Search Results (666)

Atmospheric correction, the removal of the atmospheric signal from a satellite image, still poses a challenge over optically complex coastal water. Here, we present the first atmospheric correction validation study performed in optically complex Norwegian fjords. We compare in situ reflectance measurements and chlorophyll-a concentrations from Western Norwegian fjords with atmospherically corrected Sentinel-3 Ocean and Land Colour Instrument observations and chlorophyll-a retrievals. Measurements were taken in Hardangerfjord, Bjørnafjord and Møkstrafjord during a bright green coccolithophore bloom in May 2022, and during a period of no apparent discoloration in April 2023. Coccolithophore blooms generally peak in the blue region (490 nm), but spectra measured in this bloom peaked in the green region (559 nm), possibly due to absorption by colored dissolved organic matter (a_CDOM(440) = 0.18 ± 0.01 m⁻¹) or due to high cell counts (up to 15 million cells/L). We tested a wide range of atmospheric correction algorithms, including ACOLITE, BAC, C2RCC, iCOR, L2gen, POLYMER and the SNAP Rayleigh correction. Surprisingly, atmospheric correction algorithms generally performed better during the bloom (average MAE = 1.25) rather than in the less scattering water in the following year (average MAE = 4.67), possibly because the high water-leaving radiances due to the high backscattering by coccolithophores outweighed the adjacency effect. However, atmospheric correction algorithms consistently underestimated water-leaving reflectance in the bloom. In non-bloom matchups, most atmospheric correction algorithms overestimated the water-leaving reflectance. POLYMER appears unsuitable for use over coccolithophore blooms but performed well in non-bloom matchups. Neither BAC, used in the official Level-2 OLCI products, nor C2RCC performed well in the bloom. Nine chlorophyll-a retrieval algorithms, including two algorithms based on neural nets, four based on red and near-infrared bands and three maximum band-ratio algorithms, were also tested. Most chlorophyll-a retrieval algorithms did not perform well in either year, although several did perform within the 70% accuracy threshold for case-2 waters. A red-edge algorithm performed best in the coccolithophore blooms, while a maximum band-ratio algorithm performed best in the following year. Full article

Sentinel-2/MSI and Landsat-8/OLI sensors enable the mapping of ocean color-related bio-optical parameters of surface coastal and inland waters. While many algorithms have been developed to estimate the Chlorophyll-a concentration, Chl-a, and the suspended particulate matter, SPM, from OLI and MSI data, the absorption by colored dissolved organic matter, a_cdom, a key parameter to monitor the concentration of dissolved organic matter, has received less attention. Herein we present an inverse model (hereafter referred to as AquaCDOM) for estimating a_cdom at the wavelength 412 nm (a_cdom (412)), within the surface layer of coastal waters, from measurements of ocean remote sensing reflectance, R_rs (λ), for these two high spatial resolution (around 20 m) sensors. Combined with a water class-based approach, several empirical algorithms were tested on a mixed dataset of synthetic and in situ data collected from global coastal waters. The selection of the final algorithms was performed with an independent validation dataset, using in situ, synthetic, and satellite R_rs (λ) measurements, but also by testing their respective sensitivity to typical noise introduced by atmospheric correction algorithms. It was found that the proposed algorithms could estimate a_cdom (412) with a median absolute percentage difference of ~30% and a median bias of 0.002 m⁻¹ from the in situ and synthetic datasets. While similar performances have been shown with two other algorithms based on different methodological developments, we have shown that AquaCDOM is much less sensitive to atmospheric correction uncertainties, mainly due to the use of band ratios in its formulation. After the application of the top-of-atmosphere gains and of the same atmospheric correction algorithm, excellent agreement has been found between the OLI- and MSI-derived a_cdom (412) values for various coastal areas, enabling the application of these algorithms for time series analysis. An example application of our algorithms for the time series analysis of a_cdom (412) is provided for a coastal transect in the south of Vietnam. Full article

