期刊名：Remote Sensing

期刊主页：https://www.mdpi.com/journal/remotesensing?n1=43&_utm_from=315ffb84f5

水色遥感能够提供海洋中叶绿素浓度、悬浮物含量等重要信息，对于监测海洋污染、赤潮、水质等环境问题至关重要。本期文献清单精选了15篇“海洋光学及水色遥感”相关论文，希望能给相关研究人员带来一些参考和启发。

1.

英文标题:

A Review of Machine Learning Applications in Ocean Color Remote Sensing

中文标题:

机器学习在海洋水色遥感中的应用综述

文章链接：https://www.mdpi.com/2072-4292/17/10/1776

MDPI引用格式:

Zhang, Z.; Chen, P.; Zhang, S.; Huang, H.; Pan, Y.; Pan, D. A Review of Machine Learning Applications in Ocean Color Remote Sensing. Remote Sens. 2025, 17, 1776. https://doi.org/10.3390/rs17101776

2.

英文标题：Impact of the Uncertainties of Polarized Water-Leaving Radiance on the Retrieval of Oceanic Constituents and Inherent Optical Properties in Global Oceans via Multiangle Polarimetric Observations

中文标题：偏振水体反射辐射的不确定性对全球海洋中海洋组分及固有光学性质反演的影响：基于多角度偏振观测的研究

文章链接：https://www.mdpi.com/2072-4292/17/7/1148

MDPI引用格式：Liu, J.; Li, C.; He, X.; Chen, T.; Jia, X.; Bai, Y.; Liu, D.; Qu, B.; Wang, Y.; Feng, X.; et al. Impact of the Uncertainties of Polarized Water-Leaving Radiance on the Retrieval of Oceanic Constituents and Inherent Optical Properties in Global Oceans via Multiangle Polarimetric Observations. Remote Sens. 2025, 17, 1148. https://doi.org/10.3390/rs17071148

3.

英文标题：Prediction of Sea Surface Chlorophyll-a Concentrations by Remote Sensing and Deep Learning

中文标题：基于遥感与深度学习的海洋表面叶绿素-a浓度预测

文章链接：https://www.mdpi.com/2072-4292/17/10/1755

MDPI引用格式：Ruan, Q.; Pan, D.; Wang, D.; He, X.; Gong, F.; Tian, Q. Prediction of Sea Surface Chlorophyll-a Concentrations by Remote Sensing and Deep Learning. Remote Sens. 2025, 17, 1755. https://doi.org/10.3390/rs17101755

4.

英文标题：How Representative Are European AERONET-OC Sites of European Marine Waters?

中文标题：欧洲AERONET-OC站点在欧洲海域中的代表性如何？

文章链接：https://www.mdpi.com/2072-4292/16/10/1793

MDPI引用格式：Cazzaniga, I.; Mélin, F. How Representative Are European AERONET-OC Sites of European Marine Waters? Remote Sens. 2024, 16, 1793. https://doi.org/10.3390/rs16101793

5.

英文标题：Bio-Optical Properties and Ocean Colour Satellite Retrieval along the Coastal Waters of the Western Iberian Coast (WIC)

中文标题：西伊比利亚海岸（WIC）沿岸海域的生物光学特性与海洋颜色卫星反演

文章链接：https://www.mdpi.com/2072-4292/16/18/3440

MDPI引用格式：

Favareto, L.; Rudorff, N.; Brotas, V.; Tracana, A.; Sá, C.; Palma, C.; Brito, A.C. Bio-Optical Properties and Ocean Colour Satellite Retrieval along the Coastal Waters of the Western Iberian Coast (WIC). Remote Sens. 2024, 16, 3440. https://doi.org/10.3390/rs16183440

6.

英文标题：Evaluating MULTIOBS Chlorophyll-a with Ground-Truth Observations in the Eastern Mediterranean Sea

中文标题：利用实地观测数据评估东地中海海域的MULTIOBS 叶绿素-a含量

文章链接：https://www.mdpi.com/2072-4292/16/24/4705

MDPI引用格式：Livanou, E.; Sauzède, R.; Psarra, S.; Mandalakis, M.; Dall’Olmo, G.; Brewin, R.J.W.; Raitsos, D.E. Evaluating MULTIOBS Chlorophyll-a with Ground-Truth Observations in the Eastern Mediterranean Sea. Remote Sens. 2024, 16, 4705. https://doi.org/10.3390/rs16244705

7.

