Supervisor: Dr. Scott Lamoureux
My research focuses on the interconnectivity of subsurface and surface processes at a fine-scale within the Canadian High Arctic. I focus on monitoring water table development and land surface change (i.e. subsidence and uplift) to better understand how these systems develop throughout the thaw season. An understanding of current processes and drivers is crucial to understanding how these systems may change under different climatic conditions.
Supervisor: Dr. Paul Treitz
My research project will be investigating environmental change at Cape Bounty, NU in the Canadian High Arctic. I will be using annual high resolution satellite imagery to investigate changes in vegetation (cover, greenness and distribution) and permafrost and subsequent re-vegetation of the disturbed areas. In addition, I will be comparing the trends in the satellite imagery to carbon flux measurements from eddy covariance towers and vegetation samples in 2003, 2008 and 2017. Multi-year investigations like this are are crucial in improving our understanding of the Arctic’s natural variation present and how it responds to changes in climate.
My research looks at ways we can monitor surface disturbances due to permafrost degradation via differential interferometry with satellite synthetic aperture radar (SAR) ‘images’. I’m also interested in how well different bio- and geo-physical variables such as ground ice content and soil moisture may predict an area’s susceptibility to future disturbances, with the aim of developing a ‘susceptibility raster’ for our study site at CBAWO. Emphasis will be placed on describing surface roughness on a number of different scales, with the satellite imagery, drone imagery and pin profilometer measurements capturing the large, medium and small scales respectively.
Supervisor: Dr. Paul Treitz
Vegetation indices, collected using remote sensing, can be utilized as proxies for modelling green gross ecosystem productivity (GEP), and therefore can be used to estimate net ecosystem exchange (NEE) of CO2. My research will examine the relationship between the seasonal variability of NEE and the normalized difference vegetation index (NDVI) for a mesic vegetation site at the CBAWO. The seasonal NEE of CO2 will be derived using the eddy covariance method based on data collected by sensors deployed on a flux tower. Meanwhile, multi-spatial resolution NDVI data will be collected throughout the growing season (i.e. emergence, growth, maturity, senescence) for the tower footprint. By determining the relationship between seasonal NEE of CO2 and NDVI, it will be possible to upscale seasonal NEE using satellite NDVI data and examine tundra vegetation response to climate warming over time