Dominant Tree Species Mapping Using Machine Learning Based on Multi-Temporal and Multi-Source Data

Dominant Tree Species Mapping Using Machine Learning Based on Multi-Temporal and Multi-Source Data

Timely and accurate tree species mapping is crucial for forest resource inventory, supporting management, conservation biology, and ecological restoration. This study utilized Sentinel-1 and Sentinel-2 data to classify five dominant tree species in Chengde and Beijing. To effectively capture the inf...

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Main Authors: Heyi Guo, Sornkitja Boonprong, Shaohua Wang, Zhidong Zhang, Wei Liang, Min Xu, Xinwei Yang, Kaimin Wang, Jingbo Li, Xiaotong Gao, Yujie Yang, Ruichen Hu, Yu Zhang, Chunxiang Cao
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Remote Sensing
Subjects:
tree species
sentinel-1/2
random forest, XGBoost
deep learning
large scale mapping
Online Access:https://www.mdpi.com/2072-4292/16/24/4674
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