Mapping Water Clarity in Small Oligotrophic Lakes Using Sentinel-2 Imagery and Machine Learning Methods: A Case Study of Canandaigua Lake in Finger Lakes, New York

Mapping Water Clarity in Small Oligotrophic Lakes Using Sentinel-2 Imagery and Machine Learning Methods: A Case Study of Canandaigua Lake in Finger Lakes, New York

Optical remote sensing of water quality poses challenges in small oligotrophic lakes due to the diminishing contribution of constituents to the water-leaving radiance as water clarity increases. For monitoring water clarity over such lakes, this study utilizes machine learning models and data from c...

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Bibliographic Details
Main Authors: Rabia Munsaf Khan, Bahram Salehi, Milad Niroumand-Jadidi, Masoud Mahdianpari
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Freshwater
machine learning (ML)
oligotrophic lakes
random forest (RF)
remote sensing
Secchi disk depth (SDD)
Online Access:https://ieeexplore.ieee.org/document/10416331/

Internet

https://ieeexplore.ieee.org/document/10416331/

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