Estimation of water quality variables based on machine learning model and cluster analysis-based empirical model using multi-source remote sensing data in inland reservoirs, South China

Reservoirs play important roles in the drinking water supply for urban residents, agricultural water provision, and the maintenance of ecosystem health. Satellite optical remote sensing of water quality variables in medium and micro-sized inland waters under oligotrophic and mesotrophic status is ch...

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Veröffentlicht in:	Environmental pollution (1987) Jg. 342; S. 123104
Hauptverfasser:	Tian, Di, Zhao, Xinfeng, Gao, Lei, Liang, Zuobing, Yang, Zaizhi, Zhang, Pengcheng, Wu, Qirui, Ren, Kun, Li, Rui, Yang, Chenchen, Li, Shaoheng, Wang, Meng, He, Zhidong, Zhang, Zebin, Chen, Jianyao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Elsevier Ltd 01.02.2024
Schlagworte:	Band combination model Clustering algorithm Inland water quality monitoring Machine learning Multi-source remote sensing Band combination model Inland water quality monitoring Multi-source remote sensing Clustering algorithm Machine learning
ISSN:	0269-7491, 1873-6424, 1873-6424
Online-Zugang:	Volltext
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