英文标题：Evaluation and Refinement of Chlorophyll-a Algorithms for High-Biomass Blooms in San Francisco Bay (USA)

中文标题：对美国旧金山湾高生物量水华中叶绿素-a算法的评估与改进

文章链接：https://www.mdpi.com/2072-4292/16/6/1103

MDPI引用格式：Kudela, R.M.; Senn, D.B.; Richardson, E.T.; Bouma-Gregson, K.; Bergamaschi, B.A.; Sim, L. Evaluation and Refinement of Chlorophyll-a Algorithms for High-Biomass Blooms in San Francisco Bay (USA). Remote Sens. 2024, 16, 1103. https://doi.org/10.3390/rs16061103

8．

英文标题：Exploring the Green Tide Transport Mechanisms and Evaluating Leeway Coefficient Estimation via Moderate-Resolution Geostationary Images

中文标题：探索绿潮迁移机制并基于中等分辨率静止轨道卫星影像评估风压差系数估算方法

文章链接：https://www.mdpi.com/2072-4292/16/16/2934

MDPI引用格式：Ji, M.; Dou, X.; Zhao, C.; Zhu, J. Exploring the Green Tide Transport Mechanisms and Evaluating Leeway Coefficient Estimation via Moderate-Resolution Geostationary Images. Remote Sens. 2024, 16, 2934. https://doi.org/10.3390/rs16162934

9.

英文标题：Remote Sensing Observations of a Coastal Water Environment Based on Neural Network and Spatiotemporal Fusion Technology: A Case Study of Hangzhou Bay

中文标题：基于神经网络与时空融合技术的沿海水环境遥感观测：以杭州湾为例

文章链接：https://www.mdpi.com/2072-4292/16/5/800

MDPI引用格式：Tang, R.; Wei, X.; Chen, C.; Jiang, R.; Shen, F. Remote Sensing Observations of a Coastal Water Environment Based on Neural Network and Spatiotemporal Fusion Technology: A Case Study of Hangzhou Bay. Remote Sens. 2024, 16, 800. https://doi.org/10.3390/rs16050800

10.

英文标题：A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns

中文标题：一种基于卫星数据校正叶绿素-a浓度并评估可靠物候模式的新方法

文章链接：https://www.mdpi.com/2072-4292/17/7/1156

MDPI引用格式：Biliani, I.; Skamnia, E.; Economou, P.; Zacharias, I. A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns. Remote Sens. 2025, 17, 1156. https://doi.org/10.3390/rs17071156

11.

英文标题：Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models

中文标题：地中海海域浮游植物粒径结构的遥感监测：基于原位数据与温度校正的丰富度模型分析

文章链接：https://www.mdpi.com/2072-4292/17/14/2362

MDPI引用格式：Gittings, J.A.; Livanou, E.; Sun, X.; Brewin, R.J.W.; Psarra, S.; Mandalakis, M.; Peltekis, A.; Di Cicco, A.; Brando, V.E.; Raitsos, D.E. Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models. Remote Sens. 2025, 17, 2362. https://doi.org/10.3390/rs17142362

12.

英文标题：Regional Assessment of COCTS HY1-C/D Chlorophyll-a and Suspended Particulate Matter Standard Products over French Coastal Waters

中文标题：法国沿海海域COCTS HY1-C/D叶绿素-a及悬浮颗粒物标准产品区域评估

文章链接：https://www.mdpi.com/2072-4292/17/14/2516

MDPI引用格式：Subirade, C.; Jamet, C.; Han, B. Regional Assessment of COCTS HY1-C/D Chlorophyll-a and Suspended Particulate Matter Standard Products over French Coastal Waters. Remote Sens. 2025, 17, 2516. https://doi.org/10.3390/rs17142516

13.

英文标题：Expanded Signal to Noise Ratio Estimates for Validating Next-Generation Satellite Sensors in Oceanic, Coastal, and Inland Waters

中文标题：基于改进的信噪比估算方法验证海洋、沿海和内陆水域中的新一代卫星传感器

文章链接：https://www.mdpi.com/2072-4292/16/7/1238

MDPI引用格式：Kudela, R.M.; Hooker, S.B.; Guild, L.S.; Houskeeper, H.F.; Taylor, N. Expanded Signal to Noise Ratio Estimates for Validating Next-Generation Satellite Sensors in Oceanic, Coastal, and Inland Waters. Remote Sens. 2024, 16, 1238. https://doi.org/10.3390/rs16071238

14.

英文标题：Mapping Water Quality in Nearshore Reef Environments Using Airborne Imaging Spectroscopy

中文标题：利用机载成像光谱技术对近岸礁环境的水质进行监测

文章链接：https://www.mdpi.com/2072-4292/16/11/1845

MDPI引用格式：Hondula, K.L.; König, M.; Grunert, B.K.; Vaughn, N.R.; Martin, R.E.; Dai, J.; Jamalinia, E.; Asner, G.P. Mapping Water Quality in Nearshore Reef Environments Using Airborne Imaging Spectroscopy. Remote Sens. 2024, 16, 1845. https://doi.org/10.3390/rs16111845

15.

英文标题：Satellite-Measured Suspended Particulate Matter Flux and Freshwater Flux in the Yellow Sea and East China Sea

中文标题：基于卫星测量黄海与东海悬浮颗粒物通量与淡水通量

文章链接：https://www.mdpi.com/2072-4292/17/15/2726

MDPI引用格式：Shi, W.; Wang, M. Satellite-Measured Suspended Particulate Matter Flux and Freshwater Flux in the Yellow Sea and East China Sea. Remote Sens. 2025, 17, 2726. https://doi.org/10.3390/rs17152726

……