Pedestrian-view urban street vegetation monitoring using Baidu Street View images

AimsThe distribution pattern of green vegetation in urban streets has significant impacts on urban ecological environment and physical/mental health of local residents.Accurate detecting and monitoring of street green information is of great significance for precise urban planning and management, while there are few studies focusing on urban greenery estimation using profile image system. MethodsIn this study, combining network information capturing and geospatial information analysis technology, Taiʼan city was selected as the case study area.Based on the Baidu application programming interface (API), a total of 3 276 Baidu Street View (BSV) images of 273 research samples were obtained and processed, and the green vegetation pixels in the image were extracted by computer supervised classification and compared with the artificial extraction results.Based on the proposed Baidu Street Vegetation Distribution Index (BSVDI), we monitored the street vegetation's distribution characteristics from the pedestrian perspective, and analyzed the streetscale vegetation distribution pattern. Important findingsThe BSV image could be used as the main data source to monitor the distribution of green trees and lawns in pedestrian's perspective on the street scale.BSVDI was higher in the center, northeast and southeast of the study area than the other regions.BSVDI and remote sensing extracted vegetation covered area ©植物生态学报 Chinese Journal of Plant Ecology扫 码 提 问 206 植物生态学报