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Remote Sensing
Volume 17
Issue 24
10.3390/rs17244044
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Systematic Review

Nutrient and Dissolved Oxygen (DO) Estimation Using Remote Sensing Techniques: A Literature Review

by
Androniki Dimoudi
1,*,
Christos Domenikiotis
1,
Dimitris Vafidis
1,
Giorgos Mallinis
2 and
Nikos Neofitou
1
1
Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, 38446 Volos, Greece
2
School of Rural and Surveying Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(24), 4044; https://doi.org/10.3390/rs17244044
Submission received: 5 November 2025 / Revised: 10 December 2025 / Accepted: 11 December 2025 / Published: 16 December 2025
(This article belongs to the Special Issue Remote Sensing and Geophysical Tools for Land and Water System Analysis)
Versions Notes

Abstract

Eutrophication has emerged as a critical threat to water quality degradation and ecosystem health on a global scale, calling for prompt management actions. Remote sensing enables the monitoring of eutrophication by detected changes in ocean color caused by fluctuations in chlorophyll a (chl a). Although chl a is a crucial indicator of phytoplankton biomass and nutrient overloading, it reflects the outcome of eutrophication rather than its cause. Nutrients, the primary “drivers” of eutrophication, are essential indicators for predicting the potential phytoplankton growth in water bodies, allowing adoption of effective preventive measures. Long-term monitoring of nutrients combined with multiple water quality indicators using remotely sensed data could lead to a more precise assessment of the trophic state. Retrieving non-optically active constituents, such as nutri
Keywords: remote sensing; water quality monitoring; eutrophication; nutrients; dissolved oxygen; case II waters; empirical models; machine learning; deep learning remote sensing; water quality monitoring; eutrophication; nutrients; dissolved oxygen; case II waters; empirical models; machine learning; deep learning

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MDPI and ACS Style

Dimoudi, A.; Domenikiotis, C.; Vafidis, D.; Mallinis, G.; Neofitou, N. Nutrient and Dissolved Oxygen (DO) Estimation Using Remote Sensing Techniques: A Literature Review. Remote Sens. 2025, 17, 4044. https://doi.org/10.3390/rs17244044

AMA Style

Dimoudi A, Domenikiotis C, Vafidis D, Mallinis G, Neofitou N. Nutrient and Dissolved Oxygen (DO) Estimation Using Remote Sensing Techniques: A Literature Review. Remote Sensing. 2025; 17(24):4044. https://doi.org/10.3390/rs17244044

Chicago/Turabian Style

Dimoudi, Androniki, Christos Domenikiotis, Dimitris Vafidis, Giorgos Mallinis, and Nikos Neofitou. 2025. "Nutrient and Dissolved Oxygen (DO) Estimation Using Remote Sensing Techniques: A Literature Review" Remote Sensing 17, no. 24: 4044. https://doi.org/10.3390/rs17244044

APA Style

Dimoudi, A., Domenikiotis, C., Vafidis, D., Mallinis, G., & Neofitou, N. (2025). Nutrient and Dissolved Oxygen (DO) Estimation Using Remote Sensing Techniques: A Literature Review. Remote Sensing, 17(24), 4044. https://doi.org/10.3390/rs17244044

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