Research Fellow in Remote Sensing of Vegetation
School of Geography & Environmental Science
Location: Highfield Campus
Salary: £32,348 to £39,745 per annum
Full Time Fixed Term until 03/02/2025
Closing Date: Wednesday 28 December 2022
Interview Date: To be confirmed
A research fellow with experience in remote sensing of vegetation is required to support and lead research activities in a number of externally funded projects funded through European commission and European Space Agency (https://frm4veg.org/; https://gbov.acri.fr/). Key research activities will focus on developing novel techniques to derive vegetation biophysical variables such as Leaf Area Index, Fraction of Absorbed Photosynthetic Active Radiation and Canopy Chlorophyll Content from current and upcoming satellite sensors and undertake research on validation of these variables.
You will join the School of Geography and Environmental Science at the University of Southampton and work closely with members of Southampton Geospatial. We work with nations and agencies globally across disciplines to develop new geospatial tools and dataset to solve environmental and socioeconomic challenges. You will have access to state-of-the art spectroscopy laboratory and high performance computing facility to undertake your research.
The specific work to be undertaken involves:
- Development of a harmonised and gap filled global dataset of Canopy Chlorophyll content (CCC) and the fraction of absorbed photosynthetically active radiation (FAPAR)
- Development of protocols and procedures to process and utilize existing ground data for validation of global vegetation products
- Undertaking field campaign to collect fiducial reference measurements for validation.
- Development of new methods to demonstrate application of global vegetation products in areas such as food security and carbon cycle.
You will have a strong remote sensing and image analysis skills with experience in the development and validation of biophysical variables from satellite data, previous experience satellite derived vegetation products and time series analysis are essential for the role. You would expect to have a good knowledge of programming and experience of using cloud-based data processing infrastructure and/or high-performance computing.
The post is tenable from 1st February 2023
Informal enquiries may be made to Professor Jadu Dash J.Dash@soton.ac.uk.
You should submit your completed online application form at https://jobs.soton.ac.uk. The application deadline will be midnight on the closing date stated above. If you need any assistance, please call Lauren Ward (Recruitment Team) on +44 (0) 23 8059 2750, or email firstname.lastname@example.org. Please quote reference 2084222WR on all correspondence.