Mathematics and Data Science
Adam Stone
- Associate Lecturer, Data Science
- adam.stone1@jcu.edu.au
Yang Zhang
- Lecturer, Mathematics
- yang.zhang9@jcu.edu.au
Sophie Raynor
- Lecturer, Mathematics
- sophie.raynor@jcu.edu.au
Shaun Belward
- Associate Professor
- shaun.belward@jcu.edu.au
Patrick Higgins
- Senior Lecturer
- patrick.higgins@jcu.edu.au
Carla Ewels
- Senior Lecturer, Data Science and Statistics
- carla.ewels@jcu.edu.au
Yvette Everingham
- Professor, Promotional Chair
- yvette.everingham@jcu.edu.au
Dianna Hardy
- Casual Academic
- dianna.hardy@jcu.edu.au
Foundational Development of Drone-Based AI for Early Weed Detection in Tropical Reforestation
Reforestation in tropical regions faces a major ecological and operational challenge: the rapid proliferation of aggressive weed species during the early growth stages of trees. These weeds often outcompete young seedlings for critical resources such as light, nutrients, and water, leading to high mortality rates and undermining the success of environmental restoration, carbon sequestration, and biodiversity initiatives. Current weed monitoring methods are manual, labor-intensive, and impractical for large-scale or remote reforestation projects. This project proposes to address this challenge by developing an AI-powered aerial monitoring system that uses drones to detect and map weed infestations in tropical reforestation zones. Year 1 will focus on establishing the technical foundation for this system, including sensor configuration, data collection protocols, dataset creation, and initial model development.
CLOVER – Climate-smart Optimisation for Valuable & Efficient iRrigation
CLOVER – Climate-smart Optimisation for Valuable & Efficient irrigation – will help farmers use water more wisely by combining reliable weather forecasts, crop growth information, and smart irrigation systems into one easy-to-use tool. The project will build and test this digital system on working farms and provide training to farmers and advisers so they can make confident decisions about when and how much to irrigate. By reducing wasted water, energy, and labour, CLOVER will increase farm profits and resilience during dry times. The project will also create a community of practice where farmers, researchers, and industry partners share knowledge and learn from each other. Together, these activities will support the Grant’s goals of improving drought preparedness, building capacity in regional communities, and demonstrating innovative technologies that strengthen climate resilience across Australian agriculture.
Demonstrated physically at Salvetti Farming in the Atherton Tablelands and virtually through digital twins in Mackay, Bundaberg, and across other cropping systems, C.L.O.V.E.R connects technology, climate intelligence, and community knowledge. Through the AI-Climate Smart Irrigators Community of Practice, it builds capacity, fosters collaboration, and delivers enduring economic, environmental, and social benefits for Australian agriculture.
How big will that crop be? Incorporating climate forecasting into Nitrogen management in the Wet Tropics (Old ID 22499)
Due to the close proximity of sugarcane to environmentally sensitive areas in the Wet Tropics, it is important to improve nitrogen management practices to reduce nitrogen losses. The Wet Tropics experiences one of the highest levels of climate variability in the world, which affects the yield potential of sugarcane. This makes the task of applying the right amount of nitrogen, at the right time extremely formidable. Forecasted climatic conditions, then adjusting yield potential estimates have not been used to calculate nitrogen inputs for sugarcane.
Unravelling the impact of climate and harvest time on nitrogen fertiliser requirements (Old ID 23516)
This project aims to understand how climate and harvest time impacts nitrogen use efficiency on the sugarcane farming system in the Herbert.
Developing targeted, seamless weather/climate forecasting systems for critical early season harvest periods (Old ID 21105)
The overall achievement of this research will be the attainment of a new weather/climate forecast system/product targeted and specifically focussed for the Australian sugar industry needs - especially the important harvest periods and which will provide substantial and measurable improvement over currently available systems.
Optimising productivity, variety recommendations and mill operations through analysis of mill data (Old ID 23098)
Since 20009 sugarcane productivity has fluctuated dramatically across most mill areas. Although some of this regional variation can be explained by extreme weather events or disease incursions it is important to identify those causes which can be controlled in order to increase production/profitability for industry. Hugh amounts of data are captured annually by each mill and this significant investment is under-utilised in decision making. This project will develop innovative tools to analyse and summarise mill data with the view to optimize production/profitability.
Big Data for Sustainable Tropical Agriculture and Aquaculture (Old ID 22865)
Agri- and Aqua-cultural industries in Australia and around the world are lagging behind their business counterparts when it comes to creating efficiencies and increasing profitability using Big Data technologies. Big Data refers to the volume, variety and velocity that data can be collected. Barriers imposed by geography, social fabric and technological limitations such as poor mobile phone coverage and inadequate links to modern day storage devices such as the cloud has impeded the adoption of Big Data technologies in northern Australia. This project will explore how Big Data and other digital technologies can enhance the sustainability of Agricultural and Aquaculture systems in the Tropics.
Innovative economic levers: A system for underwriting risk of practice change in cane-farming (Old ID 23138)
This project will enable reduced DIN exports from cane lands by developing and promoting a tested framework for commercial insurance businesses to underwrite risk of nitrogen practice change in sugarcane farming.
The Queensland STEM Education Network (Old ID 22162)
Establish the Queensland STEM Education Network comprising a partnership of key stakeholders in STEM education in Queensland to co-develop a range of programs and initiatives designed to build STEM capacity across the state of Queensland.
Improving water quality for the Great Barrier Reef and wetlands by better managing irrigation in the sugarcane farming system (Old ID 23136)
This project will work in partnership with industry, extension, NRM, research and government organisations to develop and deploy an irrigation system that is automatically controlled by remotely accessing feedback from the IrrigWeb decision support tool. Irrigweb provides optimal irrigation schedules on a paddock-by-paddock basis by linking information abut climate, soils and management regimes. If new water quality targets as specified in the revised Burdekin Water Quality Improvement Plan are to by met by 2025, it will be critical to establish pathways that enable industry partners to capitalise on new technologies.
Yield forecasting for marketers
- 2005
- Australian Society of Sugar Cane Technologists
- Researchers:Yvette Everingham
An exploratory investigation of the relationship between decadal rainfall and climate indices
- 2005
- Australian Society of Sugar Cane Technologists
- Researchers:Jasmine JaffresYvette Everingham
Sugarcane
- 2010
- CSIRO Publishing
- Researchers:Yvette Everingham
RAIN FORECASTER - a seasonal climate forecasting tool
- 2009
- Australian Society of Sugar Cane Technologists
- Researchers:Yvette Everingham
To screencast or not to screencast
- 2010
- Cambridge University Press
- Researchers:Patrick HigginsShaun BelwardLindsay Ward
Start Date:
01 Jan 2020
Start Date:
01 Jan 2015
Start Date:
01 Jan 2011
Start Date:
01 Jan 2010
End Date:
01 Jan 2022
Start Date:
01 Jan 2014
Start Date:
01 Jan 2025
End Date:
01 Jan 2027
Start Date:
01 Jan 2024
End Date:
01 Jan 2025
Start Date:
01 Jan 2014
Start Date:
01 Jan 2008
Start Date:
01 Jan 2018
End Date:
01 Jan 2019