Integrating remote sensing and machine learning to detect turbidity anomalies in hydroelectric reservoirs-Reference-Cited by-同舟云学术

Integrating remote sensing and machine learning to detect turbidity anomalies in hydroelectric reservoirs

Published:2023-12 Issue: Volume:902 Page:165964
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Souza Anderson P.,Oliveira Bruno A.,Andrade Mauren L.,Starling Maria Clara V.M.,Pereira Alexandre H.,Maillard Philippe,Nogueira Keiller,dos Santos Jefersson A.,Amorim Camila C.

Funder

Companhia Energética de Minas Gerais SA

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference97 articles.

1. Beginning Anomaly Detection Using Python-based Deep Learning;Alla,2019

2. Fragmentation of Andes-to-Amazon connectivity by hydropower dams;Anderson;Sci. Adv.,2018

3. Identification of seasonal variation of water turbidity using NDTI method in Panchet Hill Dam, India;Bid;Model. Earth Syst. Environ.,2019

4. Remote sensing of the water quality parameters for a shallow dam reservoir;Bielski;Appl. Sci.,2022

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