In recent decades, inland water remote sensing has seen growing interest and very strong development. This includes improved spatial resolution, increased revisiting times, advanced multispectral sensors and recently even hyperspectral sensors. However, inland waters are more challenging than oceanic waters due to their higher complexity of optically active constituents and stronger adjacency effects due to their small size and nearby vegetation and built structures. Thus, bio-optical modeling of inland waters requires higher ground-truthing efforts. Large-scale ground-based sensor networks that are robust, self-sufficient, non-maintenance-intensive and low-cost could assist this otherwise labor-intensive task. Furthermore, most existing sensor systems are rather expensive, precluding their employability. Recently, low-cost mini-spectrometers have become widely available, which could potentially solve this issue. In this study, we analyze the characteristics of such a mini-spectrometer, the Hamamatsu C12880MA, and test it regarding its application in measuring water-leaving radiance near the surface. Overall, the measurements performed in the laboratory and in the field show that the system is very suitable for the targeted application. Full article

Aerosol and aerosol-cloud radiation interactions significantly influence Earth’s radiative balance, hydrological cycle, global monsoons, atmospheric circulation, and climate, attracting substantial scientific attention. This study employs bibliometric and quantitative trend analyses to evaluate the development, knowledge structure, and research trends in aerosol and aerosol-cloud radiation interactions from 1999 to 2023 using Web of Science Core Collection data. Results reveal a consistent increase in publications and citations, indicating sustained attention in this field. The USA and China are identified as the most prolific countries, with significant contributions from institutions like the National Aeronautics and Space Administration and the Chinese Academy of Sciences. However, while the USA shows a recent decline in growth, China has demonstrated a significant upward trend in research contributions. Productive journals include Atmospheric Chemistry and Physics and the Journal of Geophysical Research-Atmospheres, with prolific authors such as Babu S. Suresh and Li Zhanqing. A co-occurrence analysis of keywords identifies research topics focused on aerosol optical properties, aerosol types, aerosol radiation interactions, and aerosol-cloud interactions. Emerging trends emphasize advanced methodologies such as remote sensing, model simulation, and artificial intelligence, with growing attention to regions like the Southern Ocean and the Arctic. This comprehensive analysis provides valuable insights for researchers, identifying knowledge gaps and guiding future research directions in aerosol and aerosol-cloud radiation interactions, which are crucial for understanding their climatic and atmospheric impacts. Full article

This study identifies the characteristics of water regions with negative normalized water-leaving radiance ($n{L}_w\left(\lambda \right)$) values in the satellite observations of the Second-generation Global Imager (SGLI) sensor aboard the Global Change Observation Mission–Climate (GCOM-C) satellite. SGLI Level-2 data, along with atmospheric and in-water optical properties measured by the sun photometers in the AErosol RObotic NETwork-Ocean Color (AERONET-OC) from 26 sites globally, are utilized in this study. The focus is particularly on Tokyo Bay and the Ariake Sea, semi-enclosed water regions in Japan where previous research has pointed out the occurrence of negative $n{L}_w\left(\lambda \right)$ values due to atmospheric correction with SGLI. The study examines the temporal changes in atmospheric and in-water optical properties in these two regions, and identifies the characteristics of regions prone to negative $n{L}_w\left(\lambda \right)$ values due to atmospheric correction by comparing the optical properties of these regions with those of 24 other AERONET-OC sites. The time series results of $n{L}_w\left(\lambda \right)$ and the single-scattering albedo ($\mathsf{\omega }\left(\lambda \right)$) obtained by the sun photometers at the two sites in Tokyo Bay and Ariake Sea, along with SGLI $n{L}_w\left(\lambda \right)$, indicate the occurrence of negative values in SGLI $n{L}_w\left(\lambda \right)$ in blue band regions, which are mainly attributed to the inflow of absorptive aerosols. However, these negative values are not entirely explained by $\mathsf{\omega }\left(\lambda \right)$ at 443 nm alone. Additionally, a comparison of in situ $n{L}_w\left(\lambda \right)$ measurements in Tokyo Bay and the Ariake Sea with $n{L}_w\left(\lambda \right)$ values obtained from 24 other AERONET-OC sites, as well as the inherent optical properties (IOPs) estimated through the Quasi-Analytical Algorithm version 5 (QAA_v5), identified five sites—Gulf of Riga, Long Island Sound, Lake Vanern, the Tokyo Bay, and Ariake Sea—as regions where negative $n{L}_w\left(\lambda \right)$ values are more likely to occur. These regions also tend to have lower $n{L}_w\left(\lambda \right)$ values at shorter wavelengths. Furthermore, relatively high light absorption by phytoplankton and colored dissolved organic matter, plus non-algal particles, was confirmed in these regions. This occurs because atmospheric correction processing excessively subtracts aerosol light scattering due to the influence of aerosol absorption, increasing the probability of the occurrence of negative $n{L}_w\left(\lambda \right)$ values. Based on the analysis of atmospheric and in-water optical measurements derived from AERONET-OC in this study, it was found that negative $n{L}_w\left(\lambda \right)$ values due to atmospheric correction are more likely to occur in water regions characterized by both the presence of absorptive aerosols in the atmosphere and high light absorption by in-water substances. Full article

