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Uses of Digital Earth Australia notebooks and tools

The following is a non-exhaustive list of scientific papers and projects that have used notebooks, code or tools from dea-notebooks. If you have used material from this repository, please reference them using this citation and add a link to your work below!

Krause, C., Dunn, B., Bishop-Taylor, R., Adams, C., Burton, C., Alger, M., Chua, S., Phillips, C., Newey, V., Kouzoubov, K., Leith, A., Ayers, D., Hicks, A., DEA Notebooks contributors 2021. Digital Earth Australia notebooks and tools repository. Geoscience Australia, Canberra. https://doi.org/10.26186/145234

Scientific papers

  • Abhik, S., Hope, P., Hendon, H.H., Hutley, L.B., Johnson, S., Drosdowsky, W. and Brown, J., 2021. The Influence of 2015-16 El Niño On the Record-Breaking Mangrove Dieback Along Northern Australia Coast. Scientific Reports, Preprint. https://doi.org/10.21203/rs.3.rs-650667/v1
  • Bishop-Taylor, R., Nanson, R., Sagar, S., Lymburner, L., 2021. Mapping Australia's dynamic coastline at mean sea level using three decades of Landsat imagery. Remote Sensing of Environment, 267, 112734. https://doi.org/10.1016/j.rse.2021.112734
  • Bishop-Taylor, R., Sagar, S., Lymburner, L., Alam, I. and Sixsmith, J., 2019. Sub-pixel waterline extraction: Characterising accuracy and sensitivity to indices and spectra. Remote Sensing, 11(24), p.2984. https://www.mdpi.com/2072-4292/11/24/2984
  • Burton, C. A., Rifai, S. W., Renzullo, L. J. and Van Dijk, A. I. J. M., 2024. Enhancing long-term vegetation monitoring in Australia: a new approach for harmonising the Advanced Very High Resolution Radiometer normalised-difference vegetation (NVDI) with MODIS NDVI, Earth System Science Data, Volume 16, pp. 4839-4416. https://doi.org/10.5194/essd-16-4389-2024
  • Chatzopoulos-Vouzoglanis, K., Reinke, K.J., Soto‐Berelov, M., Jones, S.D., 2024. Are fire intensity and burn severity associated? Advancing our understanding of FRP and NBR metrics from Himawari-8/9 and Sentinel-2, International Journal of Applied Earth Observation and Geoinformation, Volume 127, 2024, 103673, ISSN 1569-8432. https://doi.org/10.1016/j.jag.2024.103673
  • Chen, Y., Guerschman, J., Shendryk, Y., Henry, D., Harrison, M.T., 2021. Estimating Pasture Biomass Using Sentinel-2 Imagery and Machine Learning. Remote Sens. 2021, Vol. 13, Page 603 13, 603. https://doi.org/10.3390/RS13040603
  • Choo, J., Cherukuru, N., Lehmann, E., Paget, M., Mujahid, A., Martin, P. and Müller, M., 2022. Spatial and temporal dynamics of suspended sediment concentrations in coastal waters of the South China Sea, off Sarawak, Borneo: ocean colour remote sensing observations and analysis. Biogeosciences, 19(24), pp.5837-5857.
  • DaSilva, MD., Bruce, D., Hesp, PA., da Silva, GM., Downes, J., 2023. Post-Wildfire Coastal Dunefield Response using Photogrammetry and Satellite Indices. Earth Surf. Process. Landforms. https://doi.org/10.1002/esp.5591
  • Dunn, B., Ai, E., Alger, M.J., Fanson, B., Fickas, K.C., Krause, C.E., Lymburner, L., Nanson, R., Papas, P., Ronan, M., Thomas, R.F., 2023. Wetlands Insight Tool: Characterising the Surface Water and Vegetation Cover Dynamics of Individual Wetlands Using Multidecadal Landsat Satellite Data. Wetlands 43, 37. https://doi.org/10.1007/s13157-023-01682-7
  • Dunn, B., Lymburner, L., Newey, V., Hicks, A. and Carey, H., 2019. Developing a Tool for Wetland Characterization Using Fractional Cover, Tasseled Cap Wetness And Water Observations From Space. IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019, pp. 6095-6097. https://doi.org/10.1109/IGARSS.2019.8897806
