建筑环境对济南城市活力的非线性影响基于多源数据和可解释的AI
Mingyang Yu1, Qingrui Ji2, Xiangyu Zheng2
1School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, 250101, China. ymy@sdjzu.edu.cn.
Scientific reports
|January 9, 2026
概括
这项研究揭示了建筑环境如何使用人工智能影响城市活力. 像POI密度这样的客观因素是关键,为最佳城市规划确定了特定的门.
科学领域:
- 城市规划和设计
- 地理信息科学 地理信息科学
- 城市研究中的人工智能
背景情况:
- 了解城市形式和生命力之间的复杂相互作用对于有效的城市规划至关重要.
- 现有的框架往往难以捕捉建筑环境的非线性动态和主观感知.
研究的目的:
- 开发一个综合分析框架来评估受建筑环境影响的城市活力.
- 解码非线性关系,并确定建筑环境特征和城市活力之间的关键值.
- 建立一个包含客观和主观维度的综合性城市活力指数.
主要方法:
- 利用可解释的AI (XGBoost-SHAP) 来分析多源数据并发现非线性关系.
- 应用了CRITIC权重方法来构建一个新的复合城市活力指数.
- 在一个二维的建筑环境框架内集成客观 (百度热图,夜间照明,POI) 和主观 (街景图像) 数据.
主要成果:
- 在城市活力中确定了一个明显的"东方强,西方弱"的空间模式.
- 发现客观的建筑环境因素,特别是POI混合,密度和空间整合,显著影响城市活力.
- 确定了关键的非线性值:POI混合>1.5,密度下降回报超过4000单位/平方公里,开放度呈现反转的U形关系.
结论:
- 拟议的框架加强了全面城市活力的测量.
- 该研究通过结合主观感知来扩展传统的建筑环境指标.
- 为城市规划提供了一种新的分析方法,特别是在历史复杂的城市.
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