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MSc Thesis Opportunity: Use of satellite imagery to detect non-point sources of pollution in streams

A two-year M.Sc. thesis scholarship is to work with Agriculture and Agri-Food Canada (AAFC) and Fluvial Systems Research (FSR) on satellite-based monitoring of water quality and detection of non-point source sources of pollution in streams across Canada. The work will focus on development of image processing algorithms, and will primarily be based on already-existing data sets derived from watersheds across Canada that include a range of water quality measurements, high-resolution satellite imagery, acoustics, and GPS. The successful candidate will be co-supervised by Dr. Anders Knudby (uOttawa), Dr. David Lapen (AAFC) and Dr. Stephen Bird (FSR), and will be housed at SWEOL. QUALIFICATIONS T

New UAV and hyperspectral sensor

This spring our new DJI Matrice 600 Pro finally arrived. Funded by NSERC, it will be used primarily to carry our Cubert S185 SE FireFleye hyperspectral frame camera, but can also be outfitted with a range of other sensor options. With a little luck and a lot of effort, we should be able to use the data from this camera to produce 3D hyperspectral point clouds (as demonstrated here).

Gearing up for fieldwork, Summer 2019

The ice is finally melting here in Ottawa, and we're getting ready for this season's fieldwork. - In Gatineau Park, satellite image processing based on field and drone data from 2017 and 2018 allowed us to predict the locations of three large patches of wild leek - a threatened plant species in Quebec. This spring we will go to those locations to test whether our predictions were correct - and find out whether out image processing was good or not! - In central Ontario, we will take our new drone and our new hyperspectral camera into the forest, to collect 3D hyperspectral data over a couple of forest plots. We will then test whether such data can be used to identify the tree species in those