Near real-time retrieval of lake surface water temperature using Himawari-8 satellite imagery and machine learning techniques: a case study in the Yangtze River Basin

Near real-time retrieval of lake surface water temperature using Himawari-8 satellite imagery and machine learning techniques: a case study in the Yangtze River Basin

Lake Surface Water Temperature (LSWT) is essential for understanding and regulating various processes in lake ecosystems. Remote sensing for large-scale aquatic monitoring offers valuable insights, but its limitations call for a dynamic LSWT monitoring model. This study developed multiple machine le...

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Bibliographic Details
Main Authors: Kaifang Shi, Jing-Cheng Han, Peng Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Environmental Science
Subjects:
water quality
remote sensing retrieval
synchronous Satellite
LSWT
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fenvs.2023.1335725/full

Internet

https://www.frontiersin.org/articles/10.3389/fenvs.2023.1335725/full

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