This project will test the capability of satellite Earth observation (EO) to detect, map and quantify glacial suspended marine sediments from marine terminating glaciers in the Southern Ocean.
Background
The Southern Ocean is characterized by high nutrient low chlorophyll waters. The main limiting factor in primary production is the supply of Fe and other trace minerals. This expanse of low productivity is punctuated by a number of Sub Antarctic Islands, which host highly productive marine ecosystems. South Georgia is the most notable of these, sustaining major populations of seabirds and marine mammals as well as one third of the global krill catch and significant fishing industries. The driving mechanism behind this productivity is, as yet, unclear. Current biogeochemical models cannot replicate the amount or seasonality of Chlorophyll blooms around the island, but there is a growing realization that in polar seas, glacial meltwater provides an important, but as yet un-quantified contribution of Fe. This is highly likely in South Georgia where the combination of fast, warm-based, marine terminating glaciers and high rates of precipitation provide a significant sediment contribution.
Aim and research questions
South Georgia’s glaciers are in rapid retreat, and the few existing studies show that the rate of glacial change is accelerating. Less glacial ice means less erosion and less sediment delivered to the ocean. This will have a detrimental effect on the surrounding ecosystems, but the amount and distribution of glacial sediments is at present unquantified. Initial investigations from satellite remote sensing have shown that glacial sediments, especially fine particulate glacial flour, can be identified and possibly mapped in imagery. This project has four objectives four objectives:
- Testing and build an algorithm using computer-vision and image processing techniques to identify glacial flour in the surface water column in a range of satellite imagery.
- Developing a pipeline to map these sediments both locally around South Georgia and on a wider scale across the Southern Ocean to provide ongoing monitoring and baseline seasonal products to assess future change.
- Test the capability of remote sensing to phase speciate labile suspended iron fractions from remote sensing imagery.
- Using spectral properties of existing and newly acquired sediment samples for ground truthing, test the ability to quantify the suspended sediment load using satellite imagery.
Methodology and timetable
To address these objectives, the project will: O1) Utilizing a variety of optical remote sensing platforms (including VIIRS/SENTINEL3/SENTINEL2), test the ability of a variety of computer vision and machine learning applications (SAM/unsupervised classifications/ Random Forests/CNNs) to identify and discriminate suspended glacial flour. O2) Using online EO exploitation platforms such as Google Earth Engine, scale the results to map over large areas. O3) Using spectral profile from multispectral or future hyperspectral satellites, test the possibility to speciate labile suspended iron fractions. O4) Use Government of South Georgia water samples to calibrate the remote sensing results to quantity the volume of sediment in the ocean.
Training provision and required skills
You will be supervised by a team of leading remote sensors and glaciologists, gaining expertise in advanced techniques in remote sensing, data manipulation and modelling while being an integral part of the world class institutions of British Antarctic Survey and Edinburgh University. We seek an enthusiastic candidate equipped with advanced quantitative skills and a suitable degree including physics, mathematics, computer science, engineering, earth sciences or physical geography.
This PhD is part of the NERC and UK Space Agency funded Centre for Doctoral Training "SENSE": the Centre for Satellite Data in Environmental Science. SENSE will train 50 PhD students to tackle cross-disciplinary environmental problems by applying the latest data science techniques to satellite data. All our students will receive extensive training on satellite data and AI/Machine Learning, as well as attending a field course on drones, and residential courses hosted by the Satellite Applications Catapult (Harwell), and ESA (Rome). All students will experience extensive training on professional skills, including spending 3 months on an industry placement. See http://www.eo-cdt.org.