Li, X., Ratti, C., & Seiferling, I. (2018). Quantifying the shade provision of street trees in urban landscape: A case study in Boston, USA, using Google Street View. Landscape and Urban Planning, 169, 81-91.

Li, X., Ratti, C., & Seiferling, I. (2018). Quantifying the shade provision of street trees in urban landscape: A case study in Boston, USA, using Google Street View. Landscape and Urban Planning, 169, 81-91. https://doi.org/10.1016/j.landurbplan.2017.08.011

 

1. Introduction

• research necessity
  • a study on how to increase thermal comfort levels in urban spaces, particularly under global warming and rapid urbanization, has become a prominent topic in urban studies and is of key interest to decision-makers.
• research gap
  • there is little quantitative information about the extent and distribution of urban tree ecosystem services
  • canopy cover measured from aerial or satellite imagery cannot fully capture the shading effectiveness 
• sky view factor (SVF)
  • 0: when the sky is totally obstructed
  • 1: when there is no obstruction

 

2. Literature review

• SVF calculation
  • photographic method
    • using a fisheye camera lens
    • Hugin: open source panorama-generating tool (Google Street View (GSV) panorama to fisheye images) 
  • GPS signal-based method
    • using regression model
  • simulation method
    • 3D city models or Digital Surface Models (DSMs)

 

3. Study area and data

• study area
  • downtown area of Boston, Massachusetts, USA
• data
  • Google Street View (GSV) panorama
    • 319 GSVs during the green season
    • remove 22 panoramas taken in the tunnel
    • finally 297 GSVs remained
  • building footprint map
    • gained from MassGIS data (http://www.mass.gov)
  • street map of the city
    • gained from MassGIS data (http://www.mass.gov)
  • tree canopy cover map
    • gained from remotely sensed data by Raciti et al. (2014)
  • normalized Digital Surface Model (nDSM)
    • generated from LiDAR cloud point data with a spatial resolution of one meter
    • LiDAR was gained from NOAA Digital Coast
  • building height model
    • generated by overlaying the nDSM on the building footprint map

 

4. Methodology

• propose a GSV-based photographic method in combination with a building height model-based simulation method to calculate the "all-inclusive" sky view factor (SVF_p) and the "building-only" sky view factor (SVF_s)

 

5. Results

• street canyon cities surrounded by high-rise buildings have low SVF values, while the periphery of the study area has high SVF values

 

6. Discussion

• shading effectiveness of street trees is affected by tree canopy and the height of building blocks along streets
• the building height has a significant and negative correlation with the shading effectiveness of street trees, indicating that high-rise buildings overshadow any trees growing below them
• The surrounding tree canopy coverage and the canopy height have significant and positive correlations with the shade provision by the street trees

 

7. Conclusion

• The difference between these two values (SVF_s - SVF_p) defines the shading effectiveness attributable solely to street trees
• In Boston, street trees reduced the SVF by an average of approximately 18.52%
• street tree planting is an effective way to increase the shade coverage in street canyons, particularly in areas where the building heights are moderate to low