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探索温度分布和城市形态与绿色视图指数之间的空间关联
Ta-Chien Chan1,2,3,4, Ping-Hsien Lee1, Yu-Ting Lee1
1Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan.
PloS one
|May 14, 2024
概括
城市热岛因缺乏绿色空间而恶化. 谷歌街景中的街道级绿色植被指数 (GVI) 与较低的城市温度有效相关,改善了城市规划.
科学领域:
- 城市气候学 城市气候学
- 环境科学 环境科学
- 地理信息系统 (GIS) 是一个地理信息系统.
背景情况:
- 城市热岛 (UHIs) 由于缺乏绿色空间,会对居民健康产生负面影响.
- 现有的卫星图像无法捕捉小规模的城市绿色特征,如街道树木.
- 准确评估社区级绿色空间对于了解城市环境质量至关重要.
研究的目的:
- 评估台北市行人级绿地与环境温度之间的关系.
- 评估谷歌街景图像和深度学习对城市绿色空间分析的实用性.
- 确定影响城市温度的环境和土地利用因素.
主要方法:
- 在谷歌街景数据上使用深度卷积神经网络语义细分模型.
- 提取的环境特征:绿色植被指数 (GVI),建筑景观因子和天空景观因子.
- 应用了线性混合效应模型和地理加权回归与月度温度数据 (2018-2021).
主要成果:
- 较高的GVI与较低的环境温度和温度差异显著相关.
- 增加的交通量和特定的土地用途 (宗教,政府) 与更高的环境温度相关.
- 来自街景的GVI有效地捕获了社区级绿色空间对温度的影响.
结论:
- 谷歌街景和深度学习为详细的城市绿色空间评估提供了一种新的方法.
- 用GVI量化的行人级绿色空间在缓解城市热量方面发挥着重要作用.
- 将GVI与社会和环境指标相结合,可以提高对城市气候和规划的理解.
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