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Artificial Mangrove Species Mapping Using Pléiades-1: An Evaluation of Pixel-Based and Object-Based Classifications with Selected Machine Learning Algorithms.

, , , , , and . Remote Sensing, 10 (2): 294 (2018)

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Artificial Mangrove Species Mapping Using Pléiades-1: An Evaluation of Pixel-Based and Object-Based Classifications with Selected Machine Learning Algorithms., , , , , and . Remote Sensing, 10 (2): 294 (2018)Quantifying individual tree growth and tree competition using bi-temporal airborne laser scanning data: a case study in the Sierra Nevada Mountains, California., , , and . Int. J. Digit. Earth, 11 (5): 485-503 (2018)Mapping the Global Mangrove Forest Aboveground Biomass Using Multisource Remote Sensing Data., , , , , and . Remote. Sens., 12 (10): 1690 (2020)Development and Performance Evaluation of a Very Low-Cost UAV-Lidar System for Forestry Applications., , , , , , and . Remote. Sens., 13 (1): 77 (2021)The Influence of Vegetation Characteristics on Individual Tree Segmentation Methods with Airborne LiDAR Data., , , , , , , , , and 2 other author(s). Remote. Sens., 11 (23): 2880 (2019)SRTM DEM Correction in Vegetated Mountain Areas through the Integration of Spaceborne LiDAR, Airborne LiDAR, and Optical Imagery., , , and . Remote. Sens., 7 (9): 11202-11225 (2015)Efficiency of Extreme Gradient Boosting for Imbalanced Land Cover Classification Using an Extended Margin and Disagreement Performance., , , , , , and . ISPRS Int. J. Geo Inf., 8 (7): 315 (2019)The Development and Evaluation of a Backpack LiDAR System for Accurate and Efficient Forest Inventory., , , , , , , , and . IEEE Geosci. Remote. Sens. Lett., 18 (9): 1660-1664 (2021)Evaluating the Performance of Sentinel-2, Landsat 8 and Pléiades-1 in Mapping Mangrove Extent and Species., , , , , , , and . Remote Sensing, 10 (9): 1468 (2018)Loess Landslide Detection Using Object Detection Algorithms in Northwest China., , , , , , and . Remote. Sens., 14 (5): 1182 (2022)