基于深度学习和街景图像的城市环境和抑郁感知之间的合机制的研究
Haozun Sun1, Nan Zhang2, Yixin Jiang1
1School of Architecture and Art, Central South University, Changsha, 410083, China.
Scientific reports
|January 20, 2026
概括
城市环境对居民的心理健康有重大影响. 这项研究使用深度学习来将街道水平的视觉元素,如绿色空间和建筑围,与抑郁感知联系起来,为更健康的城市设计提供见解.
科学领域:
- 城市规划和环境心理学
- 在社会科学中的深度学习应用.
- 公共卫生和心理健康.
背景情况:
- 加快的城市化引发了人们对城市环境对心理健康的影响的担忧.
- 现有的研究往往忽略了多维的城市元素,缺乏精细的量化分析.
- 方法和数据的局限性阻碍了对城市环境与心理健康联系的全面理解.
研究的目的:
- 开发一种新的深度学习 (DL) 方法来量化与城市环境相关的抑郁感知 (DP).
- 确定特定的城市视觉元素,以精细的规模影响居民的DP.
- 为了解街道级城市元素与心理健康之间的关系提供一个定量框架.
主要方法:
- 建立一个大规模的数据库 (133,114) 的街景图像 (SVI).
- 提取六个关键视觉元素:绿色视图指数 (GVI),天空视图因子 (SVF),封闭程度 (DOE),机动化程度 (DOM),非机动化程度 (DON) 和人行道率 (ROS).
- 应用逐步回归来分析城市元素和DP之间的相关性.
主要成果:
- 绿色视图指数 (GVI),天空视图因子 (SVF) 和非机动化程度 (DON) 显示与抑郁感知 (DP) 有负相关性.
- 高度的封闭 (DOE) 和机动化程度 (DOM) 与负面情绪的风险增加有关.
- 空间分析显示,沿运输工业走廊的DP高,沿蓝绿色和文化走廊的DP低;历史区显示缓冲效应.
结论:
- 建立了街道级城市环境和抑郁感知之间的重要联系.
- 扩大了健康城市设计的"情感空间"机制的理论框架.
- 为城市更新,街道开发和绿色基础设施规划提供实用,定量支持和以情感为导向的战略.
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