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Incorporating Individual Tree Features into an Area-Based Approach for Estimating Forest Stock Volume

https://doi.org/10.2139/ssrn.4664227
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Random Forest Regression Model for Estimation of the Growing Stock Volumes in Georgia, USA, Using Dense Landsat Time Series and FIA Dataset
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Estimation of Individual Tree Biomass in Natural Secondary Forests Based on ALS Data and WorldView-3 Imagery
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Combining Area-Based and Individual Tree Metrics for Improving Merchantable and Non-Merchantable Wood Volume Estimates in Coastal Douglas-Fir Forests
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Forest Height Mapping Using Feature Selection and Machine Learning by Integrating Multi-Source Satellite Data in Baoding City, North China
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Mapping Forest Stock Volume Based on Growth Characteristics of Crown Using Multi-Temporal Landsat 8 OLI and ZY-3 Stereo Images in Planted Eucalyptus Forest
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Trends in Automatic Individual Tree Crown Detection and Delineation—Evolution of LiDAR Data
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The Effect of Synergistic Approaches of Features and Ensemble Learning Algorithms on Aboveground Biomass Estimation of Natural Secondary Forests Based on ALS and Landsat 8
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A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach
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Predicting forest stand variables from LiDAR data in the Great Lakes St. Lawrence forest of Ontario
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Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests
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XGBoost: A Scalable Tree Boosting System
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