Professor Thomas Bishop
People_

Professor Thomas Bishop

Academic Director
Sydney Informatics Hub
Phone
+61 2 8627 1056
Fax
+61 2 8627 1099
Address
C81 - ATP - The Biomedical Building
The University of Sydney
Professor Thomas Bishop

Tom Bishop is the Academic Director of the Sydney Informatics Hub which is a Core Research Facility at the University of Sydney. He is a Professor in the School of Life & Environmental Science where his research interests are in modelling and predicting the variation of environmental properties in space and time with an emphasis on applying this to the domains of soil, agriculture and hydrology. His main teaching is related to applied statistics, environmental science and GIS. He is an Associate Editor for the European Journal of Soil Science and Soil Research and on the Editorial Board of Geoderma and Pedosphere. Prior to starting work at the University of Sydney in 2007 he held postdoctoral positions at the University of Florida in the USA, Rothamsted Research in the United Kingdom and the University of New South Wales. He completed his PhD in Precision Agriculture in 2002 at the University of Sydney.

In broad terms my research focuses on the use of statistics to model and predict the variation of environmental properties in time and space. In the age of ubiquitous environmental data I believe there is an increasing opportunity for using such models to more precisely manage the environment at finer spatial and temporal scales. Such models are far from developed but I believe some combination of mechanistic and statistical modelling is required to predict in space and time. My main interests are in applying these methods in the domains of agriculture, soil and hydrology.

Currently my main research focus is on developing observation systems for crop yield, soil moisture and soil organic carbon using a combination of mechanistic models, space-time statistics, geospatial data products and field observations. The aim being to nowcast and forecast in near real-time at the spatial resolutions in order of a hectare (100m).

I also have ongoing interests in (i) sampling and monitoring schemes (ii) quantifying the amount and source of uncertainty in models and predictions (iii) change detection in space and time.

I have ongoing funded projects from private and public organisations including:

-using big data to predict cotton yield and constraints to yield;

-development of a decision support tool for irrigation scheduling;

-predict beef quality using metablomics.

In 2010 colleagues and I established a long term catchment-scale monitoring program in Muttama creek catchment in southern NSW where we monitor soil, plant and hydrological properties. It is a validation site for our modelling approaches and the focus of field schools for hydrology and environmental science students.

My main teaching is within Data science-related units within the Faculty of Science

Namely:

  • Foundations of Data Science (DATA100)
  • Introductory Staistical Methods (ENVX1002)
  • Applied Statistical Methods (ENVX2001)
  • Environmental GIS (ENVX3001)

In addition I make smaller contributions to:

  • Global Challenghes: food, Water and Climate (ENVI1003)
  • Environmental Chemistry (ENVI5708)
  • Scientific Method and Communication (ENSY4001)

Currently I am the main supervisor of 3 PhD students. Their research topics are:

-modelling the effect of fire on stream water quality;

-towards the development of an observation system for soil moisture;

-farm-scale nowcasting of soil moisture.

Timetable

Environment
Project titleResearch student
Soil moisture forecasting in dryland agricultureMuqeet AMIR
Leveraging Data Science For Livestock Management In FeedlotNing HAN
Integrating Remote Sensing Technologies with Machin Learning Techniques for the Assessment and Monitoring of Soil Health IndicatorsBillal HOSSEN
Using Digital Tools to Understand Crop Variability for Improved Agronomic Management.Sally POOLE

Publications

Books

  • Gray, J., Bishop, T. (2015). Climate change impacts on three key soil properties in NSW. Sydney: NSW Government: Office of Environment & Heritage.

