Browsing by Author "Poley, Lucy Gem"

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    Modelling and Mapping Fine-Scale Vegetation Biomass in Banff National Park Using Remotely Sensed Data Collected by Unmanned Aerial Systems
    (2020-05-12) Poley, Lucy Gem; McDermid, Gregory J.; Bender, Darren J.; Hugenholtz, Chris H.
    Ecological investigations and long-term monitoring programs in grassland ecosystems often require detailed information on vegetation parameters across an area of interest. However, characterization of grassland vegetation is challenging using ground-based measurements or satellite imagery due to the fine-scale heterogeneity present in grasslands. Unmanned Aerial Systems (UASs) provide a way to characterize vegetation at a high spatial resolution, bridging the gap between ground-based measurements and satellite imagery. Motivated by the need for long-term monitoring of fine-scale vegetation parameters following the reintroduction of plains bison (Bison bison bison) to Banff National Park, Canada, this research explored how UAS-derived data could be used to estimate the aboveground biomass of vegetation at remote grassland sites in Banff’s bison reintroduction zone. I assessed the factors affecting quality of UAS-based vegetation estimation in previous research to design a series of analytical experiments. I conducted UAS surveys at study sites in July 2018 using visible-light and multispectral sensors. Concurrent to the aerial surveys, I collected ground-based data on shrub and herbaceous vegetation biomass. I derived spectral and textural variables using one or more wavelengths of light from the UAS imagery and related to ground-measured biomass using linear regression models. I accurately estimated shrub biomass using an area-weighted vegetation index derived from visible-light imagery that fused spectral and structural information into one parsimonious model. For herbaceous vegetation, combining visible-light and multispectral texture information derived from vegetation indices was the best approach to biomass estimation, and I was able to quantify the relative contributions of photosynthetic and non-photosynthetic vegetation within total biomass. I then modelled the distribution of shrub and herbaceous vegetation biomass across the study site and a workflow for collecting and analyzing UAS imagery for vegetation biomass monitoring was developed. The methods and maps of grassland vegetation produced in this study will provide the data and workflow necessary to monitor fine-scale impacts of bison on vegetation in Banff National Park, supporting conservation and management of this ecologically important species. This research also increases general knowledge of remote sensing of vegetation and provides an approach to fine-scale vegetation characterization suitable for ecological investigations in grasslands ecosystems