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Dr Jim Watson

Adjunct Associate Professor

School of the Environment
Faculty of Science
j.watson@uq.edu.au

Overview

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.

Research Interests

  • Remote Sensing
    I am currently investigating methods for analysing land use history from Landsat and Sentinel satellite data.

Qualifications

  • Doctor of Philosophy, The University of Queensland

Publications

  • Journal Article: Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model

    Watson, James, Challinor, Andrew J., Fricker, Thomas E. and Ferro, Christopher A. T. (2014). Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model. Climatic Change, 132 (1), 93-109. doi: 10.1007/s10584-014-1264-3

  • Journal Article: A meta-analysis of crop yield under climate change and adaptation

    Challinor, A. J., Watson, J., Lobell, D. B., Howden, S. M., Smith, D. R. and Chhetri, N. (2014). A meta-analysis of crop yield under climate change and adaptation. Nature Climate Change, 4 (4), 287-291. doi: 10.1038/nclimate2153

  • Book Chapter: Food security and food production systems

    Porter, John R., Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammad Mohsin, Lobell, David B., Travasso, Maria Isabel, Netra Chhetri, Netra Chhetri, Garrett, Karen, Ingram, John, Lipper, Leslie, McCarthy, Nancy, McGrath, Justin, Smith, Daniel, Thornton, Philip, Watson, James and Ziska, Lewis (2014). Food security and food production systems. Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. (pp. 485-533) edited by Christopher B. Field, Vicente R. Barros, David Jon Dokken, Katharine J. Mach, Michael D. Mastrandrea, T. Eren Bilir, Monalisa Chatterjee, Kristie L. Ebi, Yuka Otsuki Estrada, Robert C. Genova, Betelhem Girma, Eric S. Kissel, Andrew N. Levy, Sandy MacCracken and Patricia R. Mastrandrea. New York, United States: Cambridge University Press.

  • Journal Article: The relative importance of rainfall, temperature and yield data for a regional-scale crop model

    Watson, James and Challinor, Andrew (2013). The relative importance of rainfall, temperature and yield data for a regional-scale crop model. Agricultural and Forest Meteorology, 170, 47-57. doi: 10.1016/j.agrformet.2012.08.001

  • Conference Publication: Patterns in complex systems modeling

    Wiles, Janet and Watson, James (2005). Patterns in complex systems modeling. Sixth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2005), Brisbane, Australia, 6-8 July 2005. Berlin, Germany: Springer-Verlag. doi: 10.1007/11508069_69

View all Publications

Publications

Featured Publications

  • Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model

    Watson, James, Challinor, Andrew J., Fricker, Thomas E. and Ferro, Christopher A. T. (2014). Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model. Climatic Change, 132 (1), 93-109. doi: 10.1007/s10584-014-1264-3

  • A meta-analysis of crop yield under climate change and adaptation

    Challinor, A. J., Watson, J., Lobell, D. B., Howden, S. M., Smith, D. R. and Chhetri, N. (2014). A meta-analysis of crop yield under climate change and adaptation. Nature Climate Change, 4 (4), 287-291. doi: 10.1038/nclimate2153

  • Food security and food production systems

    Porter, John R., Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammad Mohsin, Lobell, David B., Travasso, Maria Isabel, Netra Chhetri, Netra Chhetri, Garrett, Karen, Ingram, John, Lipper, Leslie, McCarthy, Nancy, McGrath, Justin, Smith, Daniel, Thornton, Philip, Watson, James and Ziska, Lewis (2014). Food security and food production systems. Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. (pp. 485-533) edited by Christopher B. Field, Vicente R. Barros, David Jon Dokken, Katharine J. Mach, Michael D. Mastrandrea, T. Eren Bilir, Monalisa Chatterjee, Kristie L. Ebi, Yuka Otsuki Estrada, Robert C. Genova, Betelhem Girma, Eric S. Kissel, Andrew N. Levy, Sandy MacCracken and Patricia R. Mastrandrea. New York, United States: Cambridge University Press.

  • The relative importance of rainfall, temperature and yield data for a regional-scale crop model

    Watson, James and Challinor, Andrew (2013). The relative importance of rainfall, temperature and yield data for a regional-scale crop model. Agricultural and Forest Meteorology, 170, 47-57. doi: 10.1016/j.agrformet.2012.08.001

  • Patterns in complex systems modeling

    Wiles, Janet and Watson, James (2005). Patterns in complex systems modeling. Sixth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2005), Brisbane, Australia, 6-8 July 2005. Berlin, Germany: Springer-Verlag. doi: 10.1007/11508069_69

Book Chapter

  • The use of hyperspectral proximal sensing for phenotyping of plant breeding trials

    Potgieter, Andries B., Watson, James, George-Jaeggli, Barbara, McLean, Gregory, Eldridge, Mark, Chapman, Scott C., Laws, Kenneth, Christopher, Jack, Chenu, Karine, Borrell, Andrew, Hammer, Graeme and Jordan, David R. (2019). The use of hyperspectral proximal sensing for phenotyping of plant breeding trials. Fundamentals, sensor systems, spectral libraries, and data mining for vegetation. (pp. 127-148) edited by Prasad S. Thenkabail, John G. Lyon and Alfredo Huete. Boca Raton FL, USA: CRC Press. doi: 10.1201/9781315164151-5

  • The use of hyperspectral proximal sensing for phenotyping of plant breeding trials

    Potgieter, Andries B., Watson, James, George-Jaeggli, Barbara, McLean, Gregory, Eldridge, Mark, Chapman, Scott C., Laws, Kenneth, Christopher, Jack, Chenu, Karine, Borrell, Andrew, Hammer, Graeme L. and Jordan, David R. (2018). The use of hyperspectral proximal sensing for phenotyping of plant breeding trials. Fundamentals, sensor systems, spectral libraries, and data mining for vegetation. (pp. 127-147) Boca Raton, FL, United States: CRC Press. doi: 10.1201/9781315164151-5

  • Food security and food production systems

    Porter, John R., Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammad Mohsin, Lobell, David B., Travasso, Maria Isabel, Netra Chhetri, Netra Chhetri, Garrett, Karen, Ingram, John, Lipper, Leslie, McCarthy, Nancy, McGrath, Justin, Smith, Daniel, Thornton, Philip, Watson, James and Ziska, Lewis (2014). Food security and food production systems. Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. (pp. 485-533) edited by Christopher B. Field, Vicente R. Barros, David Jon Dokken, Katharine J. Mach, Michael D. Mastrandrea, T. Eren Bilir, Monalisa Chatterjee, Kristie L. Ebi, Yuka Otsuki Estrada, Robert C. Genova, Betelhem Girma, Eric S. Kissel, Andrew N. Levy, Sandy MacCracken and Patricia R. Mastrandrea. New York, United States: Cambridge University Press.

  • Towards a network pattern language for complex systems

    Watson, J., Hawkins, J., Bradley, D., Dassanayake, D., Wiles, J. and Hanan, J. (2005). Towards a network pattern language for complex systems. Recent Advances In Artificial Life. (pp. 309-317) Shatin, Hong Kong: World Scientific Publishing. doi: 10.1142/9789812701497_0023

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