Dr Jay Gao
BE (Wuhan Tech), MS (Toronto), PhD (Georgia)
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 of Environment as a lecturer initially and later as a senior lecturer.
Research | Current
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.
Teaching | Current
My teaching has been in the area of GIS, spatial analysis, remote sensing, and digital image processing.
The courses that I have been involved in teaching include Remote Sensing of the Environment, Digital Image Processing, Geographic Data Analysis, and Spatial Analysis and GeoComputation.
Vincent Wang, PhD
Suyadi Suyadi, PhD (co-supervising)
Tingting Xu, PhD
Xuying Ma, PhD
Shi Yan, PhD
Daniel Marc dela Torre, PhD
Kumari Kshama Awasthi, MSc
Sesa Wiguna, MSc
Patrick Edards, Honors
Kate Emerson. Honors
Associate Editor of ISPRS Journal of Photogrametry and Remote Sensing
Member of Postgraduate Committee
Areas of expertise
Geographic Information System, Remote Sensing, Spatial Data Analysis, and Resources and Environmental Modelling
Selected publications and creative works (Research Outputs)
- Xu, T., & Gao, J. (2019). Directional multi-scale analysis and simulation of urban expansion in Auckland, New Zealand using logistic cellular automata. Computers, Environment and Urban Systems, 78.10.1016/j.compenvurbsys.2019.101390
- Li, X., Gao, J., Zhang, J., Wang, R., Jin, L., & Zhou, H. (2019). Adaptive strategies to overcome challenges in vegetation restoration to coalmine wasteland in a frigid alpine setting. CATENA, 18210.1016/j.catena.2019.104142
- Ma, X., Longley, I., Gao, J., Kachhara, A., & Salmond, J. (2019). A site-optimised multi-scale GIS based land use regression model for simulating local scale patterns in air pollution. The Science of the total environment, 685, 134-149. 10.1016/j.scitotenv.2019.05.408
Other University of Auckland co-authors: Jennifer Salmond
- Xu, T., Gao, J., & Li, Y. (2019). Machine learning-assisted evaluation of land use policies and plans in a rapidly urbanizing district in Chongqing, China. Land Use Policy, 87.10.1016/j.landusepol.2019.104030
- Suyadi, Gao, J., Lundquist, C. J., & Schwendenmann, L. (2019). Land-based and climatic stressors of mangrove cover change in the Auckland Region, New Zealand. AQUATIC CONSERVATION-MARINE AND FRESHWATER ECOSYSTEMS10.1002/aqc.3146
Other University of Auckland co-authors: Carolyn Lundquist, Luitgard Schwendenmann
- Wang, V., & Gao, J. (2019). Importance of structural and spectral parameters in modelling the aboveground carbon stock of urban vegetation. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 78, 93-101. 10.1016/j.jag.2019.01.017
- Wang, V., & Gao, J. (2019). Towards refined estimation of vegetation carbon stock in Auckland, New Zealand using WorldView-2 and LiDAR data: the impact of scaling. INTERNATIONAL JOURNAL OF REMOTE SENSING, 40 (23), 8727-8747. 10.1080/01431161.2019.1620376
- Xu, T., Gao, J., & Coco, G. (2019). Simulation of urban expansion via integrating artificial neural network with Markov chain - cellular automata. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 33 (10), 1960-1983. 10.1080/13658816.2019.1600701
Other University of Auckland co-authors: Tingting Xu, Giovanni Coco