Towards capturing detailed patterns of taiga-tundra ecotone forests from space

Abstract:

High northern latitude forests, particularly those in the taiga-tundra ecotone (TTE), lie at the leading edge of climate change. The structure of these forests contribute to climate feedbacks by modifying surface albedo and above- and below-ground carbon storage. These modifications are associated with vertical and horizontal forest characteristics such as tree height and canopy cover. These characteristics are changing unevenly throughout the TTE, and the degree to which forests are vulnerable to such changes varies, in part, according to whether the primary drivers of their response are controlled by site-scale factors or climate.

Observing spatial variations in TTE forest structure is difficult given the uncertainties associated with spaceborne measurements of sparse forests. Global-scale spaceborne observations of these forests tend to overestimate sparse tree cover. This overestimation increases the uncertainty in the patterns of forests that may reflect critical site-scale controls of its structure, its vulnerability to change and the potential for climate feedbacks. The key to improving prediction of feedbacks between TTE forests and climate may be linked to how well we understand the fine-scale patterns of heterogeneous TTE forest structure.

We examine the spaceborne potential for delineating fine-scale (< 2m) forest structure (height and cover) in sparse forests in the TTE. We apply automated digital stereo-photogrammetry to high resolution spaceborne images. This processing allows us to combine surface elevation models and multispectral data at forested study sites to extract detailed vertical and horizontal forest structure characteristics. With this data, we can validate coarser (~30m) global tree cover data, model forest structure characteristics and patterns, and use these patterns to examine the differences in the vulnerability of TTE forest structure at multiple scales across the circumpolar domain.