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Up-scaling fuel hazard metrics derived from terrestrial laser scanning using a machine learning model. Remote Sensing 15, 1273 (2023).
Fuels3D - final project report. (Bushfire and Natural Hazards CRC, 2022).
An early exploration of the use of the Microsoft Azure Kinect for estimation of urban tree Diameter at Breast Height. Remote Sensing Letters 11, 963-972 (2020).
Quantifying fuel hazard assessments - Fuels3D annual report 2018-2019. (Bushfire and Natural Hazards CRC, 2020).
Quantifying fuel hazard assessments - Fuels3D annual report 2019-2020. (Bushfire and Natural Hazards CRC, 2020).
Assessing the ability of image based point clouds captured from a UAV to measure the terrain in the presence of canopy cover. forests 10, (2019).
Fuels3D: barking up the wrong tree and beyond. AFAC19 powered by INTERSCHUTZ - Bushfire and Natural Hazards CRC Research Forum (Australian Institute for Disaster Resilience, 2019). at <https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/>
A Method for Validating the Structural Completeness of Understory Vegetation Models Captured with 3D Remote Sensing. Remote Sensing 11, (2019).
Methods for background temperature estimation in the context of active fire detection. Department of Natural Resources Philosophy, (2019).
Advances in active fire detection using a multi-temporal method for next-generation geostationary satellite data. International Journal of Digital Earth (2018). doi:https://doi.org/10.1080/17538947.2018.1497099
Estimating fire background temperature at a geostationary scale - an evaluation of contextual methods for AHI-8. Remote Sensing 10, (2018).
Estimating Fire Background Temperature at a Geostationary Scale—An Evaluation of Contextual Methods for AHI-8. Remote Sensing 10, (2018).
A Broad-Area Method for the Diurnal Characterisation of Upwelling Medium Wave Infrared Radiation. Remote Sensing 9, (2017).
Enhanced estimation of background temperature for fire detection using new geostationary sensors. AFAC17 (Bushfire and Natural Hazards CRC, 2017).
Mapping the efficacy of an Australian fuel reduction burn using Fuels3D point clouds. AFAC17 (Bushfire and Natural Hazards CRC, 2017).
Non-destructive estimation of above-ground surface and near-surface biomass using 3D terrestrial remote sensing techniques. Methods in Ecology and Evolution 8, (2017).