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PhD (Queensland University of Technology)
Dr. Alan Woodley is the leader of the Spatial Informatics Laboratory and a Vice Chancellor’s Research Fellow in Data Analytics for Digital Agriculture He has a joint appointment in the Institute for Future Environments (IFE) and the Science and Engineering Faculty (SEF).In the IFE he is also a domain leader of ‘Intelligence from Sensing’.
He has a background in data and computer science with a Bachelor of Information Technology and a Ph.D. from QUT. His research has focussed on applying efficient ‘big data’ solutions covering data analytics, computational modeling, and visualisation. His work has been applied to the mining and environmental domains and has developed research frameworks and tools to improve industrial sustainability and to bridge the social-technical divide. His current work focuses on using intellisensing technologies to better inform on-farm decision makig
Additional information
- Type
- Fellowships
- Reference year
- 2018
- Details
- Awarded a prestigious 3-year Vice Chancellor's Research Fellowship in Digitial Agriculture. The Fellowship will join together farm sensors, computational models, and visualizations. The Fellowship will explore how uncertainty is passed from sensors to models and how models can better deal with streaming data.
- Type
- Funding Award
- Reference year
- 2017
- Details
- Funding of $173K from the Bonneville Power Administration(a subsidiary of the US Department of Energy) for the project "Automated Fish Density Tool". The BPA supplied low emissions energy, mostly from hydroelectric power plants. The project will model, predict and visualize fish population in the North West United States. The project partners include the National Marine Mammal Lab of the National Oceanic and Atmospheric Association and the US Forest Service.
- Type
- Funding Award
- Reference year
- 2017
- Details
- Funding of $200K from the CRC for Spatial Information (Category 4: Australian Competitive Grant) for the project "Change Detection System from High-Resolution Satellite Images (CDS)". The project uses high resolution (
- Han Onn A, Woodley A, (2014) A discourse analysis on how the sustainability agenda is defined within the mining industry, Journal of Cleaner Production p116-127
- Danoucaras N, Woodley A, Moran C, (2014) The robustness of mine water accounting over a range of operating contexts and commodities, Journal of Cleaner Production p727-735
- Woodley A, Tang E, Geva S, Nayak R, Chappell T, (2016) Using parallel hierarchical clustering to address spatial big data challenges, Proceedings of the 2016 IEEE International Conference on Big Data (Big Data) p2692-2698
- McIntyre N, Woodley A, Danoucaras N, Coles N, (2015) Water management capacity building to support rapidly developing mining economies, Water Policy p1191-1208
- Paragreen N, Woodley A, (2013) Social licence to operate and the coal seam gas industry: What can be learnt from already established mining operations?, Rural Society p46-59
- Baxter P, Woodley A, Hamilton G, (2017) Modelling the spatial spread risk of plant pests and pathogens for strategic management decisions, Proceedings of the 22nd International Congress on Modelling and Simulation (MODSIM2017) p209-215
- Woodley A, Chappell T, Geva S, Nayak R, (2016) Efficient feature selection and nearest neighbour search for hyperspectral image classification, Proceedings of the 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA) p193-200
- Woodley A, Danoucaras N, (2014) A robust methodology for developing an operational systems view of mine water interactions, Proceedings of the 4th International Congress on Water Management in Mining p1-10
- Collins N, Woodley A, (2013) Social water assessment protocol: a step towards connecting mining, water and human rights, Impact Assessment and Project Appraisal p158-167
- Woodley A, Keir G, Roux E, Barrett D, White J, Vink S, (2014) Modelling the water, energy and economic nexus [Project C21033]
- A Novel Hybrid Method for Synthesizing Missing Pixels in Remote Sensing Imagery With High Accuracy
PhD, Principal Supervisor
Other supervisors: Associate Professor Shlomo Geva - Image Analytics and Classification Methods using High Resolution Remote Sensing Data for Improving Flood Mapping
PhD, Associate Supervisor
Other supervisors: Associate Professor Luis Mejias Alvarez, Dr Frederic Maire - Multimodal Big Data Fusion in Remote Sensing for Environmental Monitoring
PhD, Principal Supervisor
Other supervisors: Associate Professor Shlomo Geva, Dr Dimitri Perrin