Edited Books

  • Oliver, M., Bishop, T., Marchant, B. (2013). Precision Agriculture for Sustainability and Environmental Protection. Abingdon, UK: Routledge. [More Information]

Book Chapters

  • Han, S., Filippi, P., Roman Dobarco, M., Harianto, J., Crowther, M., Bishop, T. (2023). Multivariate analysis for soil science. In Michael J. Goss and Margaret Oliver (Eds.), Encyclopedia of Soils in the Environment, (pp. 499-508). UK: Elsevier Ltd.
  • Al-Shammari, D., Filippi, P., Moloney, J., Wimalathunge, N., Whelan, B., Bishop, T. (2020). Decision support systems (DSS) for better fertiliser management. In Leisa Armstrong (Eds.), Improving data management and decision support systems in agriculture, (pp. 1-25). Cambridge: Burleigh Dodds Science Publishing Limited. [More Information]
  • McBratney, A., Fajardo, M., Malone, B., Bishop, T., Stockmann, U., Odeh, I. (2018). Effective Multivariate Description of Soil and Its Environment. In Alex McBratney, Uta Stockmann, Budiman Minasny (Eds.), Pedometrics, (pp. 87-112). Cham: Springer. [More Information]

Journals

  • Al-Shammari, D., Whelan, B., Wang, C., Bramley, R., Bishop, T. (2025). Assessment of red-edge based vegetation indices for crop yield prediction at the field scale across large regions in Australia. European Journal of Agronomy, 164. [More Information]
  • Al-Shammari, D., Fuentes, I., Whelan, B., Wang, C., Filippi, P., Bishop, T. (2024). Combining Sentinel 1, Sentinel 2 and MODIS data for major winter crop type classification over the Murray Darling Basin in Australia. Remote Sensing Applications: society and environment, 34. [More Information]
  • Al-Shammari, D., Chen, Y., Wimalathunge, N., Wang, C., Han, S., Bishop, T. (2024). Incorporation of mechanistic model outputs as features for data-driven models for yield prediction: a case study on wheat and chickpea. Precision Agriculture, 25(5), 2531-2553. [More Information]

Conferences

  • Al-Shammari, D., Filippi, P., Bishop, T. (2024). Do pulse crops present a greater opportunity for site-specific crop-management than cereals? The 16th European Conference on Precision Agriculture, Australia: International Society of Precision Agriculture.
  • Al-Shammari, D., Filippi, P., Poole, S., Bishop, T. (2024). Identifying within-field yield gaps with boundary-line analysis. The 21st Australian Agronomy Conference, Australia: Australian Society of Agronomy Inc.
  • Bishop, T., Al-Shammari, D., Filippi, P. (2024). Mapping within-field drivers of crop production in space and time using interpretive machine learning. The 21st Australian Agronomy Conference, Australia: Australian Society of Agronomy Inc.

2025

  • Al-Shammari, D., Whelan, B., Wang, C., Bramley, R., Bishop, T. (2025). Assessment of red-edge based vegetation indices for crop yield prediction at the field scale across large regions in Australia. European Journal of Agronomy, 164. [More Information]

2024

  • Al-Shammari, D., Fuentes, I., Whelan, B., Wang, C., Filippi, P., Bishop, T. (2024). Combining Sentinel 1, Sentinel 2 and MODIS data for major winter crop type classification over the Murray Darling Basin in Australia. Remote Sensing Applications: society and environment, 34. [More Information]
  • Al-Shammari, D., Filippi, P., Bishop, T. (2024). Do pulse crops present a greater opportunity for site-specific crop-management than cereals? The 16th European Conference on Precision Agriculture, Australia: International Society of Precision Agriculture.
  • Al-Shammari, D., Filippi, P., Poole, S., Bishop, T. (2024). Identifying within-field yield gaps with boundary-line analysis. The 21st Australian Agronomy Conference, Australia: Australian Society of Agronomy Inc.

2023

  • Tilse, M., Filippi, P., Whelan, B., Bishop, T. (2023). A generalised approach to downscale areal-averaged yield and production data: a use-case in cotton quality. European Conference on Precision Agriculture (ECPA), Netherlands: Wageningen Academic Publishers.
  • Paranavithana, T., Mohamed Anas, M., Karunaratne, S., Macdonald, B., Wimalathunge, N., Bishop, T., Ratnayake, R. (2023). Environmental factors and spatial dependence explain half of the inherent variation in carbon pools of tropical paddy soils. Catena, 231, 107278. [More Information]
  • Al-Shammari, D., Chen, Y., Wimalathunge, N., Wang, C., Bishop, T. (2023). Integration of mechanistic model outputs as inputs into data-driven models for yield prediction: a case study on canola. European Conference on Precision Agriculture (ECPA), Netherlands: Wageningen Academic Publishers.

