对建筑物和社区数据进行统计处理,考虑爱尔兰都柏林的能源等级
Nasim Eslamirad1, Mehdi Gholamnia1, Payam Sajadi1
1School of Architecture Planning and Environmental Policy, University College Dublin, Ireland.
Data in brief
|October 21, 2024
概括
这项研究通过使用地理空间工具整合建筑和城市背景数据来增强城市能源分析. 这种方法支持数据驱动的战略,用于都柏林的可持续建筑和社区能源规划.
科学领域:
- 城市规划 城市规划
- 地理空间分析是什么
- 建筑的能源性能 建筑的能源性能
背景情况:
- 城市能源分析传统上依赖于有限的建筑特定数据.
- 整合城市背景数据对于全面了解能源动态至关重要.
- 地理空间数据为全面的城市分析提供了强大的框架.
研究的目的:
- 通过使用综合的地理空间数据,提出一种提高城市能源分析的方法.
- 将建筑能源数据与城市背景信息结合起来进行详细分析.
- 为了实现可持续性和能源效率的数据驱动城市规划.
主要方法:
- 使用的地缘目录 建筑能源评级 (BER) 和数字景观模型 (DLM) 数据集用于都柏林.
- 在使用 MATLAB,Python (Geopandas,Pandas,NumPy,Seaborn,Scikit-learn),ArcGIS 和 QGIS 进行数据处理和地理空间分析.
- 集成的几何和非几何建筑和社区数据,用于多尺度分析.
主要成果:
- 在建筑和社区尺度上获得了全面的几何和非几何数据.
- 在地理空间背景下实现了有效的社区规模和建筑环境分析.
- 对建筑能源性能和城市能源动态产生了宝贵的见解.
结论:
- 该方法有效地整合了各种数据集,用于强大的城市能源分析.
- 综合数据集支持环境因素预测模型的开发.
- 这种方法促进了对都柏林可持续能源管理的明智城市规划策略.
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