Effects of the Earth curvature on Mie-scattering radiances at high solar-sensor geometries based on Monte Carlo simulations.

Given the importance of vector radiative transfer models in ocean color remote sensing and a lack of suitable models capable of analyzing the Earth curvature effects on Mie-scattering radiances, this study presents an enhanced vector radiative transfer model for a spherical shell atmosphere geometry by the Monte Carlo method (MC-SRTM), considering the effects of Earth curvature, different atmospheric conditions, flat sea surface reflectance, polarization, high solar and sensor geometries, altitudes and wavelengths. A Monte Carlo photon transport model was employed to simulate the vector radiative transfer processes and their effects on the top-of-atmosphere (TOA) radiances. The accuracy of the MC-SRTM was verified by comparing its scalar model outputs from Henyey-Greenstein (HG) phase function with the Kattawar-Adams model results, and the mean relative differences were less than 2.75% and 4.33% for asymmetry factors (g-values) of 0.5 and 0.7, respectively. The vector mode results of MC-SRTM for a spherical shell geometry with the Mie-scattering phase matrix were compared with the PCOART-SA model results (from Polarized Coupled Ocean-Atmosphere Radiative Transfer model based on the pseudo-spherical assumption), and the mean relative differences were less than 2.67% when solar zenith angles (SZAs) > 70 ∘ and sensor viewing zenith angles (VZAs) < 60 ∘ for two aerosol models (coastal and tropospheric models). Based on the MC-SRTM, the effects of Earth curvature on TOA radiances at high SZAs and VZAs were analyzed. For pure aerosol atmosphere, the effects of Earth curvature on TOA radiances reached up to 5.36% for SZAs > 70 ∘ and VZAs < 60 ∘ and reduced to less than 2.60% for SZAs < 70 ∘ and VZAs > 60 ∘. The maximum Earth curvature effect of pure aerosol atmosphere was nearly same (10.06%) as that of the ideal molecule atmosphere. The results also showed no statistically significant differences for the aerosol-molecule mixed and pure aerosol atmospheres. Our study demonstrates that there is a need to consider the Earth curvature effects in the atmospheric correction of satellite ocean color data at high solar and sensor geometries.

Monitoring and spatial traceability of river water quality using Sentinel-2 satellite images.

Due to limited monitoring stations along rivers, it is difficult to trace the specific locations of high pollution areas along the whole river by traditionally in situ measurement. High-spatiotemporal-resolution Sentinel-2 satellite images make it possible to routinely monitor and trace the spatial distributions of river water quality if reliable retrieval algorithms are available. This study took seven major rivers (Qiantang River (QTR), Cao'e River (CEJ), Yongjiang River (YJ), Jiaojiang River (JJ), Oujiang River (OJ), Feiyun River (FYR), and Aojiang River (AJ)) in Zhejiang Province, China, as examples to illustrate the spatial traceability of river water quality parameters (permanganate index (CODMn), total phosphorus (TP), and total nitrogen (TN)) from Sentinel-2 satellite images. The regional retrieval models established for these parameters (CODMn, TP and TN) provided correlation coefficients (R) of 0.68, 0.82, and 0.7, respectively. Based on these models, time-series CODMn, TP, and TN products were obtained for the seven rivers from 2016 to 2021 from Sentinel-2 satellite images, and the results show that the CODMn, TP and TN were high downstream and low upstream; exceptions the CEJ, which was slightly higher in the middle reach than other reaches, and the TN in YJ, which was higher upstream than downstream. The downstream reaches were the main areas suffering from relatively high values in most seasons. Except for the springtime TN level in CEJ, the high value areas were located along the middle reaches. In summer and autumn, the high TN areas in JJ, OJ, and AJ were located along the middle and lower reaches, and the TN in YJ was highest in the upstream. More importantly, this study revealed that the specific locations of high pollution areas along rivers can be effectively traced using Sentinel-2 satellite images, which would be helpful for precise water quality control of rivers.

Satellite retrieval of the linear polarization components of the water-leaving radiance in open oceans.

