Supervisor(s): Dr. Jadu Dash, Dr Thomas Lankester (Astrium Geo) and Prof. Peter Atkinson
Funding Restrictions: Fully funded for UK/EU students
The prediction, in space and time, of vegetation phenological variables such as: time of onset of âgreennessâ, time of end of âgreennessâ, duration of the growing season, rate of âgreen upâ and rate of senescence can provide the information needed to increase understanding of the effects of climate change on vegetation.Â Such phenological variables can be predicted from ground or remotely sensed data. Time series of remotely sensed vegetation index were used in last three decades to predict phenological variables. While a number of techniques have been developed to predict phenological variables from satellite sensor, no ideal technique has been developed yet. Despite an increase in effort towards characterization of vegetation phenology from satellite data there are relatively few studies that provide proper evaluation of the results. Inherent issues of satellite derived phenology such as pixel resolution, temporal resolution and atmospheric contamination even make it more challenging to relate these to ground measurements.
This project will evaluate the uncertainties in the satellite derived phenological variable due to sensor specific factors such as error in the biophysical variables, temporal resolutions and non-sensor variables such as different growth stage, atmospheric contamination and spatial heterogeneity. In addition, the project will also investigate how these uncertainties in phenological variables propagate to regional temporal trends. The applicant will have opportunity to work closely with Astrium Geo-information services and the phenology focus group within the CEOS LPV group (http://lpvs.gsfc.nasa.gov/pheno_background.html).
The proposed project lies within the Global Environmental Change and Earth Observation (GECEO) research group. GECEO is a group of six core academic staff, several further research staffs in the GeoData Institute, several post-doctoral researchers and fellows and 27 PhD students, working to quantify and understand global environmental changes using Earth observation data and its environmental and socio-economic impacts. The proposed research would be well supported by these staff capabilities, and by the broad research environment including the specific hardware and software required to undertake the research.
Candidates must have or expect to gain a first or strong upper second class degree, in Geography, Environmental Science, Computational science or a related subject. Experience of computer programming (IDL, Matlab, C etc.) and image processing is desirable but not essential as training can be provided. Details on how to apply are available from the Graduate School Administrator, School of Geography University of Southampton, SO17 1BJ, Telephone 023 8059 2216,Â email [email protected] . Informal enquiries may be made to Dr Jadu Dash (Telephone 023 8059 2203Â â email [email protected]). For the latest information on funding opportunities, please visit the Geography website at http://www.southampton.ac.uk/geography/postgraduate/research_degrees/studentships.page?
Apply online via: http://www.soton.ac.uk/postgraduate/pgstudy/howdoiapplypg.html
Closing date: 25th August 2013
Interviews: week commencing 2nd September 2013