Status, advancements and prospects of deep learning methods applied in forest studies

Yun, Ting; Li, Jian; Ma, Lingfei; Zhou, Ji; Wang, Ruisheng; Eichhorn, Markus P.; Zhang, Huaiqing

doi:10.1016/j.jag.2024.103938

International Journal of Applied Earth Observation and Geoinfor

2024

DOI: 10.1016/j.jag.2024.103938

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Status, advancements and prospects of deep learning methods applied in forest studies

Ting Yun,

Jian Li,

Lingfei Ma

et al.

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Cited by 9 publications

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Status, advancements and prospects of deep learning methods applied in forest studies

Cited by 9 publications

References 103 publications

Potential of hyperspectral LiDAR in individual tree segmentation: a comparative study with multispectral LiDAR

Potential of hyperspectral LiDAR in individual tree segmentation: a comparative study with multispectral LiDAR

TreegrowNet: a completion network for incomplete single tree point cloud from TLS

Forecasting Precipitation and Temperature Evolution Patterns Under Climate Change Using a Random Forest Approach With Seasonal Bias Correction

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