Planning for green infrastructure by integrating multi-driver: Ranking priority based on accessibility equity

被引:3
|
作者
Dong, Xinyu [1 ,2 ]
Yang, Runjia [3 ]
Ye, Yanmei [3 ]
Yi, Shengao [4 ]
Haase, Dagmar [1 ,2 ]
Lausch, Angela [1 ,2 ,5 ,6 ]
机构
[1] Humboldt Univ, Geog Dept, Landscape Ecol Lab, D-10099 Berlin, Germany
[2] UFZ Helmholtz Ctr Environm Res, Dept Computat Landscape Ecol, D-04318 Leipzig, Germany
[3] Zhejiang Univ, Dept Land Management, Hangzhou 310058, Peoples R China
[4] Univ Penn, Dept City & Reg Planning, Philadelphia, PA 19104 USA
[5] Martin Luther Univ Halle Wittenberg, Dept Phys Geog & Geoecol, D-06120 Halle, Germany
[6] Anhalt Univ Appl Sci, Inst Geoinformat & land surveying, Dept Architecture, Facil Management & Geoinformat, D-06846 Dessau, Germany
基金
中国国家自然科学基金;
关键词
Green infrastructure planning; Urban ecosystem; Multifunctionality; Sponge city; Nature-based solution; URBANIZATION; SPACE; PM2.5; CONSERVATION; PROVISION; JUSTICE;
D O I
10.1016/j.scs.2024.105767
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
引用
收藏
页数:14
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