Atmospheric correction (AC) of polarized radiances acquired by polarization satellite sensors, remains a challenge due to the complex radiative transfer processes of the coupled ocean-atmosphere system. In this study, we proposed an innovative polarized AC algorithm built on the near-infrared band (PACNIR) with an emphasis on the retrieval of the linear polarization components of the water-leaving radiance in clear open oceans. This algorithm was based on the black ocean assumption in the near-infrared band and fitted polarized radiance measurements along multiple observation directions with nonlinear optimized processing. Our retrieval algorithm notably inverted the linearly polarized components of the water-leaving radiance and aerosol parameters. Compared with that of the simulated linear polarization components of the water-leaving radiance via the vector radiative transfer model for the studied sea regions, the mean absolute error of the PACNIR-retrieved linearly polarized components (nQw and nUw) exhibited a magnitude of 10-4, while the magnitude of that of the simulated nQw and nUw data was 10-3. Moreover, the PACNIR-retrieved aerosol optical thicknesses at 865 nm exhibited a mean absolute percentage error of approximately 30% relative to in situ values obtained from Aerosol Robotic Network-Ocean Color (AERONET-OC) sites. The PACNIR algorithm could facilitate AC of the polarized data provided by the next generation of multiangle polarization satellite ocean color sensors.

Spherical vector radiative transfer model for satellite ocean color remote sensing.

Atmospheric correction is the key step for satellite ocean color remote sensing. However, most of the existing atmospheric correction algorithms do not consider the effects of Earth curvature. In fact, Earth curvature has a significant impact on satellite observation signals under large solar zenith angles or large viewing zenith angles. In this study, based on the Monte Carlo method, a vector radiative transfer model with spherical shell atmosphere geometry (hereafter our SSA-MC model) considering the influence of Earth curvature was established, which can be applied to conditions with high solar zenith angles or high viewing zenith angles. Our SSA-MC model was first compared with the Adams&Kattawar model, and the results show that the mean relative differences are 1.72%, 1.36% and 1.28% for solar zenith angles of 0 ∘, 70.47 ∘ and 84.26 ∘, respectively. Moreover, our SSA-MC model was further validated by more recently benchmarks from Korkin's scalar and vector models, and the results show that the relative differences are mostly less than 0.5% even at extremely high solar zenith angles (84.26 ∘). Then, our SSA-MC model was verified with the Rayleigh scattering radiance calculated by the look-up tables (LUTs) in SeaDAS under low-to-moderate solar or viewing zenith angles, and the results show that the relative differences are less than 1.42% when solar zenith angles are less than 70 ∘ and viewing zenith angles are less than 60 ∘. Our SSA-MC model was also compared with the Polarized Coupled Ocean-Atmosphere Radiative Transfer model based on the pseudo-spherical assumption (PCOART-SA), and the results show that the relative differences are mostly less than 2%. At last, based on our SSA-MC model, the effects of Earth curvature on Rayleigh scattering radiance were analyzed for both high solar zenith angles and high viewing zenith angles. The result shows that the mean relative error between the plane-parallel (PP) geometry and spherical shell atmosphere (SSA) geometry is 0.90% when the solar zenith angle is 60 ∘ and the viewing zenith angle is 60.15 ∘. However, the mean relative error increases with increasing solar zenith angle or viewing zenith angle. When the solar zenith angle is 84 ∘ and the viewing zenith angle is 84.02 ∘, the mean relative error is 4.63%. Thus, Earth curvature should be considered in atmospheric corrections at large solar or viewing zenith angles.

Atmospheric correction algorithm based on the interpolation of ultraviolet and shortwave infrared bands.

Traditional atmospheric correction algorithms of ocean color remote sensing are mostly based on the extrapolation of aerosol scattering radiance from a reference band (near infrared, shortwave infrared, or ultraviolet bands), which inevitably leads to the problem of extrapolation error amplification with the increase of extrapolation spectral distance. In this study, we propose a practical interpolation-based algorithm (named the UV-SWIR-AC algorithm) using three reference bands (one ultraviolet and two shortwave infrared bands) for turbid waters. According to 6SV radiative transfer simulations with 15 customized aerosol types, we establish a fitting function framework for the aerosol scattering radiance in the wavelength range of 322-1643 nm. We apply the UV-SWIR-AC algorithm to the real satellite ocean color data observed by the Second-Generation Global Imager aboard the Global Change Observation Mission-Climate (SGLI/GCOM-C) and compare the retrieved remote sensing reflectance with the in-situ data from the observation platform of Hangzhou Bay in the East China Sea and typical bays. The results show that the UV-SWIR-AC algorithm can achieve a better performance than the traditional, extrapolation-based algorithm in turbid waters. Moreover, in the typical regional analysis, this new algorithm also demonstrates a high applicability. The UV-SWIR-AC algorithm should be helpful to improve the atmospheric correction accuracy for next-generation ocean color missions (e.g., NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission and China's Haiyang-1E/F (HY-1E/F) mission) with wider spectral ranges from the ultraviolet to shortwave infrared wavelengths.