  • Gale, M.G., Cary, G.J., van Dijk, A.I.J.M., Yebra, M., 2023. Untangling fuel, weather and management effects on fire severity: Insights from large-sample LiDAR remote sensing analysis of conditions preceding the 2019-20 Australian wildfires. Journal of Environmental Management, Volume 348, p.119474, ISSN 0301-4797. https://doi.org/10.1016/j.jenvman.2023.119474
  • Krause, C.E., Newey, V., Alger, M.J. and Lymburner, L., 2021. Mapping and monitoring the multi-decadal dynamics of Australia’s open waterbodies using Landsat. Remote Sensing, 13(8), p.1437.
  • Malan, N., Roughan, M., Hemming, M. et al. Quantifying coastal freshwater extremes during unprecedented rainfall using long timeseries multi-platform salinity observations. Nat Commun 15, 424 (2024). https://doi.org/10.1038/s41467-023-44398-2
  • Nanson, R., Bishop-Taylor, R., Sagar, S., Lymburner, L., (2022). Geomorphic insights into Australia's coastal change using a national dataset derived from the multi-decadal Landsat archive. Estuarine, Coastal and Shelf Science, 265, p.107712. Available: https://doi.org/10.1016/j.ecss.2021.107712
  • Pucino, N., Kennedy, D.M., Young, M. and Ierodiaconou, D., 2022. Assessing the accuracy of Sentinel-2 instantaneous subpixel shorelines using synchronous UAV ground truth surveys. Remote Sensing of Environment, 282, p.113293.
  • Short, M.A., Norman, R.S., Pillans, B., De Deckker, P., Usback, R., Opdyke, B.N., Ransley, T.R., Gray, S. and McPhail, D.C., 2020. Two centuries of water-level records at Lake George, NSW. Australian Journal of Earth Sciences, pp.1-20. https://www.tandfonline.com/doi/pdf/10.1080/08120099.2020.1821247
  • Sutton, A., Fisher, A., Metternicht, G. Assessing the Accuracy of Landsat Vegetation Fractional Cover for Monitoring Australian Drylands. Remote Sens. 2022, 14, 6322. https://doi.org/10.3390/rs14246322
  • Taylor, P., Almeida, A. C. D., Kemmerer, E., & de Salles Abreu, R. O. 2023. Improving spatial predictions of Eucalypt plantation growth by combining interpretable machine-learning with the 3-PG model. Frontiers in Forests and Global Change, 6, 1181049. https://doi.org/10.3389/ffgc.2023.1181049
  • Teng, J., Penton, D.J., Ticehurst, C., Sengupta, A., Freebairn, A., Marvanek, S., Vaze, J., Gibbs, M., Streeton, N., Karim, F. and Morton, S., 2022. A Comprehensive Assessment of Floodwater Depth Estimation Models in Semiarid Regions. Water Resources Research, 58(11), p.e2022WR032031.
  • Tsai, Ya-Lun & Tseng, Kuo-Hsin., 2023. Monitoring Multidecadal Coastline Change and Reconstructing Tidal Flat Topography. International Journal of Applied Earth Observation and Geoinformation, 118, 103260. https://doi.org/10.1016/j.jag.2023.103260
  • Wellington, M.J. and Renzullo, L.J., 2021. High-Dimensional Satellite Image Compositing and Statistics for Enhanced Irrigated Crop Mapping. Remote Sensing, 13(7), p.1300.
  • Wellington, M.J., Lawes, R. and Kuhnert, P., 2023. A framework for modelling spatio-temporal trends in crop production using generalised additive models. Computers and Electronics in Agriculture, 212, p.108111. https://doi.org/10.1016/j.compag.2023.108111

Conferences

  • Förtsch, S. & Hill, S., 2021, April 22 - April 23. The Bavarian Open Data Cube [Presentation]. Geopython, online.
  • Förtsch, S., Otte, I., Thiel, M., Fäth, J., Schuldt, B., Ullmann, T., 2022, May 23 - May 27. Forest intelligence - The online analytical processing cube in the context of forestry [Poster]. ESA Living Planet Symposium, Bonn, Germany. http://dx.doi.org/10.13140/RG.2.2.31623.88483
  • DaSilva, MD., Bruce, D., Hillman, M., Advancing Earth Observation Forum (AEO22), Brisbane 2022, EO360 Interactive session titled, ‘Generating an automated early warning system for Australian plantation forest health issues’

Courses and training

Creative works