PhD available for September 2018: Developing more robust soil moisture products from SAR imagery

Supervisors
Prof Keith Morison, Prof Anne Verhoef, Andrew Sowter (Geomatic Ventures Ltd)
Project Outline

The project has as its ultimate aim the development of a more robust soil moisture product from satellite radar. It sits within a work package of the prestigious 4-year NERC LANDWISE project recently awarded to the University of Reading. The project aims to identify and assess schemes for natural flood management within groundwater-fed lowland catchments. Increased infiltration into soil, evaporative losses, and below-ground water storage can all alleviate flood risk. A key parameter in the efficacy of these processes is soil moisture. Currently, soil moisture retrieval from radar imaging satellites uses the proposition that the backscatter returned from a soil is related to its dielectric properties. For a given soil type, changes in dielectric are controlled solely by moisture content variations. A backscatter amplitude value at an image pixel may then be inverted via scattering models to obtain surface moisture. However, this retrieval is complicated by the additional sensitivity of the backscatter to surface roughness, as well as overlying vegetation biomass. For the simplest cases of bare or lightly vegetated soils, extraction of accurate soil moisture information relies on an accurate model representation of the relative contributions of the moisture and roughness returns.

Because of the limitations of using amplitude, a new and potentially disruptive scheme for moisture estimation using both amplitude and phase is being pioneered at Reading. Phase provides extra insights into the radar-soil interaction, and early results suggest it may additionally be much less sensitive to the confusion associated with the amplitude signal. The study will involve experimental work, data analysis and interpretation, and modelling. A bespoke, portable, C-band imaging radar system will be built to carry out measurements at sites utilized by the LANDWISE project. The imaging will use the tomographic profiling scheme to provide very-high resolution images of the vertical amplitude and phase scattering patterns through a soil column, and their responses to varying moisture states. This will, uniquely, allow us to see how and where the signals arise from within a soil, which we normally see collapsed and overlain in SAR imagery, and hence indistinguishable. We will be able to immediately and unambiguously answer questions researchers otherwise seek to retrieve by model inversion and intelligent supposition.

The field data will be used to validate and develop an existing coherent radar ray tracing model of soil-moisture backscatter. The ground measurements will be synchronized to the time of over-passes by the C-band Sentinel satellites. We can then compare the amplitude and phase behaviours observed at the Sentinel satellites to the ground and modelling results to understand how moisture changes are perceived by satellite radar. This information will give us the insight into how the moisture signal is encoded in the satellite measurement, to best understand how it can be extracted to provide a more robust moisture product.

Training
Soil moisture studies are part of on-going collaborations with the Technical University of Vienna, Swiss Federal Institute of Technology in Zurich, and German Aerospace Centre. The student can be expected to be involved in visits and placements at these institutes over the course of the studentship.

In addition, Prof. Morrison has an on-going research study into the behaviour of radar backscatter to soil moisture using the recently built indoor GB-SAR radar laboratory. The student will have access to this state-of-the-art facility, and gain valuable experimental skills in precision microwave measurement.

To read more about the project here.

Funding Notes

The project is part of the SCENARIO Doctoral Training Partnership and is potentially fully-funded, subject to selection based on candidate excellence. Funding is available for UK or EU students. Funding is not available for international students. The project has matched funding.

To apply, please refer to the SCENARIO website.  Closing date for applications is 29 January 2018.

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