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postgraduate thesis: A critical investigation on the socio-environmental challenges of allocating green infrastructure in high-density cities
Title | A critical investigation on the socio-environmental challenges of allocating green infrastructure in high-density cities |
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Authors | |
Issue Date | 2024 |
Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
Citation | Sit, K. Y. [薛嘉盈]. (2024). A critical investigation on the socio-environmental challenges of allocating green infrastructure in high-density cities. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. |
Abstract | Green infrastructure in cities provides a multitude of ecosystem services to citizens. Given the ongoing climate emergencies and COVID-19 pandemic, green infrastructure has become an emerging topic of discussion among city leaders to create a livable, healthy, and sustainable landscape. However, the growing value of green infrastructures has also triggered environmental injustices surrounding its allocation, quality, and social impacts, as gradually unveiled by recent studies. Still, inadequate studies have targeted such inquiries in high-density cities nor explored the compatibility, challenges, and opportunities in promoting sustainable urban densification and equitably green landscapes.
Therefore, this thesis aims to conduct case studies of Hong Kong, one of the world’s densest modern cities, to critically explore three major socio-environmental challenges of allocating green infrastructure in high-density cities: (1) The daily exposure disparities of urban greenspaces across residents living in different housing and neighborhood environments; (2) the disparities in vegetation loss and potential ecosystem disservices triggered by frequent typhoon events across urban and natural land uses, and (3) the disparities of loss and disservices across socio-demographic groups and neighborhoods.
All studies were conducted using earth observation data and various geospatial-quantitative approaches. The first case study utilized cloud-free Sentinel 2 data, 3D building, and pedestrian networks to compute residents’ 10-minute walking and home vicinities greenspace exposure across housing types. The second study used three typhoons in 2023, multiple outline zoning plans, and four Sentinel-2 images to estimate vegetation loss while using the Disservice Risk Index (DRI) to calculate vulnerable sites toward ecosystem disservices. The third case study combined the latest census data with spatial boundaries of urban forms and vegetation loss data to investigate vegetation loss vulnerability across geographical regions and socio-demographic groups.
Results of all studies pointed towards the common vulnerability of residents in the high-density urban core while identifying effective initiatives such as public housing schemes, new town development, and nature conservation. People-oriented green infrastructure planning and adequate social welfare provision should be prioritized to safeguard citizens’ equitable enjoyment of green infrastructure in a high-density urban milieu.
The significance of this thesis is threefold. It provides valuable insights by focusing on the potential compatibilities of green infrastructure, urban densification, and environmental justice. It contributes to the emerging field of urban greening inequalities by extending it to high-density Asian cities. It provides in-depth examinations by combining multiple geospatial and qualitative methods for city-scale analysis. |
Degree | Master of Philosophy |
Subject | City planning - Environmental aspects - China - Hong Kong Landscape architecture - China - Hong Kong |
Dept/Program | Geography |
Persistent Identifier | http://hdl.handle.net/10722/351026 |
DC Field | Value | Language |
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dc.contributor.author | Sit, Ka Ying | - |
dc.contributor.author | 薛嘉盈 | - |
dc.date.accessioned | 2024-11-08T07:10:48Z | - |
dc.date.available | 2024-11-08T07:10:48Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | Sit, K. Y. [薛嘉盈]. (2024). A critical investigation on the socio-environmental challenges of allocating green infrastructure in high-density cities. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. | - |
dc.identifier.uri | http://hdl.handle.net/10722/351026 | - |
dc.description.abstract | Green infrastructure in cities provides a multitude of ecosystem services to citizens. Given the ongoing climate emergencies and COVID-19 pandemic, green infrastructure has become an emerging topic of discussion among city leaders to create a livable, healthy, and sustainable landscape. However, the growing value of green infrastructures has also triggered environmental injustices surrounding its allocation, quality, and social impacts, as gradually unveiled by recent studies. Still, inadequate studies have targeted such inquiries in high-density cities nor explored the compatibility, challenges, and opportunities in promoting sustainable urban densification and equitably green landscapes. Therefore, this thesis aims to conduct case studies of Hong Kong, one of the world’s densest modern cities, to critically explore three major socio-environmental challenges of allocating green infrastructure in high-density cities: (1) The daily exposure disparities of urban greenspaces across residents living in different housing and neighborhood environments; (2) the disparities in vegetation loss and potential ecosystem disservices triggered by frequent typhoon events across urban and natural land uses, and (3) the disparities of loss and disservices across socio-demographic groups and neighborhoods. All studies were conducted using earth observation data and various geospatial-quantitative approaches. The first case study utilized cloud-free Sentinel 2 data, 3D building, and pedestrian networks to compute residents’ 10-minute walking and home vicinities greenspace exposure across housing types. The second study used three typhoons in 2023, multiple outline zoning plans, and four Sentinel-2 images to estimate vegetation loss while using the Disservice Risk Index (DRI) to calculate vulnerable sites toward ecosystem disservices. The third case study combined the latest census data with spatial boundaries of urban forms and vegetation loss data to investigate vegetation loss vulnerability across geographical regions and socio-demographic groups. Results of all studies pointed towards the common vulnerability of residents in the high-density urban core while identifying effective initiatives such as public housing schemes, new town development, and nature conservation. People-oriented green infrastructure planning and adequate social welfare provision should be prioritized to safeguard citizens’ equitable enjoyment of green infrastructure in a high-density urban milieu. The significance of this thesis is threefold. It provides valuable insights by focusing on the potential compatibilities of green infrastructure, urban densification, and environmental justice. It contributes to the emerging field of urban greening inequalities by extending it to high-density Asian cities. It provides in-depth examinations by combining multiple geospatial and qualitative methods for city-scale analysis. | - |
dc.language | eng | - |
dc.publisher | The University of Hong Kong (Pokfulam, Hong Kong) | - |
dc.relation.ispartof | HKU Theses Online (HKUTO) | - |
dc.rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works. | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject.lcsh | City planning - Environmental aspects - China - Hong Kong | - |
dc.subject.lcsh | Landscape architecture - China - Hong Kong | - |
dc.title | A critical investigation on the socio-environmental challenges of allocating green infrastructure in high-density cities | - |
dc.type | PG_Thesis | - |
dc.description.thesisname | Master of Philosophy | - |
dc.description.thesislevel | Master | - |
dc.description.thesisdiscipline | Geography | - |
dc.description.nature | published_or_final_version | - |
dc.date.hkucongregation | 2024 | - |
dc.identifier.mmsid | 991044869877803414 | - |