Potential of Sample Migration and Explainable Machine Learning Model for Monitoring Spatiotemporal Changes of Wetland Plant Communities-Reference-Cited by-同舟云学术

Potential of Sample Migration and Explainable Machine Learning Model for Monitoring Spatiotemporal Changes of Wetland Plant Communities

Published:2024 Issue: Volume:17 Page:9894-9906
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Feng Kaidong¹^ORCID,Mao Dehua¹^ORCID,Zhen Jianing¹^ORCID,Pu Haiguang¹,Yan Hengqi²,Wang Ming¹,Wang Duanrui¹,Xiang Hengxing¹,Ren Yongxing¹^ORCID,Luo Ling¹,Wang Zongming¹

Affiliation:

1. State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China

2. Jilin Earthquake Agency, Changchun, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jilin Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10529504.pdf?arnumber=10529504

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4. Remote sensing of plant communities as a tool for assessing the condition of semiarid Mediterranean saline wetlands in agricultural catchments

5. Remote Sensing of Wetlands