Remote Sensing of Vegetation Change Across a Latitudinal Gradient in the Canadian Arctic

Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.

On the feasibility of time-lapse superconducting gravimetry for reservoir monitoring

The feasibility of monitoring fluid flow subsurface processes that result in density changes, using the iGrav superconducting gravimeter, is investigated. Practical targets include steam-assisted gravity drainage (SAGD) bitumen depletion and water pumping from aquifers, for which there is currently a void in low-impact, inexpensive monitoring techniques. This study demonstrates that the iGrav has the potential to be applied to multi-scale and diverse reservoirs. Gravity and gravity gradient signals are forward modeled for a real SAGD reservoir at two time steps, and for surface-fed and groundwater-fed aquifer pumping models, to estimate signal strength and directional dependency of water flow. Time-lapse gravimetry on small-scale reservoirs exhibits two obstacles, namely, a µgal sensitivity requirement and high noise levels in the vicinity of the reservoir. In this study, both limitations are overcome by proposing (i) a portable superconducting gravimeter, and (ii) a pair of instruments under various baseline geometries. This results in improved spatial resolution for locating depletion zones, as well as the cancellation of noise common in both instruments. Results indicate that a pair of iGrav superconducting gravimeters meet the sensitivity requirements and the spatial focusing desired to monitor SAGD bitumen migration at the reservoir scales. For SAGD reservoirs, the well pair separation, reservoir depth, and survey sampling determine the resolvability of individual well pair depletion patterns during the steam chamber rising phase, and general reservoir depletion patterns during the steam chamber spreading phase. Results show that monitoring water table elevation changes due to pumping and tracking whether groundwater or surface water is being extracted are feasible.