REMOTE SENSING OF BIOPHYSICAL VARIABLES AT MULTIPLE SPATIAL SCALES ALONG A LATITUDINAL GRADIENT IN THE CANADIAN ARCTIC

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Tundra ecosystems account for a large proportion of Canada’s land surface and are important systems within the context of environmental change research. Tundra ecosystems are thought to be particularly sensitive to changes in climate, yet it remains unclear as to how they will respond. Changes in tundra ecosystem patterns and processes will be expressed through shifts in vegetation phenology and species composition and abundance. In addition to the obvious impacts of increasing air temperatures, there are a number of factors that serve as controls on vegetation growth in the Canadian Arctic, including soil moisture, nutrient availability, soil type and topography/micro-topography, some of which are also impacted by warming temperatures. Hence, high spatial resolution remote sensing provides an opportunity to estimate and monitor vegetation variability, with the potential to quantify biophysical variables that control carbon fluxes over large areas. However, detailed in situ studies are required for calibration and validation of appropriate remote sensing models to estimate these variables. The focus of my NSERC Discovery Grant will be on modeling biophysical variables at multiple scales along a latitudinal gradient (~64°-75°N) for the Canadian Arctic; providing a mean-July temperature gradient of approximately 10°C. This research will be conducted at Sabine Peninsula (77ºN) and Cape Bounty (75ºN), Melville Island; Boothia Peninsula (71ºN); and Apex River, Baffin Island (64ºN), Nunavut. Although there have been studies examining biophysical variables at these latitudes, they have largely been limited to broad spatial scales (i.e., 1-8 km2) with limited field support. There has been very little research conducted in Canada's North on relating biophysical variables to high spatial resolution remote sensing data (<10 m); nor how these variables are linked to ecosystem processes (e.g., carbon flux/net ecosystem exchange). My research will: (i) quantify the relationships between biophysical variables and spectral reflectance at high spatial resolutions; (ii) model the relationships between biophysical variables and ecosystem processes; and (iii) model biophysical variables, including carbon exchange, at multiple scales in order to project changes in these variables over space and time. Variables of significance for productivity modeling and estimating net ecosystem exchange include above-ground phytomass, percent vegetation cover and fraction of absorbed photosynthetically active radiation. These are critical structural and physiological variables linked to many ecosystem processes (e.g., phytomass plays a significant role in assessing carbon stocks, is an important element in global change and productivity models, and is a measure of vegetation community structure which influences biodiversity). These variables will be measured using direct measurement and photo-plot techniques employing near-infrared photography and spectral indices. In order to scale up variables, models will be developed between field measurements and photo-plot data for comparison to high (WorldView-2), intermediate (Landsat 8) and coarse (MODIS) resolution remote sensing data. With the results of this research, i.e., modeling of biophysical variables and ecosystem processes at multiple scales, we will be able to make knowledgeable policy decisions related to development in the North. In addition, this research will help us develop adaptation strategies for communities and resource industries living and operating in Canada’s North. Finally, training of undergraduate and graduate students will contribute to the next generation of Arctic scientists, specifically earth and environmental scientists trained in arctic field methods and remote sensing image processing.