Personal profile
Biography
Tony has expertise in geographic information systems, remote sensing, machine learning applied to environmental information, AI for land cover mapping, development of national and international data standards and systems for data collection, storage and management. Tony has extensive experience in the development of integrated national information systems based on the aggregation of data from agencies across Australia, working with a range of scientific and collections-based organisations, including geoscience and environment agencies, libraries, museums, herbaria, archives and galleries.
Tony’s APS career included over 25 years in executive roles within the Department of the Environment, National Library of Australia and Bureau of Meteorology. At the Bureau, he was responsible for the development of a national database of surface and groundwater information that underpins the Water Information Program, established under Part 7 of the Water Act 2007, and products such as the National Water Account and Australian Water Resource Assessments. As co-chair of the WMO/OGC Hydrology Domain Working Group (2013-2024), he contributed to the development of the WaterML2 international standards for hydrological data exchange.
Research Interests
Tony's current research interests include use of earth observations, in situ data and AI foundation models for earth science applications such as monitoring, estimating and predicting water resources, land cover and environmental change as well as the application of machine learning techniques to data classification and interpretation.
Qualifications
BSc (Hons), Grad. Dip. Comp. Stud., PhD
Education/Academic qualification
PhD, Australian National University
Award Date: 8 Nov 2024
Graduate Diploma, Computing Studies, University of Canberra
Award Date: 22 Apr 1993
Honours, BSc, Australian National University
Award Date: 9 May 1984
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U-Net Convolutional Neural Network for Mapping Natural Vegetation and Forest Types from Landsat Imagery in Southeastern Australia
Boston, T., Van Dijk, A. & Thackway, R., 13 Jun 2024, In: Journal of Imaging. 10, 6, 24 p., 143.Research output: Contribution to journal › Article › peer-review
Open Access8 Citations (Scopus) -
Convolutional Neural Network Shows Greater Spatial and Temporal Stability in Multi-Annual Land Cover Mapping Than Pixel-Based Methods
Boston, T., Van Dijk, A. & Thackway, R., 18 Apr 2023, In: Remote Sensing. 15, 8, 21 p., 2132.Research output: Contribution to journal › Article › peer-review
Open Access10 Citations (Scopus) -
Comparing CNNs and Random Forests for Landsat Image Segmentation Trained on a Large Proxy Land Cover Dataset
Boston, T., Van Dijk, A., Larraondo, P. R. & Thackway, R., 14 Jul 2022, In: Remote Sensing. 14, 14, 19 p., 3396.Research output: Contribution to journal › Article › peer-review
Open Access57 Citations (Scopus) -
Some experiments in automated identification of Australian plants using convolutional neural networks
Boston, T. & Van Dijk, A., 2019, 23rd International Congress on Modelling and Simulation - Supporting Evidence-Based Decision Making: The Role of Modelling and Simulation, MODSIM 2019. Elsawah, S. (ed.). Modelling and Simulation Society of Australia and New Zealand Inc (MSSANZ), p. 15-21 7 p. (23rd International Congress on Modelling and Simulation - Supporting Evidence-Based Decision Making: The Role of Modelling and Simulation, MODSIM 2019).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review
2 Citations (Scopus)