Who's Who in
Sciences Academia

    Jay Gao

  • Lecturer
  • Jay Gao
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  • Department of Geology
  • http://www.geology.auckland.ac.nz/
  • University of Auckland
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  • Private Bag 92019
    Auckland
    New Zealand
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  • Contact by e-mail?
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  • Different from my colleagues, I received my first degree not in Geography, not even in Arts or Science - it was in photogrammetric engineering from Wuhan Technical University of Surveying and Mapping. I did not start my education in Geography until I enrolled in the Master’s degree programme at the University of Toronto. Upon graduation from the University of Georgia in the U.S. in 1992, I joined the School as a lecturer. Over my academic career, I have carried out quite a number of research projects on remote sensing, GIS, GPS and their integrated applications to resources management and environmental monitoring. These studies can be generalised into two major themes:

    Quantitative remote sensing: In this sub-field my research has demonstrated the possibility of retrieving physical parameters of ground features such as water quality indicators and grassland density from satellite data quantitatively. Some of these detected parameters were then linked to environmental variables to explore the impact of climate change on the natural environment.

    Integration of geo-computational methods: The emergence of new geo-computational technologies such as GPS has eased the acquisition of certain spatial data. Accompanying this new technology arises the issue of how to integrate it innovatively with other existing methods to maximize its potential. My research explored the feasibility and potential of combining GIS, GPS and remote sensing, and how the integrated technologies can benefit monitoring of the environment.

    My recent research has focused on mapping of land covers from satellite imagery using spatial information. In particular, my research has explored how accuracy might be improved through incorporation of spatial adjacency and spatial connection as well as additional spatial knowledge in image classification
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