山东理工大学学报（自然科学版）

随着老旧住区改造的推进，改善开放空间微气候成为提升居民生活质量的关键。本研究以合肥南园新村为例，提出一种基于数字技术的老旧住区开放空间微气候模拟优化方法。该方法结合建筑信息模型(BIM)与三维点云技术，通过在Revit中应用点云模型，对老旧住区开放空间内建筑及植被形态进行精确还原，以提升老旧住区开放空间微气候模拟精度。根据场地不同位置的比较分析、点云模型与实测数据及ENVI-met模型的对比结果发现，点云模型的均方根误差(RMSE)比ENVI-met模型的低0.03～0.66,平均绝对百分比误差(MAPE)低0.15%～1.8%,一致性指数(d)提高0～0.011 02,表明点云模型在模拟精度上具有显著优势；此外，研究还分析了微气候的主要影响因素，提出了相应的改造措施，可为老旧住区微气候改善提供技术支持与参考。

With the advancement of renovation in old residential areas, improving the microclimate of open spaces has become crucial for enhancing the life quality of residents. Taking Nanyuan New Village in Hefei as an example, this study proposes a digital technology-based method, which combines Building Information Modeling(BIM) and 3D point cloud technology, to simulate and optimize the microclimate of open spaces in old residential areas. The point cloud model in Revit is employed to accurately reconstruct the shapes of buildings and vegetation within the open spaces, thereby improving the accuracy of the microclimate simulations. According to the comparative analysis of different locations on the site, the comparison results between the point cloud model, measured data, and the ENVI-met model show that the Root Mean Square Error(RMSE) of the point cloud model is lower than that of the ENVI-met model by a margin of 0.03 to 0.66, the Mean Absolute Percentage Error(MAPE) is 0.15% to 1.8% lower, and the Concordance Correlation Coefficient(d) increases by 0～0.011 02, indicating that the point cloud model has significant advantages in simulation accuracy. In addition, the study also analyzes the main influencing factors of the microclimate and proposes corresponding renovation measures, providing technical support and references for the improvement of the microclimate in old residential areas.