2022

  • Al-Shammari, D., Bishop, T., Wang, C., Whelan, B., Bramley, R. (2022). A comparison between machine learning and simple mechanistic-type models for yield prediction in site-specific crop yield predictions. 20th Australian Agronomy Conference, Toowoomba: Australian Society of Agronomy.
  • Han, S., Filippi, P., Singh, K., Whelan, B., Bishop, T. (2022). Assessment of global, national and regional-level digital soil mapping products at different spatial supports. European Journal of Soil Science, 73. [More Information]
  • Li, S., Shen, J., Bishop, T., Viscarra Rossel, R. (2022). Assessment of the Effect of Soil Sample Preparation, Water Content and Excitation Time on Proximal X-ray Fluorescence Sensing. Sensors, 22(12). [More Information]

2021

  • Al-Shammari, D., Whelan, B., Wang, C., Bramley, R., Fajardo Pedraza, M., Bishop, T. (2021). Impact of spatial resolution on the quality of crop yield predictions for site-specific crop management. Agricultural and Forest Meteorology, 310, 108622. [More Information]
  • Marang, I., Filippi, P., Weaver, T., Evans, B., Whelan, B., Bishop, T., Murad, M., Al-Shammari, D., Roth, G. (2021). Machine learning optimised hyperspectral remote sensing retrieves cotton nitrogen status. Remote Sensing, 13(8), 1586. [More Information]
  • Akter, F., Bishop, T., Vervoort, R. (2021). Space-time modelling of groundwater level and salinity. Science of the Total Environment, 776, 145865. [More Information]

2020

  • Lessels, J., Bishop, T. (2020). A post-event stratified random sampling scheme for monitoring event-based water quality using an automatic sampler. Journal of Hydrology, 580, 123393. [More Information]
  • Filippi, P., Cattle, S., Pringle, M., Bishop, T. (2020). A two-step modelling approach to map the occurrence and quantity of soil inorganic carbon. Geoderma, 371, 114382. [More Information]
  • Roberton, S., Bennett, J., Lobsey, C., Bishop, T. (2020). Assessing the sensitivity of site-specific lime and gypsum recommendations to soil sampling techniques and spatial density of data collection in Australian agriculture: A pedometric approach. Agronomy, 10(11), 1676. [More Information]

2019

  • Pozza, L., Bishop, T. (2019). A meta-analysis of published semivariograms to determine sample size requirements for assessment of heavy metal concentrations at contaminated sites. Soil Research, 57(4), 311-320. [More Information]
  • Filippi, P., Jones, E., Ginns, B., Whelan, B., Roth, G., Bishop, T. (2019). A novel approach to map the depth to a soil pH constraint – a useful tool for understanding yield variability. 19th Australian Agronomy Conference 2019, Wagga Wagga: Australian Society of Agronomy.
  • Wimalathunge, N., Bishop, T. (2019). A space-time observation system for soil moisture in agricultural landscapes. Geoderma, 344, 1-13. [More Information]

2018

  • Filippi, P., Cattle, S., Bishop, T., Jones, E., Minasny, B. (2018). Combining ancillary soil data with VisNIR spectra to improve predictions of organic and inorganic carbon content of soils. MethodsX, 5, 551-560. [More Information]
  • Karunaratne, S., Steinberg, D., Reid, A., Reddy, S., Carter, L., Baldock, J., Bishop, T., Gray, J., Acharige, N. (2018). Data cube and machine learning algorithms - is this the next generation soil carbon model? National Soils Conference 2018, Australia: Soil Science Australia.
  • Dharumarajan, S., Bishop, T., Hegde, R., Singh, S. (2018). Desertification Vulnerability Index - an effective approach to assess desertification processes: a case study in Anantapur District, Andhra Pradesh, India. Land Degradation and Development, 29(1), 150-161. [More Information]

