Dr Angela Harris - Postgraduate opportunities
I welcome applications from prospective PhD students in any area of environmental remote sensing. I am happy to supervise both technical development, experiemental and applied projects using field spectroscopy, airborne imagery (including LiDAR) or satellite sensor data.
I would be particularly interested in supervising projects with a focus on linking remote sensing measurements with biophysical characteristics for the estimation of carbon fluxes and or ecosystem health and vitality. A list of some example projects are listed below:
- Spatio-temporal modelling of CO2 exchange in a Sphagnum-dominated peatland: A combined remote sensing and ecohydrological approach - This project provides an opportunity to study at the interface between remote sensing, ecology and physical geography. The research will involve both laboratory-based and field work components. The objectives will be: (1) to determine the nature of the relationship between Sphagnum productivity and spectral data under varying hydrological conditions; (2) to understand the influence of abiotic factors (i.e. temperature and illumination conditions) on the retrieval of productivity measures from Sphagnum mosses; and (3) to utilise multi-scale remote sensing data, to assess the scale-dependency of these models.
- Improving estimations of peatland carbon fluxes using a nested multi-scale sub-pixel classification approach - The aim of this project is to develop and implement a methodology for a nested multi-scale classification of boreal peatlands that can be used to (i) provide information on peatland type and structure across a range of spatial scales and (ii) effectively upscale estimations of carbon flux and plant physiological data from plots to the landscape and ultimately global scale.
- Moisture controls on peatland light use efficiency: Implications for remote sensing of peatland carbon balance - Climate induced changes in hydrology will have consequences for peatland carbon fluxes. Optical properties of mosses are indicative of peatland hydrology and productivity. This project will extend this work to other species and test a light use efficiency model under varying environmental conditions to evaluate the potential of remote sensing for spatially explicit peatland carbon flux estimation.