LAUSR

Street greenery plays an essential role in improving the street environment and residents’ health. The evaluation of street greenery is of great value to establish environmentally friendly streets. The evaluation indicators of present studies evaluating street greenery were relatively single, either the Green View Index (GVI) or Normalized Difference Vegetation Index (NDVI), which cannot describe the greenery condition in its entirety. The objective of this study is to assess the street greenery using multiple indicators, including GVI, NDVI, and Vegetation Structural Diversity (VSD). We combined street view images with a semantic segmentation method to extract the GVI and VSD and used satellite images to calculate the NDVI in the urban area of Nanjing, China. We found correlations and discrepancies of these indicators using statistical analyses in different urban districts, functional areas, and road levels. The results indicate that: (1) the GVI and NDVI are strongly correlated in open spaces, whereas weakly correlated in residential and industrial lands, (2) the areas with higher VSD are mainly located in the new city, whereas the VSD in the old city is lower, and a weak negative correlation exists between the GVI and VSD in the research area, and (3) the old city has a higher GVI level compared to the new city on the main road, whereas the new city has a higher GVI level than the old city on the branch road. Compared with the GVI, the trend of VSD in the old city and the new city is relatively consistent. Our findings suggest that considering multiple indicators of street greenery evaluation can provide a comprehensive reference for building more human-friendly and diversified street green belts.