The project, led by Charles Sturt University (CSU) through the Graham Centre for Agricultural Innovation, aims to better use the technologies to rapidly detect weeds in mixed landscapes, such as native grasslands and woodlands, coastal dunes, alpine areas, and other diverse natural systems.

The aim is to help land managers to effectively target control to prevent weed spread, and reduce herbicide use.

CSU school of agriculture, environmental and veterinary sciences livestock production management lecturer, Jane Kelly said remote sensing technology was already used in a number of agricultural and environmental contexts but challenges remain.

"Complex natural systems make it difficult to distinguish weeds from other vegetation, especially during early stages of weed growth," Dr Kelly said.

"Remote detection techniques can also be expensive, technically-challenging and inaccessible for many land managers."

Dr Kelly said the two-year project would test the limitations of available remote sensing technologies, including airborne and satellite platforms and high resolution RGB (red, green, blue), hyperspectral and multispectral sensors, in combination with machine learning, to detect weeds.

"The project will use three nationally significant 'model' weed systems, including hawkweeds, African lovegrass and bitou bush to investigate the limitations of this technology," she said.

"They've been selected on the basis of the differing growth habit, colour and texture of the weeds, and for the variety of invaded landscapes and weed management objectives."

Study sites would be located within Kosciuszko National Park, the Monaro and the north, central and south coasts.

Dr Kelly said the project also aimed to provide robust guidelines for using remote sensing in weed detection across a variety of landscapes.

"The intent is to build an online portal and a community of practice to share tools and knowledge between researchers, governments, natural resource management groups and a range of end users," Dr Kelly said.

This project is supported by CSU through funding from the Australian government Established Pest Animals and Weeds Management Pipeline program - advancing pest animal and weed control solutions.

It brings together drone, machine learning and remote sensing researchers CSU Associate Professor Lihong Zheng and Dr Remy Dehaan, Queensland University of Technology, Associate Professor Felipe Gonzalez and weed management experts from the NSW Government.

Other partners include South East, North Coast and Murray Local Land Services, MidCoast, Eurobodalla and Bega Valley councils, the Illawarra District Weeds Authority, and XAg Australia.

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