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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 and Hicks A (2021) 'DEA Notebooks contributors', Digital Earth Australia notebooks and tools repository, Geoscience Australia, Canberra. doi.org/10.26186/145234.

Scientific papers

  • Abhik S, Hope P, Hendon HH, Hutley LB, Johnson S, Drosdowsky W and Brown J (2021) 'Influence of 2015-16 El Niño on the record-breaking mangrove dieback along northern Australia coast', Scientific Reports, 11, 20411, doi.org/10.1038/s41598-021-99313-w.
  • Bishop-Taylor R, Nanson R, Sagar S and Lymburner L (2021) 'Mapping Australia's dynamic coastline at mean sea level using three decades of Landsat imagery', Remote Sensing of Environment, 267, 112734, 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):2984, doi.org/10.3390/rs11242984.
  • Burton CA, Rifai SW, Renzullo LJ and Van Dijk AIJM (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, 16, 4839-4416, doi.org/10.5194/essd-16-4389-2024.
  • Chatzopoulos-Vouzoglanis K, Reinke KJ, Soto‐Berelov M and Jones SD (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, 127, 103673, doi.org/10.1016/j.jag.2024.103673.
  • Chen Y, Guerschman J, Shendryk Y, Henry D and Harrison MT (2021), 'Estimating pasture biomass using Sentinel-2 imagery and machine learning', Remote Sensing, 13, 603, 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):5837-5857, doi.org/10.5194/bg-19-5837-2022.
  • DaSilva MD, Bruce D, Hesp PA, da Silva GM, and Downes J (2023) 'Post-wildfire coastal dunefield response using photogrammetry and satellite indices', Earth Surface Processes and Landforms, 48(9):1845-1868, doi.org/10.1002/esp.5591.
  • Dunn B, Ai E, Alger MJ, Fanson B, Fickas KC, Krause CE, Lymburner L, Nanson R, Papas P, Ronan M and Thomas RF (2023) 'Wetlands Insight Tool: characterising the surface water and vegetation cover dynamics of individual wetlands using multidecadal Landsat satellite data', Wetlands, 43(37), doi.org/10.1007/s13157-023-01682-7.
  • Dunn B, Lymburner L, Newey V, Hicks A and Carey H (28 July - 2 August 2019) 'Developing a tool for wetland characterization using fractional cover, tasseled cap wetness and water observations from space', [conference presentation], IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 6095-6097, doi.org/10.1109/IGARSS.2019.8897806.
  • Gale MG, Cary GJ, van Dijk AIJM and 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, 348, 119474, doi.org/10.1016/j.jenvman.2023.119474.
  • Krause CE, Newey V, Alger MJ and Lymburner L (2021) 'Mapping and monitoring the multi-decadal dynamics of Australia’s open waterbodies using Landsat', Remote Sensing, 13(8):1437, doi.org/10.3390/rs13081437.
  • Malan N, Roughan M, Hemming M and Ingleton T (2024) 'Quantifying coastal freshwater extremes during unprecedented rainfall using long timeseries multi-platform salinity observations', Nature Communications, 15, 424, doi.org/10.1038/s41467-023-44398-2.
  • Nanson R, Bishop-Taylor R, Sagar S and 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, 107712. doi.org/10.1016/j.ecss.2021.107712.
  • Ochungo P, Sagna N, Neema V, Akintayo A, Athie A, Kabiru A, Ndiaye A, Michaut E, Merlo S and Lane P (2025) 'Shoreline dynamics and cultural heritage sites in Kenya, Tanzania, and Senegal: integrating remote sensing and archaeological knowledge', Journal of Maps, 21(1):2487454, doi.org/10.1080/17445647.2025.2487454.
  • Pucino N, Kennedy DM, 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, 113293, doi.org/10.1016/j.rse.2022.113293.
  • Short MA, Norman RS, Pillans B, De Deckker P, Usback R, Opdyke BN, Ransley TR, Gray S and McPhail DC (2020) 'Two centuries of water-level records at Lake George, NSW', Australian Journal of Earth Sciences, 68(4):453-472, doi.org/10.1080/08120099.2020.1821247.
  • Sutton A, Fisher A and Metternicht G (2022) 'Assessing the accuracy of Landsat vegetation fractional cover for monitoring Australian drylands', Remote Sensing', 14(24):6322. doi.org/10.3390/rs14246322.
  • Taylor P, Almeida ACD, Kemmerer E and de Salles Abreu RO (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, doi.org/10.3389/ffgc.2023.1181049.
  • Teng J, Penton DJ, 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):e2022WR032031, doi.org/10.1029/2022WR032031.
  • Tsai YLS and Tseng KH (2023), 'Monitoring multidecadal coastline change and reconstructing tidal flat topography', International Journal of Applied Earth Observation and Geoinformation, 118, 103260, doi.org/10.1016/j.jag.2023.103260.
  • Wellington MJ, 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, 108111. doi.org/10.1016/j.compag.2023.108111.
  • Wellington MJ and Renzullo LJ (2021) 'High-dimensional satellite image compositing and statistics for enhanced irrigated crop mapping', Remote Sensing, 13(7):1300, doi.org/10.3390/rs13071300.

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