Essential Climate Variables (ECVs) like ocean colour provide crucial information on the Optically Active Constituents (OACs) of seawater, such as phytoplankton, non-algal particles, and coloured dissolved organic matter (CDOM). The challenge in estimating these constituents through remote sensing is in accurately distinguishing and quantifying optical and biogeochemical properties, e.g., absorption coefficients and the concentration of chlorophyll a (Chla), especially in complex waters. This study evaluated the temporal and spatial variability of bio-optical properties in the coastal waters of the Western Iberian Coast (WIC), contributing to the assessment of satellite retrievals. In situ data from three oceanographic cruises conducted in 2019–2020 across different seasons were analyzed. Field-measured biogenic light absorption coefficients were compared to satellite estimates from Ocean-Colour Climate Change Initiative (OC-CCI) reflectance data using semi-analytical approaches (QAA, GSM, GIOP). Key findings indicate substantial variability in bio-optical properties across different seasons and regions. New bio-optical coefficients improved satellite data retrieval, reducing uncertainties and providing more reliable phytoplankton absorption estimates. These results highlight the need for region-specific algorithms to accurately capture the unique optical characteristics of coastal waters. Improved comprehension of bio-optical variability and retrieval techniques offers valuable insights for future research and coastal environment monitoring using satellite ocean colour data. Full article

This paper explores a new approach to improving satellite measurements of cloud optical thickness and droplet size by considering the radiative impacts of horizontal heterogeneity in boundary-layer cumulus clouds. In contrast to the usual bottom-up approach that retrieves cloud properties for individual pixels and subsequently compiles large-scale statistics, the proposed top-down approach first determines the effect of 3D heterogeneity on large-scale cloud statistics and then distributes the overall effects to individual pixels. The potential of this approach is explored by applying a regression-based scheme to a simulated dataset containing over 3000 scenes generated through large eddy simulations. The results show that the new approach can greatly reduce the errors in widely used bispectral retrievals that assume horizontal homogeneity. Errors in large-scale mean values and cloud variability are typically reduced by factors of two to four for 1 km resolution retrievals—and the reductions remain significant even for a 4 km resolution. The calculations also reveal that over vegetation heterogeneity-caused droplet size retrieval biases are often opposite to the biases found over oceans. Ultimately, the proposed approach shows potential for improving the accuracy of both old and new satellite datasets. Full article

The high-precision magnetic survey system is crucial for ocean exploration. However, most existing systems face challenges such as high noise levels, low sensitivity, and inadequate magnetic compensation effects. To address these issues, we developed a high-precision magnetic survey system based on the manned submersible “Deep Sea Warrior” for deep-ocean magnetic exploration. This system incorporates a compact optically pumped cesium (Cs) magnetometer sensor to measure the total strength of the external magnetic field. Additionally, a magnetic compensation sensor is included at the front end to measure real-time attitude changes of the platform. The measured data are then transmitted to a magnetic signal processor, where an algorithm compensates for the platform’s magnetic interference. We also designed a deep pressure chamber to allow for a maximum working depth of 4500 m. Experiments conducted in both indoor and field environments verified the performance of the proposed magnetic survey system. The results showed that the system’s sensitivity is ≤0.5 nT, the noise level of the magnetometer sensor is ≤1 pT/√Hz at 1 Hz, and the sampling rate is 10 Hz. The proposed system has potential applications in ocean and geophysical exploration. Full article

