Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.1016/j.scs.2024.105767 |
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| Title (Primary) | Planning for green infrastructure by integrating multi-driver: Ranking priority based on accessibility equity |
| Author | Dong, X.; Yang, R.; Ye, Y.; Yi, S.; Haase, D.; Lausch, A. |
| Source Titel | Sustainable Cities and Society |
| Year | 2024 |
| Department | CLE |
| Volume | 114 |
| Page From | art. 105767 |
| Language | englisch |
| Topic | T5 Future Landscapes |
| Supplements | https://ars.els-cdn.com/content/image/1-s2.0-S2210670724005924-mmc1.docx |
| Keywords | Green infrastructure planning; Urban ecosystem; Multifunctionality; Sponge city; Nature-based solution |
| Abstract | Green infrastructure provides multifarious benefits, improving urban resilience and sustainability amid increasing climate change and urbanization. Traditional green infrastructure planning studies were based on the spatial-equity principle, which usually neglected residents’ aggregation pattern, leading to the conflict with equitable green exposure. Using the sponge city of Zhengzhou as a case, this study proposes a novel priority ranking strategy, namely accessibility equity. We first spatially quantified the regional socioecological conditions on 0.25 km2 grids as green infrastructure planning drivers, including stormwater management, urban thermal environment, air quality, habitat maintenance and water purification. Subsequently we integrated these planning drivers with population density to conduct spatial autocorrelation analysis, priority ranking, and grid clustering. While most planning drivers are positively correlated with population density, except air quality, some areas show opposite trends in terms of local perspective, suggesting that the spatial equity may lead to mismatch between residents’ demand and GI priority. The priority order based on accessibility equity, rises in the city center and falls in suburbs and industrial zones. The study area is divided into four categories using k-means clustering, and we propose the corresponding adaptive green infrastructure development strategy. The framework can be a practical tool for guiding green infrastructure and sponge city projects. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=29686 |
| Dong, X., Yang, R., Ye, Y., Yi, S., Haase, D., Lausch, A. (2024): Planning for green infrastructure by integrating multi-driver: Ranking priority based on accessibility equity Sust. Cities Soc. 114 , art. 105767 10.1016/j.scs.2024.105767 |
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