Lead researchers: Dr Christine Stone and Dr Jim O'Hehir

This project is comprised of several sub-projects which are actively involved in developing solutions for applications using a range or sensors and platforms in different situations across Australia. The project is benefitting from a high level of collaboration between industry and researchers to make multiple data sets available with knowledge sharing on solutions. 

To ensure effective communication with stakeholders, 14 seminars have been delivered across of a range of topics directly and indirectly covered by the project. 

Sub project: Growth and Yield Modelling for the Future (UniSA) 

This sub project has incorporated ground truth data into plot imputation models and shown potential to increase the efficiency, and lower the costs, of ALS surveys by reusing calibration plot data both spatially and temporally. Of importance to the industry is that preliminary results of imputation domain studies have indicated there is potential to increase the imputation accuracy and efficiency, and lower the costs, of ALS surveys by reusing calibration plot data both spatially and temporally. 

Root mean square error

Coefficient of Determination

Sub-project: Ultra high-resolution imaging from Unmanned Aerial Systems (UAS) for detection of weeds and tree health assessment (UTas) 

Data has been collected at three pine plantation sites in Northern Tasmania using a range of sensors: hyperspectral; multispectral, visible and thermal, with the aim of testing which sensors are best at detecting weeds. Data processing is now complete.

weed mapping 1 

 

Weed mapping 2

Subproject: The automation of forest inventory (University of Sydney)

The sub project is complete and has developed workflows and algorithms for tree-level census using point clouds, deep learning and human-machine interaction. The research indicates tree detection methods developed for high resolution Airborne Laser Scanning (ALS) data based on deep learning object detection have been applied effectively to low resolution ALS data. The implication for forest companies is that using this method, cheaper data can be used to obtain more tree attribute information. A report and software have been provided and the results have been communicated in a seminar.

Forest inventory

Results from all three of the above sub-projects have been communicated via individual seminars.

A short video of UAV work in the field at Tumut, NSW can be viewed here. 

Our team: Anthony Finn, Jim O'Hehir, Stefan Peters, Pankaj Kumar, Jiuyong Li, Jixue Liu, Liang Zhao, Christine Stone (NSW DPI) , Arko Lucieer (University of Tasmania), Paul Turner (University of Tasmania), Darren Turner (University of Tasmania), Mohammed Sadegh Taskhiri (University of Tasmania), Sean Krisanski (University of Tasmania), Mitch Bryson (University of Sydney), Lloyd Windrum (University of Sydney), Michael Watt (Scion, NZ), Susana Gonzalez (Interpine), Jan Rombouts (OneFortyOne), Hans Blom (FPC, WA), Irfan Iqbal (FPC, WA)

 

Contact information

Dr Jim O’Hehir
General Manager: Forest Research Mount Gambier
Ph: +61 8 830 28997
E: Jim.O'Hehir@unisa.edu.au

Michele Cranage
Administrative Officer
Ph: +61 8 830 28902
E: Michele.Cranage@unisa.edu.au