Modelling connectivity of woody vegetation and its structure at the national scale for Switzerland

Authors and Affiliations: 

Price, B. and Ginzler, C.

Remote Sensing Group, Landscape Dynamics, Swiss Federal Institute for Forest, Snow and Landscape Research WSL (Switzerland)

Corresponding author: 
Bronwyn Price

Forest connectivity may be enhanced by elements in the landscape such as trees and patches of trees outside of forest. In addition, landscape function and effective habitat connectivity will be determined not only by the presence of a binary forest cover maps but also other habitat characteristics such as the physical 3D structure of the woody vegetation. For purposes of planning, monitoring and adaptive connectivity management, the ability to model and understand connectivity at a large spatial extent but fine resolution is invaluable for regional to local scale insights. We take advantage of the nation-wide, high resolution (1m) canopy height model (CHM) for Switzerland (Ginzler and Hobi 2015) and a binary forest map (Waser et al. 2015) based on this data to map and model connectivity of woody vegetation at a range of spatial resolutions at the national extent. To consider the importance of vegetation structure we analyse connectivity for areas of tall vegetation (over 25m) and low height woody vegetation and identify areas which are of greatest importance for maintaining or enhancing connectivity across Switzerland. We determine connectivity through several approaches including traditional connectivity metrics and analysis and mapping using circuit theory. The connectivity of tall woody vegetation is significantly lower than for areas of lower canopy height or for woody vegetation in general, which has important implications for the management of connectivity for species dependent on tall trees, for example for nesting purposes. The Swiss CHM is derived from stereo aerial photography which is collected on a rolling repeat basis. Therefore, using this methodology we have the potential opportunity to monitor changes in connectivity of woody vegetation, including structural attributes, over time.

Key words: canopy height model (CHM), tree cover, 3D vegetation structure, stereo-imagery


Ginzler, C.; Hobi, M.L., 2015. Countrywide stereo-image matching for updating digital surface models in the framework of the Swiss National Forest Inventory. Remote Sens. 7: 4343-4370.

Waser, L.T., Fischer C., Wang Z., Ginzler C., 2015. Wall-to-wall forest mapping based on digital surface models from image-based point clouds and a NFI forest definition. Forests 6: 4510-4528.

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