Data underlying the publication: Comparative Analysis of Geospatial Tools for Solar Simulation
收藏DataCite Commons2025-03-11 更新2025-04-08 收录
下载链接:
https://data.4tu.nl/datasets/762b7253-556b-47b6-a7be-8360f7086640
下载链接
链接失效反馈官方服务:
资源简介:
This paper performs, describes, and evaluates a comparison of seven software tools (ArcGIS Pro, GRASS GIS, SAGA GIS, CitySim, Ladybug, SimStadt and UMEP) to calculate solar irradiation. The analysis focuses on data requirements, software usability, and accuracy simulation output. The use case for the comparison is solar irradiation on building surfaces, in particular on roofs. The research involves collecting and preparing spatial and weather data. Two test areas - the Santana district in S ̃ao Paulo, Brazil, and the Heino rural area in Raalte, the Netherlands - were selected. In both cases, the study area encompasses the vicinity of a weather station. Therefore, the meteorological data from these stations serve as ground truth for the validation of the simulation results. We create several models (raster and vector) to meet the diverse input requirements. We present our findings and discuss the output from the software tools from both quantitative and qualitative points of view. Vector-based simulation models offer better results than raster-based ones. However, they have more complex data requirements. Future research will focus on evaluating the quality of the simulation results on vertical and tilted surfaces as well as the calculation of direct and diffuse solar irradiation values for vector-based methods.
本研究针对7款用于太阳辐射计算的软件工具(ArcGIS Pro、GRASS GIS、SAGA GIS、CitySim、Ladybug、SimStadt及UMEP)开展对比实验,详述其技术特性并完成性能评估。本次分析聚焦于数据需求、软件易用性与模拟输出精度三大核心维度,对比应用场景设定为建筑表面(尤以屋顶为重点)的太阳辐射计算。研究流程涵盖空间数据与气象数据的采集与预处理环节。本次实验选取两处测试区域:巴西圣保罗市桑塔纳街区,以及荷兰拉尔特市海诺乡村区域,两处研究区域均覆盖对应气象站的周边范围,因此可利用该气象站的实测气象数据作为模拟结果验证的地面真值(ground truth)。为适配不同软件的多样化输入要求,我们构建了多组模型,包括栅格模型与矢量模型。本文将呈现本次研究的核心发现,并从定量与定性双维度对各软件工具的输出结果展开讨论。研究结果显示,基于矢量的模拟模型相较基于栅格的模型具备更优异的计算效果,但数据需求更为复杂。未来研究将聚焦于垂直与倾斜表面的模拟结果质量评估,以及针对矢量方法的直接太阳辐射与散射太阳辐射数值计算环节。
提供机构:
4TU.ResearchData
创建时间:
2025-03-11