2017

  • Huang, J., Bishop, T., Triantafilis, J. (2017). An error budget for digital soil mapping of cation exchange capacity using proximally sensed electromagnetic induction and remotely sensed gamma-ray spectrometer data. Soil Use and Management, 33(3), 397-412. [More Information]
  • Ugbaje, S., Odeh, I., Bishop, T., Li, J. (2017). Assessing the spatio-temporal variability of vegetation productivity in Africa: quantifying the relative roles of climate variability and human activities. International Journal of Digital Earth, 10(9), 879-900. [More Information]
  • Johnson, L., Bishop, T., Birch, G. (2017). Modelling drivers and distribution of lead and zinc concentrations in soils of an urban catchment (Sydney estuary, Australia). Science of the Total Environment, 598, 168-178. [More Information]

2016

  • Orton, T., Pringle, M., Bishop, T. (2016). A one-step approach for modelling and mapping soil properties based on profile data sampled over varying depth intervals. Geoderma, 262, 174-186. [More Information]
  • Gray, J., Bishop, T. (2016). Change in Soil Organic Carbon Stocks under 12 Climate Change Projections over New South Wales, Australia. Soil Science Society of America Journal, 80(5), 1296-1307. [More Information]
  • Gray, J., Bishop, T., Smith, P. (2016). Digital mapping of pre-European soil carbon stocks and decline since clearing over New South Wales, Australia. Soil Research, 54(1), 49-63. [More Information]

2015

  • Orton, T., Pringle, M., Allen, D., Dalal, R., Bishop, T. (2015). A geostatistical method to account for the number of aliquots in composite samples for normal and lognormal random variables. European Journal of Soil Science, 66(6), 1023-1032. [More Information]
  • Lessels, J., Bishop, T. (2015). A simulation based approach to quantify the difference between event-based and routine water quality monitoring schemes. Journal of Hydrology: Regional Studies, 4, 439-451. [More Information]
  • Karunaratne, S., Bishop, T., Lessels, J., Baldock, J., Odeh, I. (2015). A space-time observation system for soil organic carbon. Soil Research, 53, 647-661. [More Information]

2014

  • Karunaratne, S., Bishop, T., Lessels, J., Baldock, J., Odeh, I. (2014). A space-time observation system for soil organic carbon. Soil Change Matters International Workshop, Melbourne: State Government Victoria, Australia.
  • Karunaratne, S., Bishop, T., Baldock, J., Odeh, I. (2014). Catchment scale mapping of measureable soil organic carbon fractions. Geoderma, 219-220(May), 14-23. [More Information]
  • Akpa, S., Odeh, I., Bishop, T., Hartemink, A. (2014). Digital mapping of soil particle-size fractions for Nigeria. Soil Science Society of America Journal, 78(6), 1953-1966. [More Information]

2013

  • Orton, T., Pringle, M., Dalal, R., Allen, D., Bishop, T. (2013). Assessing the Effectiveness of Sampling Strategies for SOC Stock Estimation. 10th Biennial Meeting of Commission 1.5 Pedometrics Division 1 of the International Union of Soil Science (IUSS), Kenya: ICRAF & CIAT.
  • Akpa, S., Odeh, I., Bishop, T. (2013). Assessing the Potential Carbon Sequesterability of Soils Under Land Use Types Across Agro-climatic Zones of Nigeria. 10th Biennial Meeting of Commission 1.5 Pedometrics Division 1 of the International Union of Soil Science (IUSS), Kenya: ICRAF & CIAT.
  • Lessels, J., Bishop, T. (2013). Estimating water quality using linear mixed models with stream discharge and turbidity. Journal of Hydrology, 498, 13-22. [More Information]

2012

  • Bishop, T., Daniel, R., Guest, D., Nelson, M., Chang, C. (2012). A digital soil map of Phytophthora cinnamomi in the Gondwana Rainforests of eastern Australia. In Budiman Minasny, Brendan P. Malone, Alex B. McBratney (Eds.), Digital Soil Assessments and Beyond, (pp. 65-68). Leiden, The Netherlands: CRC Press. [More Information]
  • Gray, J., Bishop, T., Peter, S., Robinson, N., Brough, D. (2012). A pragmatic quantitative model for soil organic carbon distribution in eastern Australia. In Budiman Minasny, Brendan P. Malone, Alex B. McBratney (Eds.), Digital Soil Assessments and Beyond, (pp. 115-120). Leiden, The Netherlands: CRC Press. [More Information]
  • Bishop, T. (2012). Estimation of the probability of exceeding water quality guidelines using generalised linear mixed models. Journal of Environmental Quality, 13.

