Deriving Environmental Properties Related to Human Environmental Perception: A Comparison Between Aerial Image Classification and Street View Image Segmentation

In recent decades, urban residents’ perceptions of their surrounding environment have been widely studied, especially pertaining to the association between environmental settings and humans’ psychological wellbeing. Many studies have used aerial imagery to derive environmental properties through image classification to approximate humans’ perceived environment, while a growing number of studies use street view imagery to achieve the same with image segmentation. There is limited research comparing the two approaches. This study aims to examine how the environmental properties derived from aerial and street view images correspond with each other. We utilized two study sites in urban communities in New Jersey, United States. High-resolution aerial images were acquired and classified to derive environmental properties within set buffer zones around sample points where Google Street View images were collected for image segmentation to derive corresponding environmental properties. Several buffer sizes were experimented with. The results show that the amount of greenness and individual environmental elements derived from street view versus aerial images can be quite different at the same locations. The amount of trees derived has a greater concordance between aerial and street views than the amount of buildings derived. The amounts of grass and roads are not in agreement between the two views. Trees derived from street view images correspond with those derived from aerial better when using a small, 30 m buffer. Low-rise buildings and grass agree better when using larger buffer sizes such as 60 m and 100 m. Roads correspond better when larger buffers are employed in green environments, but smaller buffers in environments with limited greenness. Our findings indicate that the choice of buffer size used when combining environmental properties derived from both aerial and street view images together should consider both the environmental elements involved and the type of environmental settings.