Images capture the Earth through a lens and provide evidence for the world at that particular time and place. These images can be taken from satellites, cameras on the ground or from UAVs. There is now a vast array of satellite imagery that extend back to the mid 1900’s; the Landsat satellites (launched in 1972) constitute the longest time series of satellite data and is freely available to anyone that wishes to use it. I have used various optical satellite images to analyse a range of environmental phenomena and continue to actively pursue new research in this area.
I have a keen interest in using optical satellite imagery to understand glacier change. The power of Remote Sensing allows a user to analyse remote glaciers from their desk. Regions such as the Canadian Arctic and Greenland are especially remote and the lack of field measurements from these regions has impeded our understanding of how glaciers are responding to climate change. Using various Remote Sensing datasets (satellite imagery, altimetry and aergeophysical surveys) we have conducted an analysis of the fastest flowing glacier in the Canadian Arctic, the Trinity-Wykeham Glacier. Full details of this research will hopefully be published soon and details can be found here. I have also used similar data sets to analyse glacier velocity changes at John Evans Glacier, Canadian Arctic, and to analyse supraglacial and subglacial hydrology at Russell Glacier, Greenland.
Deriving spatial coverage estimates of seagrass is difficult due to their growth in water and their seasonal growth and decay. In order to aid spatial coverage estimates in East Africa, where studies on tropical coastal ecosystems are severely lacking, we analysed Landsat and Sentinel-2 imagery to understand 30-year changes in seagrass coverage. We found a decline in seagrass coverage across the coast of Kenya that accelerated beyond the 1980’s. Future studies should look to integrate these data sets with other spatial data on coastal population, land use changes and ocean temperatures in order to isolate the drivers of these changes. We also used underwater GoPro images (see below) to act as validation for our seagrass maps.
I was fortunate enough to attend the 2019 Innsbruck Summer School of Alpine Research where I learnt about a number of close range Remote Sensing techniques: UAV Photogrammetry, Terrestrial Photogrammetry, Lidar and Terrestrial Laser Scanning (TLS). TLS is an optical surveying instrument operating in the visible and infrared frequency range. It emits light and measures the total travel time to determine the range to a target. We used a Riegl TLS system to monitor landslide dynamics near Obergurgl, Austria. One of the key processing steps during TLS post-processing is to classify the point cloud into ground and non-ground points. We tested three algorithms to do this and the results will be presented at a conference soon.