Leveraging Open-Source Tools to Analyse Ground-Based Forest LiDAR Data in South Australian Forests

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This paper investigates the application of open-source software and methods for forest LiDAR analysis, with a focus on enhancing forest inventory metrics in the radiata pine forests of South Australia’s Green Triangle region. A semi-systematic survey identified 22 relevant open-source tools, evaluated for their capabilities in inventory metric extraction and practicality for implementation in industrial workflows. Ground truth data from radiata pine forests across multiple development stages provided the basis for validating the tools’ precision, accuracy, and practicality. Results showed that stratified tool selection, optimized for each forest development stage, achieved high accuracy for inventory, achieving stem detection rates up to 99.1% and errors as low as 0.94 m for height and 1.18 cm for diameter at breast height (DBH) in specific cases. Additionally, we provide scripts to support future research, discuss the limitations of our approach, and propose solutions to address these gaps in future implementations. Our findings highlight the utility of open-source tools to optimize forest inventory workflows through stratified, modular approaches.