Ramna thana (111 ha) exhibited the highest accessibility rate (64%) to the UGS compared with other thanas in Dhaka metropolitan city. The baseline findings will contribute to the long-term sustainable urban planning and development of more accessible green spaces in the study area.

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APA

Khan, M. W., Hossain, Md. S., & Alam, M. (2023). GIS-Based Analysis to Identify the Distribution and Accessibility of Urban Green Space in Dhaka Metropolitan City, Bangladesh. Journal of Geographic Information System, 15(01), 35–52. https://doi.org/10.4236/jgis.2023.151003

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