Automatic detection of suspected sewage discharge from coastal outfalls based on Sentinel-2 imagery.

Terrestrial pollution has a great impact on the coastal ecological environment, and widely distributed coastal outfalls act as the final gate through which pollutants flow into rivers and oceans. Thus, effectively monitoring the water quality of coastal outfalls is the key to protecting the ecological environment. Satellite remote sensing provides an attractive way to monitor sewage discharge. Selecting the coastal areas of Zhejiang Province, China, as an example, this study proposes an innovative method for automatically detecting suspected sewage discharge from coastal outfalls based on high spatial resolution satellite imageries from Sentinel-2. According to the accumulated in situ observations, we established a training dataset of water spectra covering various optical water types from satellite-retrieved remote sensing reflectance (Rrs). Based on the clustering results from unsupervised classification and different spectral indices, a random forest (RF) classification model was established for the optical water type classification and detection of suspected sewage. The final classification covers 14 optical water types, with type 12 and type 14 corresponding to the high eutrophication water type and suspected sewage water type, respectively. The classification result of model training datasets exhibited high accuracy with only one misclassified sample. This model was evaluated by historical sewage discharge events that were verified by on-site observations and demonstrated that it could successfully recognize sewage discharge from coastal outfalls. In addition, this model has been operationally applied to automatically detect suspected sewage discharge in the coastal area of Zhejiang Province, China, and shows broad application value for coastal pollution supervision, management, and source analysis.

Changes in riverine organic carbon input to the ocean from mainland China over the past 60 years.

Compared to rivers in Europe and North America, Chinese rivers that discharge into oceans have different organic carbon (OC) transport characteristics. Out of the top 25 largest rivers worldwide, three (Changjiang, Huanghe, and Zhujiang rivers) are located in China, along with numerous small rivers. Thus, synthesized estimates of total riverine OC flux from Chinese rivers into marginal seas are critical but remain deficient. In this study, we developed relationships between riverine OC (dissolved OC, or DOC, and particulate OC, or POC) and basin characteristic variables (basin population density, precipitation, and riverine suspended sediment concentration) to estimate annual riverine DOC and POC fluxes during 1953-2016. The results showed that rivers in mainland China transported 9.63 Tg C of OC to the marginal seas in 2008, with 4.61 Tg C of DOC and 5.02 Tg C of POC. Of this transported OC, 14.28% DOC and 17.49% POC were transported by small southeastern rivers, whose drainage areas covered only 6.68% of the total. Because of intensifying human activities, DOC export increased but POC export decreased during 1953-2016. Additionally, basin population growth and reservoir water capacity were the major factors for increasing DOC flux and decreasing POC flux, respectively. Overall, the DOC/POC ratio increased for OC transport in Chinese rivers. Therefore, this study is important for understanding human-induced impacts on environmental change and the carbon cycle in marginal seas.

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

With the increasing interest in ocean color remote sensing in polar oceans and geostationary ocean color satellite with diurnal observations, it is unavoidable to encounter ocean color retrievals under high solar zenith angles. Under these scenarios, the capability of current remote sensing algorithms is poorly known. In this study, the performance of the two widely used semi-analytical algorithms for the water inherent optical properties (QAA and GSM01) under high solar zenith angle conditions were firstly evaluated based on global in situ data set (SeaBASS-NOMAD). The results showed that the performances of both QAA and GSM01 degraded significantly with the increasing in solar zenith angle (SZA), and the biases increased about 1.3-fold when SZA varied from 30° to 80°. The high uncertainties at high SZA was mainly induced by the systematic overestimation of the key parameter u (ratio of backscattering coefficient to the sum of absorption and backscattering coefficients) at high solar zenith angles. Based on the Hydrolight-simulated data set, a new model (NN-algorithm) for retrieving u from remote sensing reflectance was developed for high solar zenith angle conditions using the neural network method. The validation results revealed that the NN-algorithm could improve the estimation of parameter u and further ocean color products. In addition, our results indicate that a more accurate atmosphere correction is needed to deal with ocean color remote sensing data acquired under large solar zenith angle conditions.

Enteral nutrition feeding in Chinese intensive care units: a cross-sectional study involving 116 hospitals.

