基于GIS网络分析法的广州市保障性住房人群绿地可达性研究
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骆雯(1969—),女,重庆涪陵人,副教授,硕士生导师,研究方向为环境艺术设计。E-mail: luowen@scut.edu.cn |
收稿日期: 2023-01-16
修回日期: 2023-03-02
网络出版日期: 2024-04-08
基金资助
国家自然科学基金项目(42301257)
国家自然科学基金项目(52078004)
国家自然科学基金项目(41971184)
国家自然科学基金项目(42142025)
广东省哲学社会科学规划2024年度一般项目(GD24CYS34)
广东省自然科学基金团队项目(2018B030312004)
广东省哲学社会科学规划2023年度岭南文化项目资助(GD23LN07)
版权
Green space accessibility of affordable housing population in Guangzhou based on GIS network analysis method
Received date: 2023-01-16
Revised date: 2023-03-02
Online published: 2024-04-08
Supported by
National Natural Science Foundation of China(42301257)
National Natural Science Foundation of China(52078004)
National Natural Science Foundation of China(41971184)
National Natural Science Foundation of China(42142025)
General Projects of Philosophy and Social Sciences Planning in Guangdong Province for 2024(GD24CYS34)
Guangdong Natural Science Foundation Team Project(2018B030312004)
Guangdong Philosophy and Social Sciences Planning Foundation Lingnan Culture Project(GD23LN07)
Copyright
城市绿地是推进空间资源合理分配的重要基础设施之一。以广州市已建成的保障性住房为研究对象,采用GIS网络分析法,分析居住在保障性住房中的居民在不同交通方式下到达不同规模等级绿地的可达性。研究发现:① 保障性住房人群到区级绿地和街道级绿地的可达性受交通方式影响较小。② 通过核密度法和标准差椭圆法验证绿地与保障性住房的分布差异,结果表明保障性住房周边绿地覆盖范围小,各等级绿地的可达性较差。保障性住房的发展方向与绿地规划方向存在不一致,导致保障性住房处于绿地边缘位置。③ 地铁与公交或驾车的可达性高于地铁与步行的组合方式,主要因为绿地通常位于城市中心或繁忙地区较远的地方,且地铁与公交或驾车能覆盖更长的距离。本研究的结果对广州市在“十四五”规划中筹建新的保障性住房提供了有益参考,助力推动城市空间布局的优化。
骆雯 , 尹梦媛 , 祝明建 , 栾博 . 基于GIS网络分析法的广州市保障性住房人群绿地可达性研究[J]. 地理科学, 2024 , 44(3) : 483 -491 . DOI: 10.13249/j.cnki.sgs.20220431
Urban green spaces are one of the essential infrastructure elements for promoting the rational allocation of spatial resources. Taking the completed affordable housing in Guangzhou City as the research object, the study employs GIS network analysis to analyze the accessibility of residents living in affordable housing to green spaces of different scales and levels using various transportation modes. Research findings: 1) The accessibility of affordable housing residents to district-level and street-level green spaces is less influenced by transportation modes. 2) The distribution differences between green spaces and affordable housing were verified using kernel density analysis and standard deviation ellipse analysis. The results indicated that green spaces around affordable housing had limited coverage, and the accessibility to green spaces of various levels was relatively poor. The development direction of affordable housing did not align with the planning direction of green spaces, resulting in affordable housing being situated at the periphery of green areas. 3) The accessibility of green spaces is higher for the combination of subway and bus or car compared to the combination of subway and walking. This is mainly because green spaces are typically located farther from the city center or busy areas, and subway, bus, or car modes can cover longer distances. The results of this study provide valuable insights for Guangzhou City’s efforts in building new affordable housing during the “14th Five-Year Plan” and can contribute to optimizing the urban spatial layout.
表1 2020年广州绿地分类统计表Table 1 Statistical table of Guangzhou green space classification in 2020 |
| 类别 | 规模/m2 | 总面积/km2 | 占总面积比重/% |
| 市级绿地 | ≥200000 | 1424.59 | 97.29 |
| 区级绿地 | [50000, 200000) | 29.09 | 1.99 |
| 街道级绿地 | [10000, 50000) | 8.23 | 0.56 |
| 社区级绿地 | [500, 10000) | 2.42 | 0.17 |
图4 2022年广州市绿地核密度与保障性住房可达性分析Fig. 4 Analysis of green space kernel density and accessibility to affordable housing in Guangzhou, 2022 |
表2 2022年广州多尺度绿地可达性分析Table 2 Multi-scale green space accessibility analysis in Guangzhou, 2022 |
| 可达性/m | 市级绿地面积/km2 | 区级绿地面积/km2 | 街道级绿地面积/km2 | 社区级绿地面积/km2 | 占总面积比重/% |
| [0,5000) | 80.49 | 3.24 | 1.02 | 0.23 | 5.80 |
| [5000,10000) | 224.66 | 11.32 | 3.57 | 1.43 | 16.46 |
| [10000,15000) | 300.00 | 5.31 | 1.00 | 0.40 | 20.95 |
| [15000,25000) | 439.44 | 4.20 | 1.79 | 0.30 | 30.44 |
| [25000,50000) | 380.00 | 5.02 | 0.85 | 0.06 | 26.36 |
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