Tools that support the discovery, analysis and re-use of data
- Cloud-based virtual desktop to run and share experiments (CoESRA)
- Data submission, harmonisation and retrieval of ecological data (SHaRED)
- Discovery, mapping and analysis of landscape-scale ecosystem datasets (Data Visualiser)
- Cloud-based analysis, synthesis and training platform
Space-based network for agriculture & ecosystems
TERN allows Australia and the world to respond to ever-evolving environmental and agricultural challenges, including climate impacts, food security and species loss.
From better weather forecasting and carbon budgeting to improved agricultural productivity forecasts, TERN data ensure the accuracy of some of the planet’s most important satellite monitoring and prediction tools. TERN provides the international space agencies, including NASA, with high-quality, on-the-ground data to properly calibrate and validate satellite observations and predictions.
Yang, Shanshan, Jiahua Zhang, Sha Zhang, Jingwen Wang, Yun Bai, Fengmei Yao, and Huadong Guo. 2020. ‘The potential of remote sensing-based models on global water-use efficiency estimation: An evaluation and intercomparison of an ecosystem model (BESS) and algorithm (MODIS) using site level and upscaled eddy covariance data’, Agricultural and Forest Meteorology, 287. https://doi.org/10.1016/j.agrformet.2020.107959
Woodgate, W., van Gorsel, E., Hughes, D. et al. THEMS: an automated thermal and hyperspectral proximal sensing system for canopy reflectance, radiance and temperature. Plant Methods 16, 105 (2020). https://doi.org/10.1186/s13007-020-00646-w
Song, R.; Muller, J.-P.; Kharbouche, S.; Yin, F.; Woodgate, W.; Kitchen, M.; Roland, M.; Arriga, N.; Meyer, W.; Koerber, G.; Bonal, D.; Burban, B.; Knohl, A.; Siebicke, L.; Buysse, P.; Loubet, B.; Leonardo, M.; Lerebourg, C.; Gobron, N. Validation of Space-Based Albedo Products from Upscaled Tower-Based Measurements Over Heterogeneous and Homogeneous Landscapes. Remote Sens. 2020, 12, 833. https://doi.org/10.3390/rs12050833
Metternicht G., Mueller N., Lucas R. (2020) Digital Earth for Sustainable Development Goals. In: Guo H., Goodchild M.F., Annoni A. (eds) Manual of Digital Earth. Springer, Singapore. https://doi.org/10.1007/978-981-32-9915-3_13
Fisher, J. B., Lee, B., Purdy, A. J., Halverson, G. H., Dohlen, M. B., Cawse-Nicholson, K., et al. (2020). ECOSTRESS: NASA’s Next Generation Mission to measure evapotranspiration from the International Space Station. Water Resources Research, 56, e2019WR026058. https://doi.org/10.1029/2019WR026058
Data-driven carbon farming innovation
Increasing soil carbon and soil moisture promotes sustainable production, resilience to climate variability and environmental change and is a tradeable asset on the global carbon market.
Based on an innovative use of carbon flux monitoring, TERN is working with a consortium of major beef producers, seed companies, environmental consultants, and government agencies to increase soil carbon in grazing lands and develop new methods of validating carbon sequestration. The CO2, water and energy exchange data provided by TERN are ideal for calibrating and validating carbon stock models and provide a cost-effective alternative to expensive soil sampling for quantifying soil carbon sequestration at scale.
Li, Jinquan, Junmin Pei, Feike A. Dijkstra, Ming Nie, and Elise Pendall. 2021. ‘Microbial carbon use efficiency, biomass residence time and temperature sensitivity across ecosystems and soil depths’, Soil Biology and Biochemistry, 154: 108117. https://doi.org/10.1016/j.soilbio.2020.108117
Johnston, A.S.A., Meade, A., Ardö, J. et al. Temperature thresholds of ecosystem respiration at a global scale. Nat Ecol Evol 5, 487–494 (2021). https://doi.org/10.1038/s41559-021-01398-z
Campbell, David I., Georgie L. Glover-Clark, Jordan P. Goodrich, Christopher P. Morcom, Louis A. Schipper, and Aaron M. Wall. 2021. ‘Large differences in CO2 emissions from two dairy farms on a drained peatland driven by contrasting respiration rates during seasonal dry conditions’, Science of The Total Environment, 760: 143410. https://doi.org/10.1016/j.scitotenv.2020.143410
Li, J. Q., M. Nie, J. R. Powell, A. Bissett, and E. Pendall. 2020. ‘Soil physico-chemical properties are critical for predicting carbon storage and nutrient availability across Australia’, Environmental Research Letters, 15. https://doi.org/10.1088/1748-9326/ab9f7e
Improved economic viability for industry and agri-business
TERN and its research partners provide federal and state government agricultural departments with essential data for agricultural monitoring, planning and risk mitigation.