Ocean salinity plays an important role in oceanographic research as one of the fundamental parameters. An optical salinometer based on the Michelson interferometer (MI) suitable for in situ measurement in deep-sea environments is proposed in this work, and it features real-time calibration and multichannel multiplexing using the frequency modulated continuous wave (FMCW) technique. The symmetrical sapphire structure used to withstand deep-sea pressure can not only achieve automatic temperature compensation, but also counteract the changes in optical path length under deep-sea pressure. A model formula suitable for optical salinity demodulation is proposed through the nonlinear least squares fitting method. In vertical profile testing, the optical salinometer demonstrated remarkable tracking performance, achieving an error of less than 0.001 psu. The sensor displays a stable salinity demodulation error within ±0.002 psu during a three-month long-term test at a depth of 4000 m. High stability and resolution make this optical salinometer have broad development prospects in ocean observation. Full article

The deep integration of communication and sensing technology in fiber-optic systems has been highly sought after in recent years, with the aim of rapid and cost-effective large-scale upgrading of existing communication cables in order to monitor ocean activities. As a proof-of-concept demonstration, a high-degree of compatibility was shown between forward-transmission distributed fiber-optic vibration sensing and an on–off keying (OOK)-based communication system. This type of deep integration allows distributed sensing to utilize the optical fiber communication cable, wavelength channel, optical signal and demodulation receiver. The addition of distributed sensing functionality does not have an impact on the communication performance, as sensing involves no hardware changes and does not occupy any bandwidth; instead, it non-intrusively analyzes inherent vibration-induced noise in the data transmitted. Likewise, the transmission of communication data does not affect the sensing performance. For data transmission, 150 Mb/s was demonstrated with a BER of 2.8 × 10⁻⁷ and a Q_dB of 14.1. For vibration sensing, the forward-transmission method offers distance, time, frequency, intensity and phase-resolved monitoring. The limit of detection (LoD) is 8.3 pε/Hz^1/2 at 1 kHz. The single-span sensing distance is 101.3 km (no optical amplification), with a spatial resolution of 0.08 m, and positioning accuracy can be as low as 10.1 m. No data averaging was performed during signal processing. The vibration frequency range tested is 10–1000 Hz. Full article

Underwater optical wireless communication (UOWC) is a field of research that has gained popularity with the development of unmanned underwater vehicle (UUV) technologies. Its utilization is crucial in offshore industries engaging in sustainable alternatives for food production and energy security. Although UOWC can meet the high data rate and low latency requirements of underwater video transmission for UUV operations, the links that enable such communication are affected by the inhomogeneous light attenuation and the presence of sunlight. Here, we present how the underwater spectral distribution of the light field can be modeled along the depths of eight stratified oceanic water types. We considered other established models, such as SPCTRL2, Haltrin’s single parameter model for inherent optical properties, and a model for the estimation of the depth distribution of chlorophyll-a, and present insights based on transmission wavelength for the maximum signal-to-noise ratio (SNR) under different optical link parameter combinations such as beam divergence and transmit power under “daytime” and “nighttime” conditions. The results seem to challenge the common notion that the blue-green spectrum is the most suitable for underwater optical communication. We highlight a unique relationship between the transmission wavelength for the optimal SNR and the link parameters and distance, which varies with depth depending on the type of oceanic water stratification. Our analyses further highlighted potential implications for solar discriminatory approaches and strategies for routing in cooperative optical wireless networks in the photic region. Full article

Water quality indicator algorithms often separate marine and freshwater systems, introducing artificial boundaries and artifacts in the freshwater to ocean continuum. Building upon the Ocean Colour- (OC) and Lakes Climate Change Initiative (CCI) projects, we propose an improved tool to assess the interactions across river–sea transition zones. Fuzzy clustering methods are used to generate optical water types (OWT) representing spectrally distinct water reflectance classes, occurring within a given region and period (here 2016–2021), which are then utilized to assign membership values to every OWT class for each pixel and seamlessly blend optimal in-water algorithms across the region. This allows a more flexible representation of water provinces across transition zones than classic hard clustering techniques. Improvements deal with expanded sensor spectral band-sets, such as Sentinel-3 OLCI, and increased spatial resolution with Sentinel-2 MSI high-resolution data. Regional clustering was found to be necessary to capture site-specific characteristics, and a method was developed to compare and merge regional cluster sets into a pan-regional representative OWT set. Fuzzy clustering OWT timeseries data allow unique insights into optical regime changes within a lagoon, estuary, or delta system, and can be used as a basis to improve WQ algorithm performance. Full article

