Urban trees can significantly improve the outdoor thermal environment, especially in subtropical zones. However, due to the lack of fundamental evaluations of numerical simulation models, design and modification strategies for optimizing the thermal environment in subtropical hot-humid climate zones cannot be proposed accurately. To resolve this issue, this study investigated the physiological parameters (leaf surface temperature and vapor flux) and thermal effects (solar radiation, air temperature, and humidity) of four common tree species (Michelia alba, Mangifera indica, Ficus microcarpa, and Bauhinia blakeana) in both spring and summer in Guangzhou, China. A comprehensive comparison of the observed and modeled data from ENVI-met (v4.2 Science, a three-dimensional microclimate model) was performed. The results show that the most fundamental weakness of ENVI-met is the limitation of input solar radiation, which cannot be input hourly in the current version and may impact the thermal environment in simulation. For the tree model, the discrepancy between modeled and observed microclimate parameters was acceptable. However, for the physiological parameters, ENVI-met tended to overestimate the leaf surface temperature and underestimate the vapor flux, especially at midday in summer. The simplified calculation of the tree model may be one of the main reasons. Furthermore, the thermal effect of trees, meaning the differences between nearby treeless sites and shaded areas, were all underestimated in ENVI-met for each microclimate variable. This study shows that the tree model is suitable in subtropical hot-humid climates, but also needs some improvement.

The evaluation and renovation of existing building envelope has important practical significance for energy conservation and emission reduction in the field of architecture. With the development of digital cities, 3D models with rich temperature information can realize the comprehensive and accurate detection and evaluation of the existing building envelope. However, the 3D model reconstructed from thermal infrared images has only relative temperature distribution and no temperature value of each location, so it is impossible to quantify the extent of the defect from it. To solve this issue, this paper develops a method to establish a 3D point cloud model with temperature information at selected points. The proposed 3D model is generated based on the thermal infrared images acquired by an unmanned aerial vehicle (UAV) equipped with an infrared camera. In the generated 3D thermal infrared model, we can not only get the relative temperature distribution of the building’s full envelope structure, but also obtain the exact temperature value of any selected point. This method has been verified by field measurements and the result shows that the deviation is within 5 °C. In addition to temperature information, the generated 3D model also has spatial and depth information, which can reflect the appearance information and 3D structure of the monitoring target more realistically. Thus, by using this method, it is possible to achieve a comprehensive, accurate, and efficient on-site assessment of the building envelope in the urban area.