BACKGROUND: There is a lack of large-scale epidemiological data on the clinical practice of enteral nutrition (EN) feeding in China. This study aimed to provide such data on Chinese hospitals and to investigate factors associated with EN delivery. METHODS: This cross-sectional study was launched in 118 intensive care units (ICUs) of 116 mainland hospitals and conducted on April 26, 2017. At 00:00 on April 26, all patients in these ICUs were included. Demographic and clinical variables of patients on April 25 were obtained. The dates of hospitalization, ICU admission and nutrition initiation were reviewed. The outcome status 28 days after the day of investigation was obtained. RESULTS: A total of 1953 patients were included for analysis, including 1483 survivors and 312 nonsurvivors. The median study day was day 7 (IQR 2-19 days) after ICU entry. The proportions of subjects starting EN within 24, 48 and 72 h after ICU entry was 24.8% (84/352), 32.7% (150/459) and 40.0% (200/541), respectively. The proportion of subjects receiving > 80% estimated energy target within 24, 48, 72 h and 7 days after ICU entry was 10.5% (37/352), 10.9% (50/459), 11.8% (64/541) and 17.8% (162/910), respectively. Using acute gastrointestinal injury (AGI) 1 as the reference in a Cox model, patients with AGI 2-3 were associated with reduced likelihood of EN initiation (HR 0.46, 95% CI 0.353-0.599; p < 0.001). AGI 4 was significantly associated with lower hazard of EN administration (HR 0.056; 95% CI 0.008-0.398; p = 0.004). In a linear regression model, greater Sequential Organ Failure Assessment scores (coefficient - 0.002, 95% CI - 0.008 to - 0.001; p = 0.024) and male gender (coefficient - 0.144, 95% CI - 0.203 to - 0.085; p < 0.001) were found to be associated with lower EN proportion. As compared with AGI 1, AGI 2-3 was associated with lower EN proportion (coefficient - 0.206, 95% CI - 0.273 to - 0.139; p < 0.001). CONCLUSIONS: The study showed that EN delivery was suboptimal in Chinese ICUs. More attention should be paid to EN use in the early days after ICU admission.

Refined use of AISA band-differences for oil slick identification beyond brightness contrast reversal under sunglint.

Marine oil slicks show brighter or darker than surrounding oil-free seawater under different sunglint, which can be observed by satellite optical sensors. Although this has been interpreted using a critical angle concept and simulated using the Cox-Munk model, it has not been demonstrated in high spatial resolution images from airborne sensors. In this study, an AISA (airborne imaging spectrometer for applications) image was used to determine the characteristics of non-emulsion oil slicks under sunglint in high spatial resolution images. Although a similar positive or negative contrast between non-emulsion oil slicks and oil-free seawater can be observed, it is difficult to directly model sunglint reflectance due to the different remote sensing scale effect. There are many sun glitter pepper noise produced by various micro-mirror facets of ocean surface in high spatial resolution images. Based on the optical image characteristics, a normalized noise index (ξ) was designed to evaluate the pepper noise in 1830 band-difference results. Then a level segmentation method was used to delineate the oil slicks under various sunglint from a minimum pepper noise image. Our study provides a preliminary reference for airborne optical remote sensing of oil slicks under various levels of sunglint.

Ocean color retrieval from MWI onboard the Tiangong-2 Space Lab: preliminary results.

The Moderate-resolution Wide-wavelengths Imager (MWI) is the ocean color sensor onboard the Chinese Tiangong-2 Space Lab, which was launched on Sept. 15, 2016. The MWI is also an experimental satellite sensor for the Chinese next generation ocean color satellites, HY-1E and HY-1F, which are scheduled for launch around 2021. With 100m spatial resolution and 18 bands in the visible light and infrared wavelengths, MWI provides high quality ocean color observations especially over coastal and inland waters. For the first time, this study presents some important results on water color products generated from the MWI for the oceanic and inland waters. Preliminary validation in turbid coastal and inland waters showed good agreement between the MWI-retrieved normalized water-leaving radiances (Lwn) and in situ data. Further, the MWI-retrieved Lwn values compared well with the GOCI-retrieved Lwn values, with the correlation coefficient greater than 0.90 and mean relative differences smaller than 26.63% (413 nm), 4.72% (443 nm), 3.69% (490 nm), 7.15% (565 nm), 9.45% (665 nm), 8.11% (682.5 nm), 14.68% (750 nm) and 18.55% (865 nm). As for the Level 2 product (e.g, total suspended matter TSM) in turbid Yangtze River Estuary and Hangzhou Bay waters, the relative difference between MWI and GOCI-derived TSM values was ~18.59% with the correlation coefficient of 0.956. In open-oceanic waters, the retrieved MWI-Chla distributions were well consistent with the MODIS/Aqua and VIIRS Chla values products and resolved finer spatial structures of phytoplankton blooms. This study provides encouraging results for the MWI's performance and operational applications in oceanic and inland regions.

