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Applying machine learning methods and time series analysis to create a National Dynamic Land Cover Dataset for Australia.

, , , , , and . IGARSS, page 4289-4292. IEEE, (2013)

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Atmospheric Correction and Water Surface Issues for Aquatic Applications of Landsat 8., , , and . IGARSS, page 6899-6902. IEEE, (2019)Atmospheric Correction Inter-Comparison Exercise., , , , , , , , , and 5 other author(s). Remote. Sens., 10 (2): 352 (2018)Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans, , , , , , , and . Remote Sensing of Environment, 92 (4): 475--482 (September 2004)Mapping land surface fluxes using microwave and optical remote sensing data under high vegetation cover conditions during SMEX02/SMACEX., , , , and . IGARSS, page 4285-4288. IEEE, (2004)Utility of remote sensing based two-source energy balance model to estimate land surface fluxes during SMACEX., , , and . IGARSS, page 1327-1330. IEEE, (2004)The variability of satellite derived surface BRDF shape over Australia from 2001 to 2011., , , , , and . IGARSS, page 255-258. IEEE, (2013)MODTRAN®61 Generated Single Scattering Adjacency Function., , and . IGARSS, page 6678-6681. IEEE, (2020)Creating multi-sensor time series using data from Landsat-5 TM and Landsat-7 ETM+ to characterise vegetation dynamics., , , , , and . IGARSS, page 961-963. IEEE, (2013)Analysis Ready Data Sensitivity Analyses., , , , , and . IGARSS, page 5642-5645. IEEE, (2019)Effect of remote sensing spatial resolution on interpreting tower-based flux observations, , , , and . Remote Sensing of Environment, 112 (2): 337--349 (2008)