A Method for Chlorophyll-a and Suspended Solids Prediction through Remote Sensing and Machine Learning

A Method for Chlorophyll-a and Suspended Solids Prediction through Remote Sensing and Machine Learning

Total Suspended Solids (TSS) and chlorophyll-a concentration are two critical parameters to monitor water quality. Since directly collecting samples for laboratory analysis can be expensive, this paper presents a methodology to estimate this information through remote sensing and Machine Learning (M...

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Bibliographic Details
Main Authors: Lucas Silveira Kupssinskü, Tainá Thomassim Guimarães, Eniuce Menezes de Souza, Daniel C. Zanotta, Mauricio Roberto Veronez, Luiz Gonzaga, Frederico Fábio Mauad
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Sensors
Subjects:
chlorophyll-a
total suspended solids
remote sensing
machine learning
artificial neural networks
random forest
Online Access:https://www.mdpi.com/1424-8220/20/7/2125

Internet

https://www.mdpi.com/1424-8220/20/7/2125

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