Community park visits determined by the interactions between built environment attributes: An explainable machine learning method

IF 4 2区 地球科学 Q1 GEOGRAPHY
Zuopeng Xiao , Chengbo Zhang , Yonglin Li , Yiyong Chen
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引用次数: 0

Abstract

Uncovering the association between built environment (BE) attributes and community park visits by considering potential nonlinear effects can inform more effective spatial policies. This study utilizes real-time population visitation big data to depict the spatial variances in community park visits in the case city of Shenzhen. An explainable machine learning method incorporating random forest and Shapley Additive exPlanations (SHAP) is applied to reveal the relative importance of BE attributes and to examine the nonlinear associations and interaction effects on park visits. The results confirm the decisive roles of park size and walking-based street connectivity on associating with visits, with threshold points at 2 hm2for park size and 0.3 for network warp. The revealed interaction between park size and surrounding BE attributes benefits defining the optimal scale by considering surrounding attributes of both attraction and demand factors. Based on the findings, we further discuss the possible patterns of threshold effects and interaction effects rooted in the examined nonlinearity. The findings guide policy makers in adopting smarter and more effective strategies to improve community park visits.
建筑环境属性之间的相互作用决定了社区公园的访问量:可解释的机器学习方法
通过考虑潜在的非线性效应来揭示建筑环境(BE)属性与社区公园访问量之间的关联,可以为制定更有效的空间政策提供依据。本研究利用实时人口访问大数据来描述深圳社区公园访问量的空间差异。研究采用随机森林和 Shapley Additive exPlanations(SHAP)相结合的可解释机器学习方法来揭示 BE 属性的相对重要性,并检验公园访问量的非线性关联和交互效应。研究结果证实,公园面积和步行街的连通性对公园访问量具有决定性作用,公园面积的阈值为 2 hm2,网络翘曲的阈值为 0.3。所揭示的公园规模与周边 BE 属性之间的相互作用有利于通过考虑吸引力和需求因素的周边属性来确定最佳规模。根据研究结果,我们进一步讨论了所研究的非线性中可能存在的阈值效应和交互效应模式。研究结果将指导政策制定者采取更明智、更有效的策略来提高社区公园的访问量。
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来源期刊
Applied Geography
Applied Geography GEOGRAPHY-
CiteScore
8.00
自引率
2.00%
发文量
134
期刊介绍: Applied Geography is a journal devoted to the publication of research which utilizes geographic approaches (human, physical, nature-society and GIScience) to resolve human problems that have a spatial dimension. These problems may be related to the assessment, management and allocation of the world physical and/or human resources. The underlying rationale of the journal is that only through a clear understanding of the relevant societal, physical, and coupled natural-humans systems can we resolve such problems. Papers are invited on any theme involving the application of geographical theory and methodology in the resolution of human problems.
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