One of my research topics is the use of image texture measures and pattern recognition algorithms for improved classification of remotely sensed imagery.
Geographic Object-Based Image Analysis
My research looks at the use of object-based image analysis to derive useful information from high-resolution satellite or airborne imagery.
3D point clouds
My research looks at comparing LiDAR point clouds with computer vision point clouds for characterisation of vegetation structure.
Unmanned Aircraft Systems (UAS)
My research focuses on the use of UAS for environmental and agricultural remote sensing. I specialise in the integration of multiple sensors (hyperspectral, thermal, LiDAR) on-board UAS and development of image processing workflows.
Hyperspectral image analysis
This image shows a hyperspectral image of an Antarctic moss bed acquired from an Unmanned Aircraft System (UAS).
Home page of Arko Lucieer
I am a Senior Lecturer in Remote Sensing and GIS in the Surveying and Spatial Sciences Group, School of Land and Food at the University of Tasmania, Australia. My research focus is on the use of Unmanned Aircraft Systems (UAS) for quantitative remote sensing and high precision aerial surveys for environmental and agricultural applications.
This video was acquired by a small quadcopter (DJI Vision+) during a TERNAusCover field campaign (2 – 6 Feb 2015) in the old growth forest of southern Tasmania. The footage is of the Warra flux tower, which towers at 80 m over a 50-60 m tall canopy of wet eucalyptus forest. The data was collected as part of an airborne hyperspectral campaign and field campaign to measure forest properties. See the following link this TERN media release for more information.
Darren Turner (PhD student in the TerraLuma group), Prof. Steven de Jong (Utrecht University), and I just published a new paper in the journal Remote Sensing. The study looks at the use of UAV structure-from-motion (SfM) and image correlation techniques to monitor landslide deformation.
Turner, D., Lucieer, A., and de Jong, S.M. (2015). Time series analysis of landslide dynamics using an unmanned aerial vehicle (UAV). Remote Sensing. 7(2): 1736 – 1757; doi:10.3390/rs70201736 | Download PDF
We developed a gimbal stabilisation system for the Headwall Photonics micro-Hyperspec. This brushless gimbal actively stabilises the pushbroom scanner to achieve smoother image acquisition. We also re-designed the CameraLink data recording system, and integrated the micro-Hyperspec with a dual frequency GPS unit, MEMS-based IMU, and machine vision camera (all sensors synchronised). The video below demonstrates the stabilisation of the gimbal. The wires need to be loose to reduce the resistance on the gimbal.
The original HyperUAS system is described in our publication here: Lucieer, A., Malenovsky, Z., Veness, T., Wallace, L. (2014). HyperUAS – Imaging spectroscopy from a multi-rotor unmanned aircraft system. Journal of Field Robotics, 31(4): 571-590. doi:10.1002/rob.21508 | Download PDF
The system shown in the video aims to overcome some of the limitations of the HyperUAS setup.
Late last year, we tested the Devourer D130, an X8 mega-quad with 28″ props. Very successful test with a 3 kg dummy payload, getting good flight times of 20+ minutes. This platform will be used for our heavier sensors, such as the micro-Hyperspec and LiDAR.