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Central Europe",
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@article{bb259903,
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profiles from discrete return airborne lidar",
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@article{bb259905,
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@article{bb259906,
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@article{bb259907,
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@article{bb259908,
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@article{bb259909,
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forest inventory",
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address the old challenges associated with forest inventories",
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@article{bb259911,
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@article{bb259912,
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Vegetation Height Estimation in Tropical Forests of Mexico",
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        NUMBER = "8",
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@article{bb259913,
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Reconstruction Based on Combined RTK and CCD Continuous Photography",
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@article{bb259914,
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        TITLE = "Forest Variable Estimation Using a High Altitude Single Photon Lidar
System",
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        NUMBER = "9",
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@article{bb259915,
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        TITLE = "Augmentation of Traditional Forest Inventory and Airborne Laser
Scanning with Unmanned Aerial Systems and Photogrammetry for Forest
Monitoring",
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@article{bb259916,
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Using MISR-HR and LiDAR Remote Sensing Data",
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        NUMBER = "10",
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@article{bb259917,
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Imagery on the Accuracy of Canopy Height Models over Forested Alpine
Regions",
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        NUMBER = "10",
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@article{bb259918,
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Ginkgo plantations",
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@article{bb259919,
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Airborne Lidar: Leaf Area Profile Sensitivity to Pulse Density and
Spatial Sampling",
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        NUMBER = "1",
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@article{bb259920,
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Forests Using Lidar-Derived Structural Profiles and Species
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@article{bb259921,
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        TITLE = "A Comparison of Standard Modeling Techniques Using Digital Aerial
Imagery with National Elevation Datasets and Airborne LiDAR to
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        NUMBER = "1",
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@article{bb259922,
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@article{bb259923,
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@article{bb259924,
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@article{bb259925,
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@article{bb259926,
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@article{bb259927,
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Estimating Forest Variables in a Mountain Environment",
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@article{bb259928,
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@article{bb259929,
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Aerial Imagery, and Harvester Data",
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@article{bb259930,
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        NUMBER = "7",
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@article{bb259931,
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@article{bb259932,
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Different Spatial Aggregation Levels in Northern California using
Multitemporal LiDAR",
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        NUMBER = "8",
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@article{bb259933,
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@article{bb259934,
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Photon Cloud Data in Forest Area",
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@article{bb259935,
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Resolution Satellite and Environmental Data",
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@article{bb259936,
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@article{bb259938,
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Airborne Light Detection and Ranging (LiDAR):
A Case Study of Cheonan, South Korea",
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@article{bb259939,
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@article{bb259940,
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Stand and Ecological Variables from Airborne LiDAR Data in Central
European Forests",
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@article{bb259941,
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@article{bb259942,
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@article{bb259943,
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@article{bb259944,
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@article{bb259945,
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@article{bb259946,
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a Deciduous Forest Using Small-Footprint Airborne LiDAR Data",
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@article{bb259947,
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@article{bb259948,
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@article{bb259951,
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@article{bb259952,
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@article{bb259953,
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@article{bb259954,
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@article{bb259955,
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@article{bb259956,
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@article{bb259957,
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@article{bb259958,
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LiDAR-Derived DTM and on Forest Attribute Estimation through
Area-Based Approach",
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@article{bb259959,
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LiDAR-Landsat Covariance",
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@article{bb259960,
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from 360° Spherical Camera Using YOLO v2",
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@article{bb259961,
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A Drone-Based Image Point Cloud Digital Surface Model",
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@article{bb259962,
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@article{bb259963,
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        TITLE = "Improved Supervised Learning-Based Approach for Leaf and Wood
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@article{bb259964,
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@article{bb259965,
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@article{bb259966,
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@article{bb259967,
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@article{bb259968,
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@article{bb259969,
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@article{bb259971,
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@article{bb259972,
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@article{bb259973,
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@article{bb259975,
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@article{bb259977,
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@article{bb259978,
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@article{bb259979,
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@article{bb259980,
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@article{bb259981,
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@article{bb259982,
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@article{bb259983,
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@article{bb259984,
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@article{bb259985,
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@article{bb259986,
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@article{bb259988,
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@article{bb259990,
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@article{bb259991,
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@article{bb259994,
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@article{bb259995,
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Last update:Jan 13, 2022 at 22:02:22