The underwater environment used for communication is harsh and complex, necessitating heightened standards for spectral efficiency and reliability in underwater wireless optical communication (UWOC) systems. The focus of this work is on the performance of multi-user UWOC systems operating in oblique channels of ocean turbulence downlink, where users are randomly distributed at a certain depth. A joint optimization scheme is proposed, which joints rate-splitting multiple access (RSMA) and power allocation so that the system’s ergodic sum capacity is optimized to improve the transmission bandwidth. Furthermore, the probability density function (PDF) and cumulative distribution function (CDF) models for the received signal-to-noise ratio (SNR) of a multi-user multiple-input multiple-output (MIMO) system operating in the turbulent underwater oblique channels are established, accounting for the avalanche photodiode (APD) shot noise and solar radiation noise. Theoretical derivations are presented to quantify the ergodic capacity and outage probability of the multi-user system utilizing the RSMA technology. Subsequently, a numerical analysis is conducted to investigate the influence of the power allocation coefficient, RSMA, and the joint optimization algorithm on the performance of a two-user MIMO system leveraging RSMA. The simulation results show that our optimization scheme effectively reduces the outage probability, thereby achieving the maximum system sum rate and validating the practical feasibility and efficacy of the proposed scheme. Full article

Ocean acidification has become a major climate change concern requiring continuous observation. Additionally, in the industry, pH surveillance is of great importance. Consequently, there is a pressing demand to develop robust and inexpensive pH sensors. Ratiometric fluorescence pH sensing stands out as a promising concept. The application of carbon dots in fluorescent sensing presents a compelling avenue for the advancement of pH-sensing solutions. This potential is underpinned by the affordability of carbon dots, their straightforward manufacturing process, low toxicity, and minimal susceptibility to photobleaching. Thus, investigating novel carbon dots is essential to identify optimal pH-sensitive candidates. In this study, five carbon dots were synthesized through a simple solvothermal treatment, and their fluorescence was examined as a function of pH within the range of 5–9, across an excitation range of 200–550 nm and an emission range of 250–750 nm. The resulting optical features showed that all five carbon dots exhibited pH sensitivity in both the UV and visible regions. One type of carbon dot, synthesized from m-phenylenediamine, displayed ratiometric properties at four excitation wavelengths, with the best results observed when excited in the visible spectrum at 475 nm. Indeed, these carbon dots exhibited good linearity over pH values of 6–9 in aqueous Carmody buffer solution by calculating the ratio of the green emission band at 525 nm to the orange one at 630 nm (${\mathcal{I}}_{525\mathrm{nm}}$/${\mathcal{I}}_{630\mathrm{nm}}$), demonstrating highly suitable properties for ratiometric sensing. Full article

Monitoring oil drift by integrating multi-source satellite imagery has been a relatively underexplored practice due to the limited time-sampling of datasets. However, this limitation has been mitigated by the emergence of new satellite constellations equipped with both Synthetic Aperture Radar (SAR) and optical sensors. In this manuscript, we take advantage of multi-temporal and multi-source satellite imagery, incorporating SAR (Sentinel-1 and ICEYE-X) and optical data (Sentinel-2/3 and Landsat-8/9), to provide insights into the spatio-temporal variations of oil spills. We also analyze the impact of met–ocean conditions on oil drift, focusing on two specific scenarios: marine floating oil slicks off the coast of Qatar and oil spills resulting from a shipwreck off the coast of Mauritius. By overlaying oils detected from various sources, we observe their short-term and long-term evolution. Our analysis highlights the finding that changes in oil structure and size are influenced by strong surface winds, while surface currents predominantly affect the spread of oil spills. Moreover, to detect oil slicks across different datasets, we propose an innovative unsupervised algorithm that combines a Bayesian approach used to detect oil and look-alike objects with an oil contours approach distinguishing oil from look-alikes. This algorithm can be applied to both SAR and optical data, and the results demonstrate its ability to accurately identify oil slicks, even in the presence of oil look-alikes and under varying met–ocean conditions. Full article