Home | Our members | Contact us | Français | |  

Vincent Sasseville

 

Ph.D. student

Department of Applied Geomatics, Université de Sherbrooke

2500, boul. de l'Université
Université de Sherbrooke
Quebec, Canada
J1K 2R1

8199430766
Vincent.Sasseville@USherbrooke.ca

 

 


 

Direction

 
 

Projet de recherche

Implementation of a habitat quality index for the Peary caribou using snow geophysical properties retrieved from satellite remote sensing and modeling

The enhanced warming observed in the arctic region already generated strong feedbacks in last three decades. The actual warming is estimated at +1.06°C/decades in the Arctic, while the rest of the planet is estimated at +0.45°C/decades or in Canada at +0.24°C/decades). Thus, patterns of negative anomalies in mass balances and spatial snow cover are observed, with a significant impact on how the cryosphere responds to climate change. One effect of this warming is the increased occurrence of rain on snow (ROS) events that leads to the formation of ice crust in the snow pack. This phenomenon affects the capacity of the Peary caribou to reach their food on the ground underneath the snowpack and is a cause for the population decrease observed over the last three generations (70%). This issue is further amplified when the snow density is high. Currently, there is no assessment possible with regards to future grazing conditions for the Peary caribou, and it is expected for the project to provide baseline data on the horizon of 2100 using a modeling approach.

The aim of this project is, therefore, to produce a quality index for the Peary caribou in northern Canada. Given the vast study area in the Canadian Arctic Archipelago, new technologies such as remote sensing and modeling will be required. As a first step, to detect the presence of the ice layers and ROS events, passive microwave satellite data will be used and detection algorithms will be developed. Furthermore, the properties of the snow cover will be simulated using the SNOWPACK model, forced with meteorological data from in-situ weather stations, reanalyses and climate models. The model will be adapted for the arctic snow and will be validated using field observations from yearly field campaigns. Finally, with both, the results of satellite data and the snow cover simulations, it will be possible to produce a system to monitor the habitat of the Peary caribou in real time by updating the quality index. This will help to better predict future migrations and survival chances of the species.
 
 

Scientific communications

Vargel, C., Royer, A., Saint-Jean Rondeau, O., Picard, G., Roy, A.R., Sasseville, V., Langlois, A., 2020. Arctic and subarctic snow microstructure analysis for microwave brightness temperature simulations. Remote Sensing of Environment, 242, 11754. DOI: 10.1016/j.rse.2020.111754.

 
© 2020 All rights reserved | Adapted from an original design by BinaryTheme.com