Landscape Ecology

, Volume 33, Issue 3, pp 491–511 | Cite as

Integrating airborne lidar and satellite imagery to model habitat connectivity dynamics for spatial conservation prioritization

  • Xuan Guo
  • Nicholas C. Coops
  • Sarah E. Gergel
  • Christopher W. Bater
  • Scott E. Nielsen
  • J. John Stadt
  • Mark Drever
Research Article



The application of regional-level airborne lidar (light detection and ranging) data to characterize habitat patches and model habitat connectivity over large landscapes has not been well explored. Maintaining a connected network of habitat in the presence of anthropogenic disturbances is essential for regional-level conservation planning and the maintenance of biodiversity values.


We quantified variation in connectivity following simulated changes in land cover and contrasted outcomes when different conservation priorities were emphasized.


First, we defined habitat patches using vegetation structural attributes identified via lidar. Second, habitat networks were constructed for different forest types and assessed using network connectivity metrics. And finally, land cover change scenarios were simulated using a series of habitat patch removals, representing the impact of implementing different spatial prioritization schemes.


Networks for different forest structure types produced very different patch distributions. Conservation scenarios based on different schemes led to contrasting changes during land cover change simulations: the scheme prioritizing only habitat area resulted in immediate near-term losses in connectivity, whereas the scheme considering both habitat area and their spatial configurations maintained the overall connectivity most effectively. Adding climate constraints did not diminish or improve overall connectivity.


Both habitat area and habitat configuration should be considered in dynamic modeling of habitat connectivity under changing landscapes. This research provides a framework for integrating forest structure and cover attributes obtained from remote sensing data into network connectivity modeling, and may serve as a prototype for multi-criteria forest management and conservation planning.


Vegetation structure Biodiversity conservation Network analysis Inter-patch connectivity Climate stability Alberta Canada 



This work was funded by the Government of Alberta (GOA: 16GRFMB08) and a Natural Sciences and Engineering Research Council (NSERC) (RGPIN 311926-13 and 6563) Discovery grant to N. Coops. The ALS data were provided by Alberta Agriculture and Forestry.


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Authors and Affiliations

  1. 1.Faculty of ForestryUniversity of British ColumbiaVancouverCanada
  2. 2.Forest Management Branch, Forestry DivisionAlberta Agriculture and ForestryEdmontonCanada
  3. 3.Department of Renewable Resources, Faculty of Agricultural, Life, and Environmental SciencesUniversity of AlbertaEdmontonCanada
  4. 4.Canadian Wildlife Service, Environment and Climate Change CanadaPacific Wildlife Research CentreDeltaCanada

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