Doctor of Philosophy (Queensland University of Technology)
Ecology and Environmental Science: The smart use of leading edge technology for efficient and accurate wildlife monitoring
Research area: Conservation using drones, artificial intelligence and advanced analytics Developing detection and aerial survey of animals of conservation concern using drones, detection of weeds, pests and invasives. Projects include: Automated detection of koalas in complex environments - we have developed a leading edge methodology for the detection and abundance estimation of koalas. Automated detection of feral species, including deer Automated detection of weeds Improving surveillance design for wildlife and pests
Areas of expertise:
- Koala detection
- Detection and abundance estimation using drones and AI
- Biological Invasions
- Ecological Statistics
- Ecological modelling.
- 2022: Discovery Project: Averting Disaster: New Ways to Assess Bushfire Risk and Building Integrity
- 2021: Landcare Led Bushfire Recovery:Establishing an AI Enabled Drone Monitoring Network for Wildlife
- 2020: Analysis of post bushfire koala populations on Kangaroo Island. Department for Environment and Water, South Austrlia
- 2018-2019. Landscape level abundance estimation and vegetation assessment- koalas. Gympie Regional Council
- 2019-2021. Deer detection with AI. Department of Environment and Science, Queensland
- 2017-2018. Horizon scan for new technologies/ industries. AgriFutures Australia.
- 2017-2019. Developing an Accurate and Cost Effective Koala Abundance Estimation Methodology Using UAVs. Department of Environment and Science, Queensland
- Detecting opportunities and challenges for Australian agricultural and Rural Industries. AgriFutures Australia.
- 2014-2018. Decision Making for eradiaction and quarantine zones. Plant Biosecurity CRC
- 2014-2017. Optimizing surveillance protocols using UAVs. Plant Biosecurity CRC
- Agri-intelligence in Cotton Production Systems
- Assessing the capabilities of digital imaging and Unmanned Aerial Systems (UAE) for species management: Koala Abundance
- Does habitat reflectivity influence the detection of bat echolocation by moths?
- Evaluation of infrared thermography for detection of animal species
- Fishing pressure and abundance in humphead wrasse and bumphead parrotfish
- Predicting Opportunities for Australian Agriculture
- Corcoran E, Denman S, Hanger J, Wilson B, Hamilton G, (2019) Automated detection of koalas using low-level aerial surveillance and machine learning, Scientific Reports, 9 (1), pp. 1-9.
- Pearse A, Hamilton R, Choat J, Pita J, Almany G, Peterson N, Hamilton G, Peterson E, (2018) Giant coral reef fishes display markedly different susceptibility to night spearfishing, Ecology and Evolution, 8 (20), pp. 10247-10256.
- Excoffier L, Hamilton G, (2003) Comment On Genetic Structure Of Human Populations, Science, 300 (5627), pp. 1877.
- Hamilton G, Stoneking M, Excoffier L, (2005) Molecular analysis reveals tighter social regulation of immigration in patrilocal populations than in matrilocal populations, Proceedings of the National Academy of Sciences of the United States of America, 102 (21), pp. 7476-7480.
- Baxter P, Hamilton G, (2018) Learning to fly: integrating spatial ecology with unmanned aerial vehicle surveys, Ecosphere, 9 (4), pp. 1-17.
- Johnson S, Abal E, Ahern K, Hamilton G, (2014) From science to management: Using Bayesian networks to learn about Lyngbya, Statistical Science, 29 (1), pp. 36-41.
- Elmouttie D, Flinn P, Kiermeier A, Subramanyam B, Hagstrum D, Hamilton G, (2013) Sampling stored-product insect pests: a comparison of four statistical sampling models for probability of pest detection, Pest Management Science, 69 (9), pp. 1073-1079.
- Elmouttie D, Kiermeier A, Hamilton G, (2010) Improving detection probabilities for pests in stored grain, Pest Management Science, 66 (12), pp. 1280-1286.
- Hamilton G, McVinish R, Mengersen K, (2009) Bayesian model averaging for harmful algal bloom prediction, Ecological Applications, 19 (7), pp. 1805-1814.
- Rasmussen R, Hamilton G, (2012) An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata, Environmental Modelling and Software, 29 (1), pp. 1-10.
- Agri-Intelligence in Cotton Production Systems - Stage 1
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- Start year
- Agriculture Cybernetics; Digital Agriculture; In-Farm Decision Support Systems; Management of Inputs in Agriculture; Value Chain of Cotton Crops
- Utility of an Existing Biotic Score Method in Assessing the Stream Health In Bhutan (2016)
- Hierarchical Bayesian Models for Estimating the Extent of Plant Pest Invasions. (2011)
- Market Access of Papua New Guinea Bananas (Musa Spp.) with Particular Respect to Banana Fly (Bactrocera musae (Tryon)) (Diptera: Tephritidae) (2010)