Monitoring Water Quality of Valle de Bravo Reservoir, Mexico, Using Entire Lifespan of MERIS Data and Machine Learning Approaches

Monitoring Water Quality of Valle de Bravo Reservoir, Mexico, Using Entire Lifespan of MERIS Data and Machine Learning Approaches

Remote-sensing-based machine learning approaches for water quality parameters estimation, Secchi Disk Depth (SDD) and Turbidity, were developed for the Valle de Bravo reservoir in central Mexico. This waterbody is a multipurpose reservoir, which provides drinking water to the metropolitan area of Me...

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Bibliographic Details
Main Authors: Leonardo F. Arias-Rodriguez, Zheng Duan, Rodrigo Sepúlveda, Sergio I. Martinez-Martinez, Markus Disse
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
turbidity
secchi disk depth
trophic state
remote sensing
gaussian processes regression
support vector machines
Online Access:https://www.mdpi.com/2072-4292/12/10/1586

Internet

https://www.mdpi.com/2072-4292/12/10/1586

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