Deep Learning with WASI Simulation Data for Estimating Chlorophyll <i>a</i> Concentration of Inland Water Bodies

Deep Learning with WASI Simulation Data for Estimating Chlorophyll <i>a</i> Concentration of Inland Water Bodies

Information about the chlorophyll <i>a</i> concentration of inland water bodies is essential for water monitoring. This study focuses on estimating chlorophyll <i>a</i> with remote sensing data, and machine learning (ML) approaches on the real-world SpecWa dataset. We adapt a...

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Bibliographic Details
Main Authors: Philipp M. Maier, Sina Keller, Stefan Hinz
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Remote Sensing
Subjects:
machine learning
regression
CNN
artificial neural network
radiative transfer model
WASI
Online Access:https://www.mdpi.com/2072-4292/13/4/718

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