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Sub-Compartment Variation in Tree Height, Stem Diameter and Stocking in a Pinus radiata D. Don Plantation Examined Using Airborne LiDAR Data.

, , , , and . Remote. Sens., 6 (8): 7592-7609 (2014)

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Sub-Compartment Variation in Tree Height, Stem Diameter and Stocking in a Pinus radiata D. Don Plantation Examined Using Airborne LiDAR Data., , , , and . Remote. Sens., 6 (8): 7592-7609 (2014)Predicting Sphaeropsis sapinea damage on Pinus radiata stands from CASI-2 using spectral mixture analysis., , and . IGARSS, page 1007-1012. IEEE, (2004)A Comparison of ALS and Dense Photogrammetric Point Clouds for Individual Tree Detection in Radiata Pine Plantations., , , and . Remote. Sens., 13 (17): 3536 (2021)Automated Mapping of Woody Debris over Harvested Forest Plantations Using UAVs, High-Resolution Imagery, and Machine Learning., , , , and . Remote Sensing, 11 (6): 733 (2019)A comparison of area-based forest attributes derived from airborne laser scanner, small-format and medium-format digital aerial photography., , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2019)The Potential of Sentinel Satellites for Large Area Aboveground Forest Biomass Mapping., , and . IGARSS, page 9030-9033. IEEE, (2018)Comparison of models describing forest inventory attributes using standard and voxel-based lidar predictors across a range of pulse densities., , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2019)A reference data framework for the application of satellite time series to monitor forest disturbance., , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2021)The Performance of Random Forests in an Operational Setting for Large Area Sclerophyll Forest Classification., , , and . Remote Sensing, 5 (6): 2838-2856 (2013)