Quantification and Measurement of Combined Building–Tree Shadows via a Panoramic-Photo-Based Approach for Thermal Environment Assessment

In hot and humid areas, combined shadows from buildings and trees are critical to imagery involving outdoor thermal environments, but are difficult to quantify in complex building–tree intertwined surroundings. This study introduces a shadow geographical ratio (SGR) to quantify combined shadow coverage and proposes a panoramic-photo-based measurement (PPM) framework to compute SGR. Field validation on the campus of Xiamen University, China, using UAV imagery as reference, gave a mean relative error of 1.69% and an RMSE of 0.03 for PPM-derived SGR. The results further showed that SGR was strongly correlated with the sky view factor (SVF) and exhibited significantly higher sensitivity to thermal environment and comfort indicators than SVF, except for relative humidity. Conversely, SVF correlated more strongly with thermal stability. The PPM framework features pedestrian-scale characterization, minimal hardware requirements, and robust error control. The SGR and PPM frameworks offer a practical method for shadow data acquisition in complex environments, supporting microclimate optimization in hot and humid climates. This approach facilitates field data collection and simulation calibration, advancing future studies of shadows.