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European Journal of Remote Sensing Volume 57, 2024 - Issue 1
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Research Article

Predictions of Spartina alterniflora leaf functional traits based on hyperspectral data and machine learning models

Wei Lia Institute of Wetland Research, Chinese Academy of Forestry, Beijing Key Laboratory of Wetland Services and Restoration, Beijing, China;b Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, ChinaView further author information
,
Xueyan Zuoa Institute of Wetland Research, Chinese Academy of Forestry, Beijing Key Laboratory of Wetland Services and Restoration, Beijing, China;b Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, ChinaView further author information
,
Zhijun Liua Institute of Wetland Research, Chinese Academy of Forestry, Beijing Key Laboratory of Wetland Services and Restoration, Beijing, China;b Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, ChinaView further author information
,
Leichao Niea Institute of Wetland Research, Chinese Academy of Forestry, Beijing Key Laboratory of Wetland Services and Restoration, Beijing, China;b Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, ChinaView further author information
,
Huazhe Lia Institute of Wetland Research, Chinese Academy of Forestry, Beijing Key Laboratory of Wetland Services and Restoration, Beijing, China;b Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, ChinaView further author information
,
Junjie Wangc College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, ChinaView further author information
,
Zhiguo Doua Institute of Wetland Research, Chinese Academy of Forestry, Beijing Key Laboratory of Wetland Services and Restoration, Beijing, China;b Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, ChinaView further author information
,
Yang Caia Institute of Wetland Research, Chinese Academy of Forestry, Beijing Key Laboratory of Wetland Services and Restoration, Beijing, China;b Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, ChinaView further author information
,
Xiajie Zhaia Institute of Wetland Research, Chinese Academy of Forestry, Beijing Key Laboratory of Wetland Services and Restoration, Beijing, China;b Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, ChinaView further author information
&
Lijuan Cuia Institute of Wetland Research, Chinese Academy of Forestry, Beijing Key Laboratory of Wetland Services and Restoration, Beijing, China;b Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, ChinaCorrespondence[email protected]
View further author information
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Article: 2294951 | Received 26 Jul 2023, Accepted 09 Dec 2023, Published online: 22 Dec 2023

References

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