John Beal

Name: John Beal

Project title: Towards field-scale soil moisture measurement using SAR remote sensing and the COSMOS-UK network

Where based: Cranfield University and CEH(Wallingford)


I have arrived at soil science by a very odd route – I began my career as an experimental physicist in a defence laboratory. But this is where I was first exposed to remote sensing, using thermal imaging and passive millimetre waves, and have been fascinated by satellite imagery, aerial photography and map making ever since. The opportunity to study for an MSc in Geographical Information Management at Cranfield was a great vehicle to indulge my interests and test the water for a return to academic life. Through the team at Cranfield and my thesis project on cauliflowers, I became interested in precision agriculture and soils. However, I then spent several years as an innovation consultant specialising in engineering and transport (railways, industrial heritage and sailing are other hobbies of mine). The STARS CDT project is a great opportunity for me to get stuck in to a challenge that plays to my interests.

Project description:

Knowledge of soil moisture is an important import into climate, meteorological and hydrological models and has important applications in agriculture, management of natural resources and predicting and preventing flooding. Field-scale measurements are potentially possible, despite many challenges, through Synthetic Aperture Radar (SAR) from satellite. The CEH’s COsmic-ray Soil Moisture Observing System (COSMOS-UK network) can match the SAR spatial and temporal scales to validate, calibrate or compliment the SAR product with ground data. I will be investigating the capabilities and synergies of SAR and COSMOS, exploiting novel, statistical models based on change point detection and other techniques. I will be trying to overcome the problems associated with vegetation cover and soil texture that limit the ability of SAR to reliably measure soil moisture, and to understand the relationship between a surface measurement and one at greater depth, and whether that is a limiting factor to the usefulness of the data.