2011

  • Lessels, J., Bishop, T. (2011). A geostatistical comparison between routine and event-based water quality sampling. The 34th World Congress of the International Association for Hydro-Environment Engineering and Research (IAHR 2011), Barton, ACT: Engineers Australia.
  • Nelson, M., Bishop, T., Triantafilis, J., Odeh, I. (2011). An error budget for different sources of error in digital soil mapping. European Journal of Soil Science, 62(3), 417-430. [More Information]
  • Niazi, N., Bishop, T., Singh, B. (2011). Evaluation of Spatial Variability of Soil Arsenic Adjacent to a Disused Cattle-Dip Site, Using Model-Based Geostatistics. Environmental Science & Technology, 45, 10463-10470. [More Information]

2010

  • Niazi, N., Singh, B., Bishop, T. (2010). A geostatistical model based approach to evaluate spatial variability of arsenic in soil and to compare arsenic hyperaccumulation efficiency of two fern species. 7th International Conference on Phytotechnologies "Phytotechnologies in the 21st century: challenges after Copenhagen 2009.
  • Niazi, N., Bishop, T., Singh, B. (2010). Comparative study for the arsenic hyperaccumulation by ferns: a model-based geostatistical approach. ConSoil International Conference on the Management of Groundwater.
  • Niazi, N., Singh, B., Bishop, T., Van Zwieten, L., Kachenko, A. (2010). Environmentally friendly approach to clean-up arsenic contaminated soils. The 'Centenary Research Symposium' of The Faculty of Agriculture, Food and Natural Resources, The University of Sydney.

2009

  • Panten, K., Bramley, R., Lark, R., Bishop, T. (2009). Enhancing the value of field experimentation through whole-of-block designs. Precision Agriculture, 11(2), 198-213. [More Information]
  • Easdown, D., Ougrinovskaia, A., Saunders, N., Warren, D., Ancev, T., Bishop, T., Mansfield, S. (2009). Learning and Teaching in Summer: Is it better and why? UniServe Science, The University of Sydney Conference 2009, Australia: Uniserve Science.
  • Ji, Y., Vervoort, R., Bishop, T. (2009). Spatiotemporal Model of Monthly Rainfall in the Coxs' Creek Catchment. 32nd Hydrology and Water Resources Symposium H2009, Australia: Engineers Australia.

2008

  • Bishop, T., Lark, R. (2008). A comparison of parametric and non-parametric methods for modelling a coregionalization. Geoderma, 148, 13-24. [More Information]
  • Minasny, B., Bishop, T. (2008). Analysing uncertainty. In NJ McKenzie; MJ Grundy; R Webster; AJ Ringrose-Voase (Eds.), Guidelines for Surveying soil and Land Resources, (pp. 383-393). Australia: CSIRO Publishing.
  • Odeh, I., Bishop, T., Malone, B. (2008). Modelling Soil Organic Carbon Dynamics Under Different Crop Production Systems In North -Western NSW Using The Rothc Model. Soils 2008 - The Living Skin of Planet Earth, New Zealand: Soil Science Australia and New Zealand Society for Soil Science.

2007

  • Bishop, T., Lark, R. (2007). A landscape-scale experiment on the changes in available potassium over a winter wheat cropping season. Geoderma, 141(3-4), 384-396. [More Information]
  • Lark, R., Bishop, T. (2007). Cokriging particle size fractions of the soil. European Journal of Soil Science, 58(3), 763-774. [More Information]
  • Lark, R., Bishop, T., Webster, R. (2007). Using expert knowledge with control of false discovery rate to select regressors for prediction of soil properties. Geoderma, 138(1-2), 65-78. [More Information]

