CSIRO IPhD- Optimising solar farm usage utilising aerial images
The PhD will use historical and current ground-based data and observations to validate and train a machine learning model to obtain the same information from high resolution hyperspectral satellite images.
This project aims to leverage high resolution satellite images and artificial intelligence to enhance vegetation management and grazing efficiency in solar farms.
Key details
Reference number
20246658
For course
MRes Year 2 + PhD, PhD
Key dates
Applications close on 31 October 2024
Student type
Domestic
Area of study
Engineering
Stipend value
(Direct payment)
$47,000 p.a.
The potential benefits are enhanced solar operation and vegetation management efficiency, bush fire risk monitoring and solar grazing.
The main objectives are to:
- develop an algorithm using commercial satellite imagery to monitor and predict key factors including curing rates, vegetation growth, grazing patterns and effectiveness of land management.
- explore the use of free satellite imagery to achieve similar outcomes within an acceptable degree of accuracy and uncertainty.
- compare the algorithm with real-world data to improve vegetation management, optimise grazing patterns, prevent overgrazing, and automate the data required to determine the curing rating.
Availability
This scholarship is available to eligible candidates to undertake:
- a direct entry three-year PhD program, or
- a four-year MRes Year 2 + PhD program.
Components
The scholarships comprise:
- a tuition fee offset/scholarship
- a living allowance stipend.
- supervision by the participating university, CSIRO and an industry partner
- a project Expense and Development package of $13,000 per annum
- a three month industry engagement component with the industry partner
- a structured professional development and training program to develop your applied research skills.
The value of each stipend scholarship is $47,000 per annum (full-time, fixed rate) for four years.