| 摘要: |
| 社区公园是与居民联系最为紧密的社区级公共绿色空间，实现其布局空间公平是推进基本公共服务均等化的重要需求。基于人工智能方法，从整体差
异、区域间差异和分配差异选取评价指标，构筑数量、区位和面积的组合模式，量化分析三基础要素及其组合对社区公园布局空间公平的影响，经由姑苏区案例
验证模拟结果。结果表明，社区公园布局由“少而大”转为“多而小”，3种要素在不同的空间公平层级产生影响：1)数量要素关联社区公园覆盖率以影响整体差
异，整体差异共降低57.60%；2)区位要素改变居民与社区公园空间关系以影响区域间差异，区域间差异共降低59.41%；3)面积要素调整供需关系以影响分配
差异，分配差异共降低44.32%；4)姑苏区社区公园布局的基础要素对空间公平的影响遵循上述模拟规律，但整体差异与分配差异变化更显著，而区域间差异变
化则相对较小。揭示了社区公园布局基础要素对空间公平的影响规律，为落实社区公园布局空间公平理念提供支撑，为其规划优化提供精准化指引。 |
| 关键词: 风景园林 社区公园布局 基础要素 空间公平 人工智能模拟 |
| DOI：10.19775/j.cla.2025.02.0048 |
| 投稿时间：2024-01-24修订日期：2024-05-24 |
| 基金项目:国家自然科学基金面上项目(51778389，42471218)；“十四五”江苏省重点学科(风景园林学)；江苏省企业研究生工作站(苏州园林设计院股份有限
公司)；江苏省普通高校研究生实践创新计划(SJCX22＿1599) |
|
| Study on the Impact of Basic Elements of Community Park Layout on Spatial Equity Based on ArtificialIntelligence Simulation |
| LIU Zhiqiang,,ZHU Yifan,,HONG Genwei*,,YU Hui |
| Abstract: |
| Community parks are vital public green spaces at the community level that
play a key role in urban environments, closely linked to residents' daily lives. These
parks not only provide recreational and social benefits but also enhance the overall
quality of life for residents. Achieving spatial equity in their layout, ensuring fair
and equal access for all residents, is a critical objective to promote the equalization
of basic public services. A well-distributed network of community parks allows
people from all areas to enjoy green spaces, regardless of their residential location,
which enhances the sense of inclusivity and cohesion within communities. In this
study, we apply advanced artificial intelligence methods to simulate the supplyside
layout of community parks. Our approach evaluates key indicators at three
levels: 1) the overall difference, which examines the equity of the layout throughout
the entire area; 2) the inter-regional difference, which focuses on spatial disparities
among different regions; and 3) the distribution difference, which assesses the
balance of park distribution within specific regions. These indicators are essential
for understanding how community park layouts align with spatial equity goals.
Using these metrics, we construct a variety of combination models that analyze the
interplay of three basic elements: quantity, location, and area. Each model captures
how different configurations affect spatial equity. Based on these models, we conduct
a quantitative analysis to understand the impact of each factor-quantity, location, and
area on spatial equity in community park layouts. By applying our models to realworld
cases, particularly in Gusu District, we verify the accuracy of our simulations.
Gusu District serves as a case study to test how well the simulation results align with
actual patterns, enabling us to examine the applicability of our findings in real-life
urban contexts. The findings demonstrate that the artificial intelligence simulation
method allows for a highly effective, quantitative assessment of spatial equity by
adjusting parameters such as the number of parks, their locations, and their average
size. This approach enables rapid and precise quantitative analysis of the influence of
these basic elements on spatial equity, providing a clear picture of how community
park layouts can be improved. By increasing the number of parks, reducing spacing
among them, and adjusting average park sizes, the model shows an improvement
in spatial equity across different accessibility levels. The main findings can be
summarized as follows: 1) Quantity Element: Our study shows that increasing the
number of community parks reduces the overall difference in spatial equity by making
parks more accessible across the area. As park numbers grow, the initial reduction
in spatial equity difference is gradual, but it accelerates as more parks are added,
enhancing accessibility. This finding indicates that quantity changes primarily impact
the overall spatial equity difference, and with coverage improvements, the overall
difference is reduced by 57.60%. 2) Location Element: Alterations in park location
impact inter-regional differences, altering the spatial relationship between residents
and community parks. By redistributing parks to balance access between regions, the
simulation shows a 59.41% reduction in inter-regional differences. Thus, location
is a major factor influencing how equitably parks are accessible to residents across
regions. 3) Area Element: Park size affects the distribution difference by adjusting
the supply and demand relationship within specific regions. Reducing park sizes
and increasing the number of smaller parks can help maintain accessibility without
concentrating resources in fewer, larger parks. This change results in a 44.32%
reduction in distribution difference, suggesting that area adjustments can enhance
spatial equity by ensuring parks are more evenly spread across a region. Furthermore,
these simulation outcomes were closely aligned with the real-life patterns observed
in Gusu District. When we applied these simulation insights to Gusu District's
community park layout, we discovered that the rules observed in the simulation
generally held in real-world conditions. Specifically, the overall and distributional
differences showed more pronounced changes, while inter-regional differences were
relatively stable. This suggests that in real-life applications, a "multiple but small"
layout strategy - characterized by an increased number of smaller parks - can be
an effective approach to improving spatial equity. This strategy works particularly
well in regions where population distribution differences are minimal, as it ensures
a more equitable distribution of green spaces across the area. In conclusion, this
study demonstrates the importance of quantity, location, and area in achieving spatial
equity in community park layouts. By simulating various scenarios using artificial
intelligence, we provide a comprehensive, data-driven framework that enables urban
planners and policymakers to optimize park layouts for enhanced spatial equity. This
framework supports the concept of spatial equity in public green spaces, providing
actionable insights that can guide efforts in urban planning and park development.
Ultimately, this research reveals the significant impact of these basic elements on
spatial equity and highlights the importance of a data-driven approach to urban
planning. With the insights gained from our AI-based simulations and the real-life
case study in Gusu District, we offer precise guidelines for optimizing community
park layouts. These findings help support future planning initiatives aimed at ensuring
that community parks are accessible and beneficial to residents in all areas, promoting
a more inclusive and equitable urban environment |
| Key words: landscape architecture community parks layout basic elements spatial
equity Artificial Intelligence Modelling |
