Lake Surface Temperature Predictions under Different Climate Scenarios with Machine Learning Methods: A Case Study of Qinghai Lake and Hulun Lake, China

Lake Surface Temperature Predictions under Different Climate Scenarios with Machine Learning Methods: A Case Study of Qinghai Lake and Hulun Lake, China

Accurate prediction of lake surface water temperature (LSWT) is essential for understanding the impacts of climate change on aquatic ecosystems and for guiding environmental management strategies. Predictions of LSWT for two prominent lakes in northern China, Qinghai Lake and Hulun Lake, under vario...

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Bibliografiske detaljer
Main Authors: Zhenghao Li, Zhijie Zhang, Shengqing Xiong, Wanchang Zhang, Rui Li
Format: Article
Sprog:English
Udgivet: MDPI AG 2024-08-01
Serier:Remote Sensing
Fag:
lake surface water temperature prediction
machine learning
Random Forest
climate change
Online adgang:https://www.mdpi.com/2072-4292/16/17/3220

Internet

https://www.mdpi.com/2072-4292/16/17/3220

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