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October 23, 2025Remote SensingOpen Access

Evaluation of Atmospheric Preprocessing Methods and Chlorophyll Algorithms for Sentinel-2 Imagery in Coastal Waters

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Authors

TWTori WoltersNDNaomi E. DetenbeckSRSteven A. Rego

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Overview

Comparative analysis reveals remote sensing methods improve chlorophyll-a mapping in Chesapeake Bay, highlighting machine learning algorithms' efficacy.

Key Points

  • Machine learning algorithms enhanced chlorophyll-a mapping effectiveness in coastal waters, indicating improved monitoring of algal blooms.
  • The comparison found significant results between different atmospheric preprocessing methods and remote sensing techniques.
  • Observations in the Chesapeake Bay featured a focus on turbidity and chlorophyll-a levels, crucial for monitoring aquatic health.
  • This study highlights potential avenues for better detection of harmful algal blooms through refined remote sensing methods.

Cite This Study

Wolters et al. (2025) studied this question.

synapsesocial.com/papers/68f9f86eb2c35e10cc4e3e36https://doi.org/10.3390/rs17203503
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