Polarization-based enhancement of ocean color signal for estimating suspended particulate matter: radiative transfer simulations and laboratory measurements.

Absorption and scattering by molecules, aerosols and hydrosols, and the reflection and transmission over the sea surface can modify the original polarization state of sunlight. However, water-leaving radiance polarization, containing embedded water constituent information, has largely been neglected. Here, the efficiency of the parallel polarization radiance (PPR) for enhancing ocean color signal of suspended particulate matter is examined via vector radiative transfer simulations and laboratory experiments. The simulation results demonstrate that the PPR has a slightly higher ocean color signal at the top-of-atmosphere as compared with that of the total radiance. Moreover, both the simulations and laboratory measurements reveal that, compared with total radiance, PPR can effectively enhance the normalized ocean color signal for a large range of observation geometries, wavelengths, and suspended particle concentrations. Thus, PPR has great potential for improving the ocean color signal detection from satellite.

Variation of dissolved organic carbon transported by two Chinese rivers: The Changjiang River and Yellow River.

Real-time monitoring of riverine dissolved organic carbon (DOC) and the associated controlling factors is essential to coastal ocean management. This study was the first to simulate the monthly DOC concentrations at the Datong Hydrometric Station for the Changjiang River and at the Lijin Hydrometric Station for the Yellow River from 2000 to 2013 using a multilayer back-propagation neural network (MBPNN), along with basin remote-sensing products and river in situ data. The average absolute error between the modeled values and in situ values was 9.98% for the Changjiang River and 10.84% for the Yellow River. As an effect of water dilution, the variations of DOC concentrations in the two rivers were significantly negatively affected by discharge, with lower values reported during the wet season. Moreover, vegetation growth status and agricultural activities, represented by the gross primary product (GPP) and cropland area percent (CropPer) in the river basin, respectively, also significantly affected the DOC concentration in the Changjiang River, but not the Yellow River. The monthly riverine DOC flux was calculated using modeled DOC concentrations. In particular, the riverine DOC fluxes were affected by discharge, with 71.06% being reported for the Changjiang River and 90.71% for the Yellow River. Over the past decade, both DOC concentration and flux in the two rivers have not shown significant changes.

A new simple concept for ocean colour remote sensing using parallel polarisation radiance.

Ocean colour remote sensing has supported research on subjects ranging from marine ecosystems to climate change for almost 35 years. However, as the framework for ocean colour remote sensing is based on the radiation intensity at the top-of-atmosphere (TOA), the polarisation of the radiation, which contains additional information on atmospheric and water optical properties, has largely been neglected. In this study, we propose a new simple concept to ocean colour remote sensing that uses parallel polarisation radiance (PPR) instead of the traditional radiation intensity. We use vector radiative transfer simulation and polarimetric satellite sensing data to demonstrate that using PPR has two significant advantages in that it effectively diminishes the sun glint contamination and enhances the ocean colour signal at the TOA. This concept may open new doors for ocean colour remote sensing. We suggest that the next generation of ocean colour sensors should measure PPR to enhance observational capability.

Atmospheric correction of satellite ocean color imagery using the ultraviolet wavelength for highly turbid waters.

Instead of the conventionally atmospheric correction algorithms using the near-infrared and shortwave infrared wavelengths, an alternative practical atmospheric correction algorithm using the ultraviolet wavelength for turbid waters (named UV-AC) is proposed for satellite ocean color imagery in the paper. The principle of the algorithm is based on the fact that the water-leaving radiance at ultraviolet wavelengths can be neglected as compared with that at the visible light wavelengths or even near-infrared wavelengths in most cases of highly turbid waters due to the strong absorption by detritus and colored dissolved organic matter. The UV-AC algorithm uses the ultraviolet band to estimate the aerosol scattering radiance empirically, and it does not need any assumption of the water's optical properties. Validations by both of the simulated data and in situ data show that the algorithm is appropriate for the retrieval of the water-leaving radiance in turbid waters. The UV-AC algorithm can be used for all the current satellite ocean color sensors, and it is especially useful for those ocean color sensors lacking the shortwave infrared bands. Moreover, the algorithm can be used for any turbid waters with negligible water-leaving radiance at ultraviolet wavelength. Based on our work, we recommend the future satellite ocean color remote sensors setting the ultraviolet band to perform the atmospheric correction in turbid waters.