Landsat-based spatiotemporal estimation of subtropical forest aboveground carbon storage using machine learning algorithms with hyperparameter tuning
This study provided a set of effective hyperparameters and model of machine learning suitable for subtropical forests and a reference data for improving carbon sequestration capacity of subtropical forests in Lishui City.
Authors
- Huaqiang Du (ORCID: https://orcid.org/0000-0002-6765-2279)
- Fangjie Mao (ORCID: https://orcid.org/0000-0003-2005-3452)
- Zihao Huang (ORCID: https://orcid.org/0000-0002-7443-6515)
- Lei Huang (ORCID: https://orcid.org/0000-0002-7889-6121)
- Weilong Zhou (ORCID: https://orcid.org/0009-0003-5998-2045)
- Yinyin Zhao
- Jiacong Yu
- Su‐Mei Wu (ORCID: https://orcid.org/0009-0005-8704-6419)
- Xuejian Li
- Meixuan Song
- Lujin Lv
Institutions
- Zhejiang A & F University (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2024-08-29
- DOI
- https://doi.org/10.3389/fpls.2024.1421567
- Citations
- 15
- Primary Topic
- Remote Sensing and LiDAR Applications
- Type
- article
- Field-Weighted Citation Impact
- 3.09