Application of machine-learning methods in forest ecology: recent progress and future challenges

@inproceedings{Liu2018ApplicationOM,
  title={Application of machine-learning methods in forest ecology: recent progress and future challenges},
  author={Zelin Liu and Changhui PengC. Peng and Timothy T. Work and J. Candau and Annie DesRochers and Daniel Kneeshaw},
  year={2018}
}
Machine learning, an important branch of artificial intelligence, is increasingly being applied in sciences such as forest ecology. Here, we review and discuss three commonly used methods of machine learning (ML) including decision-tree learning, artificial neural network, and support vector machine and their applications in four different aspects of forest ecology over the last decade. These applications include: (i) species distribution models, (ii) carbon cycles, (iii) hazard assessment and… CONTINUE READING

Similar Papers