The use of either satellite-based earth observation (EO) or simulation models of crops offers significant opportunities to refine decision support tools to the field and sub-field level. Such refinement offers advantages and savings for farmers by reducing the need for direct field measurements while enhancing the accuracy and resolution of decision-making. However, using EO data or simulation models by themselves is hampered by two challenges. First and regarding EO, saturation issues in metrics such as the Normalized Difference Vegetation Index (NDVI) make them difficult to directly convert to a crop performance metric (e.g., cover, leaf area, biomass, yield). Second, and regarding simulation models, their calibration procedure relies on ground data from direct crop measurements. A potential solution to overcome these challenges is to couple biophysical crop models with EO where the EO data informs the models, while the models fill gaps in data caused through both image saturation and interruption. This project will investigate and develop this solution for applications in the Australian Broadacre cropping industries.
Novel Biophysical Crop Model and Earth Observation Calibration Methods
To be eligible applicants must:
- Have completed a research-based postgraduate or honours qualification in a discipline related to the project (ie Agriculture or Environmental Science);
- Be native English speakers and/or meet UniSQ’s English Language Requirements for International applicants;
- Have applied, or currently enrolled in the at UniSQ;
- Not be receiving equivalent support providing a benefit greater than 75% of the student’s stipend rate;
- Be eligible to commence or continue a PhD Program in 2024.
To be eligible applicants must:
- Have a strong academic record and hold a qualification equivalent to an Australian research postgraduate or honours degree;
- Have completed study and/or research experience in agricultural or environmental science;
- Possess a good standing or potential to publish in high-quality journals in the related areas;
- Possess potential of working with agricultural and crop modelling;
- Be enthusiastic, self-driven, and highly motivated;
- Possess excellent verbal and written communication skills.
To apply, please ensure you have digital copies of the below information:
- One page cover letter outlining addressing the selection criteria,
- Curriculum vitae; encompassing any research presentations and/or publications,
- Education qualifications (testamur and academic transcripts for all undergraduate and postgraduate awards).
Application must be made via the m by the closing date.
If you require assistance in completing your application please download the Scholarship Online Application Manual (PDF 2.14MB).