TERN’s near real-time satellite data products are enabling early and accurate estimates of grain crops and regular seasonal outlooks for sorghum and wheat. Enabling prediction of crop size and geographical distribution help industry make strategic decisions and avoid market volatility within Australia and globally. This commodity forecasting, enabled by TERN data, facilitates Australian agricultural businesses and government agency decision-making processes.
Moore, C. E., K. Meacham-Hensold, P. Lemonnier, R. A. Slattery, C. Benjamin, C. J. Bernacchi, T. Lawson, and A. P. Cavanagh. 2021. ‘The effect of increasing temperature on crop photosynthesis: From enzymes to ecosystems’, Journal of Experimental Botany, 72: 2822-44. https://doi.org/10.1093/jxb/erab090
Giltrap, Donna L., Miko U. F. Kirschbaum, and Lìyǐn L. Liáng. 2021. ‘The potential effectiveness of four different options to reduce environmental impacts of grazed pastures. A model-based assessment’, Agricultural Systems, 186: 102960. https://doi.org/10.1016/j.agsy.2020.102960
Amazirh, A., O. Merlin, S. Er-Raki, E. Bouras, and A. Chehbouni. 2021. ‘Implementing a new texture-based soil evaporation reduction coefficient in the FAO dual crop coefficient method’, Agricultural Water Management, 250.https://doi.org/10.1016/j.agwat.2021.106827
Verburg, Kirsten; Cocks, Brett; Stockmann, Uta; Thomas, Mark; Austin, Jenet; Glover, Mark; Gallant, John. Using plant available water (PAW) to inform decision-making and crop resourcing: What to do when you do not have a PAWC characterisation on-site?. In: GRDC Grains Research Updates; 3-4 March 2020; Goondiwindi. GRDC; 2020. 12. http://hdl.handle.net/102.100.100/354896?index=1
Shen, J. X., A. Huete, X. L. Ma, N. N. Tran, J. Joiner, J. Beringer, D. Eamus, and Q. Yu. 2020. ‘Spatial pattern and seasonal dynamics of the photosynthesis activity across Australian rainfed croplands’, Ecological Indicators, 108.https://doi.org/10.1016/j.ecolind.2019.105669
Potgieter, A. B., K. Lawson, and A. R. Huete. 2013. ‘Determining crop acreage estimates for specific winter crops using shape attributes from sequential MODIS imagery’, International Journal of Applied Earth Observation and Geoinformation, 23: 254-63. https://doi.org/10.1016/j.jag.2012.09.009
Ensuring the sustainability of Australia's cities
Without TERN-delivered data, governments would not be able to quantify groundwater recharge of a crucial urban water supply source and understand and manage the ecological and social consequences.
TERN monitoring infrastructure delivers the data required to determine the long-term sustainability of Perth’s main groundwater supply. TERN data on soil moisture and land-atmosphere exchanges help scientists understand the recharge rates to the Gnangara groundwater mound and how they’re changing over time. Data also shed light on how large areas of native vegetation respond to groundwater changes.
Silberstein, R., Macfarlane, C., Lambert, T., Hawdon, A., McJannet, D. (2014). Innovative ways to estimate recharge to Perth’s groundwater mound. Hydrology and Water Resources Symposium 2014 / Engineers Australia and National Committee on Water Engineering (986-993). Engineers Australia. https://publications.csiro.au/publications/publication/PIcsiro:EP136713.
Shanafield, M., P. G. Cook, H. A. Gutierrez-Jurado, R. Faux, J. Cleverly, and D. Eamus. 2015. ‘Field comparison of methods for estimating groundwater discharge by evaporation and evapotranspiration in an arid-zone playa’, Journal of Hydrology, 527: 1073-83. https://doi.org/10.1016/j.jhydrol.2015.06.003
Jarihani, A. A., J. R. Larsen, J. N. Callow, T. R. McVicar, and K. Johansen. 2015. ‘Where does all the water go? Partitioning water transmission losses in a data-sparse, multi-channel and low-gradient dryland river system using modelling and remote sensing’, Journal of Hydrology, 529: 1511-29. https://dx.doi.org/10.1016/j.jhydrol.2015.08.030
Reducing the cost of droughts and heatwaves
TERN enables governments, businesses and individuals in Australia and around the world to make informed decisions on climate change mitigation, adaptation and resilience to reduce the cost of extreme events.
Long-term data collected by TERN and its partners on Australia’s land-atmosphere exchanges of energy, carbon and water (fluxes) are the world’s most valuable observations for building and evaluating models for projecting future droughts and heatwaves. Australian flux data collected by TERN are the only data that enable land surface models—vital components of climate models—to operate accurately and reflect the range of conditions now and those we’re likely to experience in the future.
Global Analysis of Atmospheric Transmissivity Using Cloud Cover, Aridity and Flux Network Datasets Srivastava et al. (2021)
Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions Chang et al (2021) Nature Communications
Carbon and water fluxes in two adjacent Australian semi-arid ecosystems Tarin et al (2020)