Overview
Background
Dr Jim Watson is Principal Scientist (Remote Sensing) at the New South Wales Department of Planning and Environment, and a member of the Joint Remote Sensing Research Program (https://www.jrsrp.org.au/).
He designs and leads research projects for monitoring native vegetation, with a focus on algorithms for extracting information from satellite datasets and aerial photography.
Jim received a PhD in Computer Science from the University of Queensland. He has previously worked on the statistical inference of network interactions at the School of Computing (University of Leeds, United Kingdom), crop-climate modelling at the Institute for Climate and Atmospheric Science (University of Leeds), and agricultural proximal sensing at the Queensland Alliance for Agriculture and Food Innovation (University of Queensland).
He is a contributing author of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (AR5), has developed a number of novel feature detection algorithms, and is experienced in high performance computing.
Availability
- Dr Jim Watson is:
- Available for supervision
Qualifications
- Doctor of Philosophy, The University of Queensland
Research interests
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Remote Sensing
I am currently investigating methods for analysing land use history from Landsat and Sentinel satellite data.
Works
Search Professor Jim Watson’s works on UQ eSpace
2002
Conference Publication
Evolving Complex Integrated Behaviour by Masking and Unmasking Selection Pressures
Wiles, Janet, Watson, James, Tonkes, Bradley and Deacon, Terrence (2002). Evolving Complex Integrated Behaviour by Masking and Unmasking Selection Pressures. International Conference on Complex Systems (ICCS2002), Nashua, NH, United States, 9-14 June 2002.
2002
Conference Publication
Stability and Task Complexity: A Neural Network Model of Evolution and Learning
Watson, James, Geard, Nicholas and Wiles, Janet H. (2002). Stability and Task Complexity: A Neural Network Model of Evolution and Learning. The 8th International Conference on Artificial Life (Artificial Life VIII), Sydney, Australia, 9-13 December, 2002. Cambridge, Massachusetts: The MIT Press.
2001
Conference Publication
How learning can guide evolution in hierarchical modular tasks
Wiles, J. H., Tonkes, B. and Watson, J. R. (2001). How learning can guide evolution in hierarchical modular tasks. Twenty-Third Annual Conference of the Cognitive Science Society, Edinburgh, Scotland, 1-4 August, 2001. Mahwah, New Jersey: Lawrence Erlbaum Associates.
Supervision
Availability
- Dr Jim Watson is:
- Available for supervision
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Media
Enquiries
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