Urban Ecosystems

, Volume 19, Issue 4, pp 1749–1765 | Cite as

Using high-resolution LiDAR data to quantify the three-dimensional structure of vegetation in urban green space

  • Rhiannon J. C. Caynes
  • Matthew G. E. Mitchell
  • Dan Sabrina Wu
  • Kasper Johansen
  • Jonathan R. Rhodes


The spatial arrangement and vertical structure of vegetation in urban green spaces are key factors in determining the types of benefits that urban parks provide to people. This includes opportunities for recreation, spiritual fulfilment and biodiversity conservation. However, there has been little consideration of how the fine-scale spatial and vertical structure of vegetation is distributed in urban parks, primarily due to limitations in methods for doing so. We addressed this gap by developing a method using Light Detection and Ranging (LiDAR) data to map, at a fine resolution, tree cover, vegetation spatial arrangement, and vegetation vertical structure. We then applied this method to urban parks in Brisbane, Australia. We found that parks varied mainly in their amount of tree cover and its spatial arrangement, but also in vegetation vertical structure. Interestingly, the vertical structure of vegetation was largely independent of its cover and spatial arrangement. This suggests that vertical structure may be being managed independently to tree cover to provide different benefits across urban parks with different levels of tree cover. Finally, we were able to classify parks into three distinct classes that explicitly account for both the spatial and vertical structure of tree cover. Our approach for mapping the three-dimensional vegetation structure of urban green space provides a much more nuanced and functional description of urban parks than has previously been possible. Future research is now needed to quantify the relationships between vegetation structure and the actual benefits people derive from urban green space.


Vegetation vertical structure Vegetation spatial structure Urban parks LiDAR Brisbane, Australia Remote sensing 



This research was supported by Australian Research Council Discovery Project DP130100218. We thank Brisbane City Council for assisting with and providing data sets, Danielle Shanahan for assisting with the parks data, and the Departments of Science, Information Technology and Innovation and Natural Resources and Mines for providing access to the airborne LiDAR data. The authors also thank three anonymous reviewers for comments that greatly improved the manuscript.

Supplementary material

11252_2016_571_MOESM1_ESM.pdf (5.3 mb)
ESM 1 (PDF 5.27 mb)


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Rhiannon J. C. Caynes
    • 1
  • Matthew G. E. Mitchell
    • 1
  • Dan Sabrina Wu
    • 1
  • Kasper Johansen
    • 1
  • Jonathan R. Rhodes
    • 1
  1. 1.School of Geography, Planning and Environmental ManagementThe University of QueenslandBrisbaneAustralia

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