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2026

Conference Publication

Mapping vegetation functional states across climate extremes: spectral deep learning from drylands to Antarctic cryptogam ecosystems

Sotomayor, Laura N., Lucieer, Arko, Turner, Darren, Haynes, Ryan, Cimoli, Emiliano, Youssef, Mathew, Galvez-Serna, Julian, Fedrigo, Melissa, Kattenborn, Teja and Barthélemy, Johan (2026). Mapping vegetation functional states across climate extremes: spectral deep learning from drylands to Antarctic cryptogam ecosystems. 12th SCAR Open Science Conference, Oslo, Norway, 10 - 14 August 2026. doi: 10.5281/zenodo.23518885

Mapping vegetation functional states across climate extremes: spectral deep learning from drylands to Antarctic cryptogam ecosystems

2025

Conference Publication

Sensor-agnostic 3D structure mapping pipeline: from UAS-derived 2D orthophotos and LiDAR point clouds to volumetric training data for 3D U-Net modelling

Sotomayor, Laura N., Lucieer, Arko, Turner, Darren, Lewis, Megan, Shaun, Levick and Kattenborn, Teja (2025). Sensor-agnostic 3D structure mapping pipeline: from UAS-derived 2D orthophotos and LiDAR point clouds to volumetric training data for 3D U-Net modelling. IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2025), Brisbane, Australia, 3-8 August 2025. doi: 10.5281/zenodo.23946673

Sensor-agnostic 3D structure mapping pipeline: from UAS-derived 2D orthophotos and LiDAR point clouds to volumetric training data for 3D U-Net modelling

2025

Conference Publication

Deep learning for identification of 3D plant growth forms in Fractional Vegetation Cover

Sotomayor, Laura N., Turner, Darren, Megan, Lewis, Levick, Shaun and Kattenborn, Teja (2025). Deep learning for identification of 3D plant growth forms in Fractional Vegetation Cover. European Geosciences Union General Assembly 2025 (EGU25), Vienna, Austria, 27 April-2 May 2025. doi: 10.5194/egusphere-egu25-3984

Deep learning for identification of 3D plant growth forms in Fractional Vegetation Cover

2024

Conference Publication

Investigating Deep Learning Techniques to Estimate Fractional Vegetation Cover in the Australian Semi-arid Ecosystems combining Drone-based RGB imagery, multispectral Imagery and LiDAR data

Sotomayor, Laura N., Kattenborn, Teja, Darren, Turner, Lewis, Megan and Lucieer, Arko (2024). Investigating Deep Learning Techniques to Estimate Fractional Vegetation Cover in the Australian Semi-arid Ecosystems combining Drone-based RGB imagery, multispectral Imagery and LiDAR data. European Geosciences Union General Assembly 2024 (EGU24), Vienna, Austria, 14-19 April 2024. doi: 10.5194/egusphere-egu24-5766

Investigating Deep Learning Techniques to Estimate Fractional Vegetation Cover in the Australian Semi-arid Ecosystems combining Drone-based RGB imagery, multispectral Imagery and LiDAR data