Minimize PhD opportunity on remote sensing data assimilation into agronomic models to support precision fertilisation in arable crops

Date added: 31 July 2017

Organisation: Department of Agriculture and Forestry, University of Tuscia

Location: Viterbo, Central Italy

The 3 years PhD position is fully funded by the European Space Agency (ESA) and the University of Tuscia, within the European-Chinese scientific cooperation programme Dragon 4. The PhD candidate will join a multidisciplinary team of European and Chinese researchers involved in the project ESA-MOST Dragon 4 "Combined exploitation of Sino-EU earth observation data for supporting the monitoring and management of agricultural resources" and specifically sub-project ADEMS Algorithm development exploiting multitemporal and multisensor satellite data for improving crop classification, biophysical and agronomic variables retrieval and yield prediction.

The goal of the specifc research that will be carried out by the candidate is the development and improvement of algorithms exploiting multi-temporal and multi-sensor satellite data assimilation into crop models, especially targeting nitrogen-related variable, in support of precision agriculture applications. An unprecedented frequency of high spatial resolution data can be obtained by combining European and Chinese satellite acquisitions. This calls for the development of specific data assimilation approaches addressing the issue of the multi-scale and multivariate nature of these data.

There are several methodological problems, e.g. the assessment of errors and uncertainties in the remote sensing observations, in crop models and parameters. The project will address these aspects thanks to a truly multidisciplinary team with competences ranging from optical to radar remote sensing, crop modeling and agronomy.


  • Master of Science or equivalent degree in geosciences, environmental sciences, geography, agricultural sciences or in a related discipline, with a preferably previous exposure to quantitative remote sensing and crop modelling.


  • interest in the use of satellite remote sensing data
  • interest and motivation to learn something on agronomic modelling
  • interest and motivation to travel in Europe and China and to spend some periods (at least 3 months overall) in China
  • good coding capacity preferably in Matlab and/or Python and/or IDL
  • fluency in spoken and written English, preferably willingness to learn some Italian
  • adaptation capability, flexibility.

For more information and formal application instructions please get in touch as soon as possible with Prof Raffaele Casa ( by sending a CV and a motivation letter. Application deadline 15th September 2017.

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