Dataset Information

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

ABSTRACT: 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 (ML) techniques. TSS and chlorophyll-a are optically active components, therefore enabling measurement by remote sensing. Two study cases in distinct water bodies are performed, and those cases use different spatial resolution data from Sentinel-2 spectral images and unmanned aerial vehicles together with laboratory analysis data. In consonance with the methodology, supervised ML algorithms are trained to predict the concentration of TSS and chlorophyll-a. The predictions are evaluated separately in both study areas, where both TSS and chlorophyll-a models achieved R-squared values above 0.8.

SUBMITTER: Silveira Kupssinsku L

PROVIDER: S-EPMC7181123 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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

Silveira Kupssinskü Lucas L Thomassim Guimarães Tainá T Menezes de Souza Eniuce E C Zanotta Daniel D Roberto Veronez Mauricio M Gonzaga Luiz L Mauad Frederico Fábio FF

Sensors (Basel, Switzerland) 20200409 7

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 (ML) techniques. TSS and chlorophyll-a are optically active components, therefore enabling measurement by remote sensing. Two study cases in distinct water bodies are performed, and those cases use diff ...[more]

PMID: 32283787

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Dataset Information

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

Publications

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

Similar Datasets

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