Forest Vertical Structure Mapping Using Two-Seasonal Optic Images and LiDAR DSM Acquired from UAV Platform through Random Forest, XGBoost, and Support Vector Machine Approaches

Forest Vertical Structure Mapping Using Two-Seasonal Optic Images and LiDAR DSM Acquired from UAV Platform through Random Forest, XGBoost, and Support Vector Machine Approaches

Research on the forest structure classification is essential, as it plays an important role in assessing the vitality and diversity of vegetation. However, classifying forest structure involves in situ surveying, which requires considerable time and money, and cannot be conducted directly in some in...

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Bibliographic Details
Main Authors: Jin-Woo Yu, Young-Woong Yoon, Won-Kyung Baek, Hyung-Sup Jung
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Remote Sensing
Subjects:
forest vertical structure
multiseason
machine learning
classification
Online Access:https://www.mdpi.com/2072-4292/13/21/4282

Internet

https://www.mdpi.com/2072-4292/13/21/4282

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