地质空间城市数据的地质处理在塔林,爱沙尼亚
Nasim Eslamirad1, Francesco De Luca2, Kimmo Sakari Lylykangas2
1FinEst Centre for Smart Cities, Tallinn University of Technology, Tallinn, Estonia.
Data in brief
|June 29, 2023
概括
这项研究处理了多尺度的城市空间数据,以创建用于评估爱沙尼亚塔林城市热岛 (UHI) 效应的机器学习模型. 该数据集支持城市规划和可持续性目标.
科学领域:
- 环境科学 环境科学
- 城市规划 城市规划
- 数据科学数据科学数据科学
背景情况:
- 数字时代需要大规模,复杂的跨学科项目,可靠的数据库对于成功至关重要.
- 城市项目需要分析,以支持可持续发展目标,由指数级增长的空间数据驱动.
- 评估城市热岛 (UHI) 效应对于了解和减轻城市环境挑战至关重要.
研究的目的:
- 为了处理塔林,爱沙尼亚城市热岛 (UHI) 评估项目的多尺度城市空间数据.
- 为UHI分析构建一个生成,预测和可解释的机器学习模型.
- 为城市规划者,研究人员,建筑师和政策制定者提供必要的基线数据.
主要方法:
- 处理和整合多尺度城市空间数据.
- 开发一个包含生成,预测和可解释组件的机器学习模型.
- 用于UHI评估的数据集编制.
主要成果:
- 一个全面的多尺度城市数据数据集被生成.
- 该数据集作为机器学习模型的输入,用于预测和解释UHI效应.
- 处理的数据为各种城市发展利益相关者提供了基线信息.
结论:
- 开发的数据集对于推进城市热岛研究和评估至关重要.
- 该资源支持可持续城市规划和建筑环境项目的知情决策.
- 该数据集使利益相关者能够将城市数据纳入其战略,以改善城市特征和可持续性成果.
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