Remote sensing water quality inversion using sparse representation: Chlorophyll-a retrieval from Sentinel-2 MSI data
Author:
Funder
Ministry of Science and Technology, Taiwan
Environmental Protection Agency
Publisher
Elsevier BV
Subject
Computers in Earth Sciences,Geography, Planning and Development
Reference38 articles.
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3. Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations;Beck;Rem. Sens. Environ.,2016
4. Data-driven Science and Engineering: Machine Learning, Dynamical Systems, and Control;Brunton,2022
5. Robust flow reconstruction from limited measurements via sparse representation;Callaham;Physical Review Fluids,2019
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