Research
My research interests lie at the intersection of coastal and glacial morphology, remote sensing, and geophysical surveying. I aim to understand how coastal and glacial systems evolve on various timescales (days to years) using state-of-the-art geophysical instruments such as Unmanned Aircraft Systems, Ground Penetrating Radar, and Real Time Kinematic GPS. Much of my work relies on satellite remote sensing data and, as such, I am interested in assessing the uncertainty of these data and their derivative products using in situ field data.
Using drones to map nearshore bathymetry
Acquiring bathymetric data in the nearshore zone (0-10 mbsl) is notoriously difficult due to the substantial navigational hazards presented by shallow depths for ship-mounted surveys. We are developing a technique for mapping cm-scale bathymetry in these shallow zones by measuring changes in reflectance values of UAS-mounted multispectral imagery with depth. This work is being led by Timothy Clarke, MS student.
Are satellite-derived glacier flow velocities reliable?
Given the logistical difficulties of measuring glacier flow velocities in situ, we primarily rely on velocity estimates derived from image-pairs of optical and radar satellite imagery (i.e. Landsat/Sentinel-1). Although this technique has been proven to be effective in polar environments, little work has been done on assessing the uncertainty in temperate, alpine environments. By conducting GNSS field surveys of flow velocities on the Juneau Icefield (and using the Juneau Icefield Research Program's robust data archive), we provide evidence that satellite-derived velocities yield poor results in the accumulation and transient snowline zones with the opposite holding true in the ablation zone. (in review at Remote Sensing 2023).
Coastal monitoring in the 21st century (NASA)
This NASA-funded project focused on developing a novel automated shoreline mapping technique using new commercial satellite imagery (Planet) and machine learning (Google Earth Engine). The order-of-magnitude improvement in spatial resolution of Planet (3 m/pixel) over Landsat (30 m/pixel) enabled the mapping of a shoreline indicator (High Water Line) from a spaceborne platform, a feat previously unattainable. We compared the position of the Planet-derived shoreline with contemporaneous Mean High Water shoreline positions derived from cm-scale 3D surface models (UAS SfM) and show that the Planet shoreline is accurate to within 3 m of the in situ data when collected at low tide. (led by Suvam Patel, MS Graduate 2023 - AGU abstract here).
Is there a connection between climate change and shoreline dynamics along southeast Queensland?
The aim of this project was to to understand the relative influence that regional and global climate cycles, such as the El Niño-Southern Oscillation and Pacific Decadal Oscillation, have on shoreline change along southeast Queensland. We mapped over 9,000 km of tide-corrected shoreline positions in southeast Queensland across 21 years using Landsat and correlated shoreline change curves to climate index data. We found that shoreline dynamics (erosion/growth) are controlled by variability in the El Niño-Southern Oscillation during negative Interdecadal Pacific Oscillation (IPO) phases and by the Subtropical Ridge during positive IPO phases. Read more in our paper in Marine Geology.