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A Comparison of Imputation Approaches for Estimating Forest Biomass Using Landsat Time-Series and Inventory Data.

, , , , and . Remote Sensing, 10 (11): 1825 (2018)

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Intercomparison of Real and Simulated GEDI Observations across Sclerophyll Forests., , , and . Remote. Sens., 14 (9): 2096 (2022)Estimate Forest Biomass Dynamics Using Multi-Temporal Lidar And Single-Date Inventory Data., , , , and . IGARSS, page 7338-7341. IEEE, (2019)A New Semi-Automatic Seamless Cloud-Free Landsat Mosaicing Approach Tracks Forest Change Over Large Extents., , , , , and . IGARSS, page 4954-4957. IEEE, (2018)A satellite data driven approach to monitoring and reporting fire disturbance and recovery across boreal and temperate forests., , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2020)Monitoring aboveground forest biomass dynamics over three decades using Landsat time-series and single-date inventory data., , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2020)A reference data framework for the application of satellite time series to monitor forest disturbance., , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2021)A Comparison of Imputation Approaches for Estimating Forest Biomass Using Landsat Time-Series and Inventory Data., , , , and . Remote Sensing, 10 (11): 1825 (2018)Landsat Time-Series for Estimating Forest Aboveground Biomass and Its Dynamics across Space and Time: A Review., , , , and . Remote Sensing, 12 (1): 98 (2020)Using Landsat time series and bi-temporal GEDI to compare spectral and structural vegetation responses after fire., , , and . Int. J. Appl. Earth Obs. Geoinformation, (August 2023)Using Landsat Spectral Indices in Time-Series to Assess Wildfire Disturbance and Recovery., , , , , and . Remote Sensing, 10 (3): 460 (2018)