LAUSR

The significance of street-side greenery monitoring is increasing for precise urban planning and environmental management, especially in rapid sprawling urban cities, while there have been few studies focusing on urban greenery estimation using new profile image system. In this study, Baidu Street View (BSV) images, which were taken by Baidu vehicles and had view angles similar to those of pedestrians on the street, were selected for calculating the magnitude of street profile greenery. From 278 randomly selected street sample sites in Tai’an city of China, 3336 images were acquired via the Baidu Application Programming Interface (API). A Baidu Green View Index (BGVI) was proposed to quantitatively describe the street-side profile greenery. The results demonstrated that green vegetation can be distinguished efficiently from BSV images. The BGVI varied in the different portions of the study area, and it can be used to grade street system by considering pedestrians’ visualized greenery. Though BGVI had a significant correlation with the overlooking green canopy coverage, in some street sample sites it can delineate different scenarios. BGVI can be regarded as complementary information to urban planning and management.