2006

  • Van Griensven, A., Meixner, T., Grunwald, S., Bishop, T., Diluzio, M., Srinivasan, R. (2006). A global sensitivity analysis tool for the parameters of multi-variable catchment models. Journal of Hydrology, 324(1-4), 10-23. [More Information]
  • Bishop, T., Minasny, B. (2006). Digital Soil-Terrain Modeling: The Predictive Potential and Uncertainty. In Sabine Grunwald (Eds.), Environmental Soil-Landscape Modeling Geographic Information Technologies and Pedometris, (pp. 185-213). USA: CRC Press.
  • Bishop, T., Minasny, B. (2006). Digital soil-terrain modelling: the predictive potential & uncertainty. In Not known (Eds.), Environmental Soil-Landscape Modeling: Geographic Information Technologies and Pedometrics, (pp. 185-213). TBC.

2003

  • Grunwald, S., Bishop, T. (2003). Modelling water quality in the Sandusky watershed, Ohio. 2003 ASAE International Conference.
  • Bishop, T., Grunwald, S. (2003). Modelling water quality in the Sandusky watershed, Ohio: spatial sensitivity of the SWAT model. 2003 ESRI User Conference.

2002

  • Bishop, T., McBratney, A. (2002). Creating Field Extent Digital Elevation Models for Precision Agriculture. Precision Agriculture, 3(1), 37-46. [More Information]

2001

  • Bishop, T., McBratney, A. (2001). A comparison of prediction methods for the creation of field-extent soil property maps. Geoderma, 103(1-2), 149-160. [More Information]
  • Bishop, T., McBratney, A., Whelan, B. (2001). Measuring the quality of digital soil maps using information criteria. Geoderma, 103, 95-111. [More Information]
  • Bishop, T., Odeh, I. (2001). The role of geographic information systems in catchment scale soil studies. In S.R. Cattle & B.H. George (Eds.), Describing, Analysing and Managing Our Soil, (pp. 361-384). Sydney: Australian Soil Science Society.

2000

  • McBratney, A., Odeh, I., Bishop, T., Dunbar, M., Shatar, T. (2000). An overview of pedometric techniques in soil survey. Geoderma, 97(3-4), 293-327. [More Information]
  • McBratney, A., Bishop, T., Teliatnikov, I. (2000). Two soil profile reconstruction techniques. Geoderma, 97(3-4), 209-221. [More Information]

1999

  • Bishop, T., McBratney, A. (1999). Interpolation techniques for creating digital elevation models. 2nd European Conference on Precision Agriculture. Sheffield Academic Press.
  • Bishop, T., McBratney, A., Laslett, G. (1999). Modelling soil attribute depth functions with equal-area quadratic smoothing splines. Geoderma, 91(1-2), 27-45. [More Information]
  • McBratney, A., Bishop, T. (1999). The information content of digital (soil) maps. The Second Approximation International Conference on Soil Resources: Their Inventory, Analysis and Interpretation for Use in the 21st Century.

1998

  • Bishop, T., Boydell, B., Shatar, T., Whelan, B., McBratney, A. (1998). Data handling and spatial prediction techniques and their application to Precision Agriculture. A Workshop Held at Mercure Inn, Townsville: CSIRO.

Selected Grants

2024

  • Landuse risks for pesticides and N movement in cotton catchments, Bishop T, Van Ogtrop F, Cotton Research and Development Corporation/Client Commissioned Research
  • RES: SmartSat CRC Project P3-38: Earth Observation (EO) analytics for site-specific weed management - Data Farming, SmartSat - Thomas Bishop - RA0003034, Bishop T, SmartSat CRC Ltd/Client Commissioned Research

2023

  • National Collaborative Research Infrastructure Strategy - for Australian Plant Phenomics Facility (APPF), Bishop T, Department of Education and Training (Federal)/National Collaborative Research Infrastructure Strategy (NCRIS)
  • RES, Geospatial analytics to predict the impact of residual herbicides on establishment and yield. NSW Department of Primary Industries. Bishop, Thomas. RA0003031, Bishop T, Department of Primary Industries NSW/Client Commissioned Research
  • Heurist Collections Integration, Bishop T, Australian Research Data Commons (ARDC)/Client Commissioned Research