Urban Ecosystems

, Volume 14, Issue 4, pp 617–634

Nature of vegetation and building morphology characteristics across a city: Influence on shadow patterns and mean radiant temperatures in London


DOI: 10.1007/s11252-011-0184-5

Cite this article as:
Lindberg, F. & Grimmond, C.S.B. Urban Ecosyst (2011) 14: 617. doi:10.1007/s11252-011-0184-5


Vegetation and building morphology characteristics are investigated at 19 sites on a north-south LiDAR transect across the megacity of London. Local maxima of mean building height and building plan area density at the city centre are evident. Surprisingly, the mean vegetation height (zv3) is also found to be highest in the city centre. From the LiDAR data various morphological parameters are derived as well as shadow patterns. Continuous images of the effects of buildings and of buildings plus vegetationon sky view factor (Ψ) are derived. A general reduction of Ψ is found, indicating the importance of including vegetation when deriving Ψ in urban areas. The contribution of vegetation to the shadowing at ground level is higher during summer than in autumn. Using these 3D data the influence on urban climate and mean radiant temperature (Tmrt) is calculated with SOLWEIG. The results from these simulations highlight that vegetation can be most effective at reducing heat stress within dense urban environments in summer. The daytime average Tmrt is found to be lowest in the densest urban environments due to shadowing; foremost from buildings but also from trees. It is clearly shown that this method could be used to quantify the influence of vegetation on Tmrt within the urban environment. The results presented in this paper highlight a number of possible climate sensitive planning practices for urban areas at the local scale (i.e. 102- 5 × 103 m).


LiDAR Shadow patterns Mean radiant temperature Sky view factor Urban vegetation Urban morphology SOLWEIG Spatial variability Urban trees 

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Environmental Monitoring and Modelling Group, Department of GeographyKing’s College LondonLondonUK
  2. 2.Department of Earth SciencesUniversity of GothenburgGothenburgSweden

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