Detection of tangled lignum (Duma florulenta) from UAVs using imagery and machine learning - Final report

Aug 4, 2026

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Final version of a technical report on detecting tangled lignum (Duma florulenta) using UAV-derived imagery and machine learning, prepared for the Mallee Catchment Management Authority by the Centre for Applied Water Science, University of Canberra (submitted July 2023). The study sets project aims and objectives, describes the study area and on-ground field-survey data collection and analysis, and outlines remote-sensing workflows combining LiDAR imagery with machine-learning methods. Results, acknowledgments, and funding through The Living Murray program are included, with publication and liability notices.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages36

Reading Time1 h 31 min

AccessFree to download

Executive Summary

Introduction

Background

Target species-tangled lignum (Duma florulenta)

Remote sensing

Machine learning

LiDAR Imagery

Project aim and objectives

Study area

On ground field-survey method

Data collection

Data analysis

Results

Remote sensing methods (machine learning and LiDAR)

Image collection

Machine learning

Detection of tangled lignum (Duma florulenta) from UAVs using imagery and machine learning Report prepared for the Mallee Catchment Management Authority by the Centre for Applied Water Science, University of Canberra. Final version submitted July 2023. This document has been coordinated by Dr Will Higgisson and includes contribution by Ms Alica Tschierschke, Mr Marcello Blaxell, Ms Angela Lanspeary, Mr Adrian Cobb, Assoc. Prof. Duanne White and Prof. Fiona Dyer © University of Canberra With the exception of the Commonwealth Coat of Arms, the Murray-Darling Basin Authority logo, Victorian State logos, photographs and Mallee CMA logos and photographs, all material presented in this document is provided under a Creative Commons Attribution 4.0 International licence. ( [https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/) ) . For the avoidance of any doubt, this licence only applies to the material set out in this document. The details of the licence are available on the Creative Commons website (accessible using the links provided) as is the full legal code for the CC BY 4.0 licence ( [https://creativecommons.org/licenses/by/4.0/legalcode](https://creativecommons.org/licenses/by/4.0/legalcode) ) . MDBA’s preference is that this publication be attributed (and any material sourced from it) using the following: Publication title: Higgisson, W., Tschierschke, A., Blaxell, M., Lanspeary, A., Cobb, A., White, D., and Dyer, F., (2023) Detection of tangled lignum (Duma florulenta) from UAVs using imagery and machine learning. A report prepared for the Mallee Catchment Management Authority, Mildura, Vic. Source: Licensed from the University of Canberra under a Creative Commons Attribution 4.0 International Licence The contents of this publication do not purport to represent the position of the Commonwealth of Australia or the MDBA in any way and are presented for the purpose of informing and stimulating discussion for improved management of Basin's natural resources. To the extent permitted by law, the copyright holders (including its employees and consultants) exclude all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this report (in part or in whole) and any information or material contained in it. Acknowledgments: We would like to acknowledge Ibrahim Radwan, Jill Bartlett and Cherie Campbell for their contribution to this project. The project team respectfully acknowledge the traditional owners of the land on which this work was conducted, their Elders past and present, their Nations of the Murray-Darling Basin, and their cultural, social, environmental, spiritual and economic connection to their lands and waters. This report was funded by the Mallee Catchment Management Authority through The Living Murray program. The Living Murray is a joint initiative funded by the New South Wales, Victorian, South Australian and Commonwealth Governments, coordinated by the Murray-Darling Basin Authority. Cover photo: DJI Matrice 300 RTK LiDAR Drone landing in Hattah Lakes, Victoria, March 2023. Will Higgisson. Contents Abbreviations ...................................................................................................................................... 2 Table of figures ................................................................................................................................... 3 Table of tables..................................................................................................................................... 3 Executive Summary................................................................................................................................. 4 1. Introduction .............................................................................................................

FAQs

What species and data sources does the report focus on?

The report targets tangled lignum (Duma florulenta) and uses UAV-derived imagery, including LiDAR imagery, supported by on-ground field-survey data.

How is the project structured from field survey to remote sensing?

It defines project aim and objectives, describes the study area, then presents on-ground data collection and analysis, followed by remote sensing methods integrating machine learning with LiDAR.

Who prepared and funded the report?

The report was prepared by the Centre for Applied Water Science, University of Canberra, coordinated by Dr Will Higgisson, and funded by the Mallee Catchment Management Authority through The Living Murray program.

Aug 4, 2026

Upload by Skyler