Semi-analytical algorithms of ocean color remote sensing under high solar zenith angles

Li, Hao; He, Xianqiang; Shanmugam, Palanisamy; Bai, Yan; Wang, Difeng; Huang, Haiqing; Zhu, Qiankun; Gong, Fang

doi:10.1364/oe.27.00a800

Cited by 11 publications

(8 citation statements)

References 31 publications

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“…Over the past several decades, most remote-sensing algorithms have been established and validated based on satellite and in situ data under conditions of low-to-moderate SZA (<70 • ). In recent years, however, some studies showed the ability of satellites to detect ocean colour components under high SZAs [19,50]. Coastal waters are complex due to various factors, including changes in optical properties, absorbing aerosols effects, interactions with land and high SZAs in the morning and at dusk.…”

Section: Discussionmentioning

confidence: 99%

“…However, AC often fails under high solar zenith angles (SZAs) [18], limiting the potential application of ocean colour satellite data in the aquatic environment monitoring to the noontime. The performance of standard AC algorithms is significantly influenced by the SZA [19]. Under high SZAs (≥70 • ), the current AC algorithms usually fail to produce accurate ocean colour data products.…”

Section: Introductionmentioning

confidence: 99%

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Ocean Colour Atmospheric Correction for Optically Complex Waters under High Solar Zenith Angles: Facilitating Frequent Diurnal Monitoring and Management

Wang,

Liu,

Zhang

et al. 2023

Remote Sensing

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Accurate atmospheric correction (AC) is one fundamental and essential step for successful ocean colour remote-sensing applications. Currently, most ACs and the associated ocean colour remote-sensing applications are restricted to solar zenith angles (SZAs) lower than 70°. The ACs under high SZAs present degraded accuracy or even failure problems, rendering the satellite retrievals of water quality parameters more challenging. Additionally, the complexity of the bio-optical properties of the coastal waters and the presence of complex aerosols add to the difficulty of AC. To address this challenge, this study proposed an AC algorithm based on extreme gradient boosting (XGBoost) for optically complex waters under high SZAs. The algorithm presented in this research has been developed using pairs of Geostationary Ocean Colour Imager (GOCI) high-quality noontime remote-sensing reflectance (Rrs) and the Rayleigh-corrected reflectance (ρrc) derived from the Ocean Colour–Simultaneous Marine and Aerosol Retrieval Tool (OC-SMART) in the morning (08:55 LT) and at dusk (15:55 LT). The algorithm was further examined using the daily GOCI images acquired in the morning and at dusk, and the hourly (total suspended sediment) TSS concentration was also obtained based on the atmospherically corrected GOCI data. The results showed that: (i) the model produced an accurate fitting performance (R2 ≥ 0.90, RMSD ≤ 0.0034 sr−1); (ii) the model had a high validation accuracy with an independent dataset (R2 = 0.92–0.97, MAPD = 8.2–26.81% and quality assurance (QA) score = 0.9–1); and (iii) the model successfully retrieved more valid Rrs for GOCI images under high SZAs and enhanced the accuracy and coverage of TSS mapping. This algorithm has great potential to be applied to AC for optically complex waters under high SZAs, thus increasing the frequency of available observations in a day.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ocean Colour Atmospheric Correction for Optically Complex Waters under High Solar Zenith Angles: Facilitating Frequent Diurnal Monitoring and Management

Wang,

Liu,

Zhang

et al. 2023

Remote Sensing

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“…The faithful color imaging of the ocean surface plays an important role in many civil and military domains such as the ship camouflage, the ocean target detection and recognition, the ocean scene simulation, and so on [1][2][3] . However, the color characterization of the digital camera for the ocean surface imaging is a difficult work, because the color of the ocean surface was influenced by various factors such as the measurement geometry, the illumination condition, the pattern of the ocean surface, the composition of the ocean water, the depth of the ocean bottom, and so on.…”

Section: Introductionmentioning

confidence: 99%

Colorimetric characterization of digital camera for the ocean surface imaging using a two-step training method

Chen,

Song,

et al. 2024

2024 International Conference on Optoelectronic Information and Optical Engineering (OIOE 2024)

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“…At present, empirical, semi-empirical, and semi-analytical models are often employed in remote-sensing-based inversion. The empirical and semi-analytical models are mainly established based on statistical regression between in situ sampled water quality parameters and L w or R rs [35][36][37][38]. Empirical or semi-empirical models are simple but effective given sufficient in situ measurements, but the model transferability is usually limited.…”

Section: Introductionmentioning

confidence: 99%

Remote Estimation of Water Clarity and Suspended Particulate Matter in Qinghai Lake from 2001 to 2020 Using MODIS Images

et al. 2022

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Climate change and human activities have been heavily affecting oceanic and inland waters, and it is critical to have a comprehensive understanding of the aquatic optical properties of lakes. Since many key watercolor parameters of Qinghai Lake are not yet available , this paper aims to study the spatial and temporal variations of the water clarity (i.e., Secchi-disk depth, ZSD) and suspended particulate matter concentration (CSPM) in Qinghai Lake from 2001 to 2020 using MODIS images. First, the four atmospheric correction models, including the NIR–SWIR, MUMM, POLYMER, and C2RCC were tested. The NIR–SWIR with decent accuracy in all bands was chosen for the experiment. Then, four existing models for ZSD and six models for CSPM were evaluated. Two semi-analytical models proposed by Lee (2015) and Jiang (2021) were selected for ZSD (R2 = 0.74) and CSPM (R2 = 0.73), respectively. Finally, the distribution and variation of the ZSD and CSPM were derived over the past 20 years. Overall, the water of Qinghai Lake is quite clear: the monthly mean ZSD is 5.34 ± 1.33 m, and CSPM is 2.05 ± 1.22 mg/L. Further analytical results reveal that the ZSD and CSPM are highly correlated, and the relationship can be formulated with ZSD=8.072e−0.212CSPM (R2 = 0.65). Moreover, turbid water mainly exists along the edge of Qinghai Lake, especially on the northwestern and northeastern shores. The variation in the lakeshore exhibits some irregularity, while the main area of the lake experiences mild water quality deterioration. Statistically, 81.67% of the total area is dominated by constantly increased CSPM, and the area with decreased CSPM occupies 4.56%. There has been distinct seasonal water quality deterioration in the non-frozen period (from May to October). The water quality broadly deteriorated from 2001 to 2008. The year 2008 witnessed a sudden distinct improvement, and after that, the water quality experienced an extremely inconspicuous degradation. This study can fill the gap regarding the long-time monitoring of water clarity and total suspended matter in Qinghai Lake and is expected to provide a scientific reference for the protection and management of the lake.

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Semi-analytical algorithms of ocean color remote sensing under high solar zenith angles

Cited by 11 publications

References 31 publications

Ocean Colour Atmospheric Correction for Optically Complex Waters under High Solar Zenith Angles: Facilitating Frequent Diurnal Monitoring and Management

Ocean Colour Atmospheric Correction for Optically Complex Waters under High Solar Zenith Angles: Facilitating Frequent Diurnal Monitoring and Management

Colorimetric characterization of digital camera for the ocean surface imaging using a two-step training method

Remote Estimation of Water Clarity and Suspended Particulate Matter in Qinghai Lake from 2001 to 2020 Using MODIS Images

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