This PDF file contains the front matter associated with SPIE Proceedings Volume 12728, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Estimating water quality variables from satellite images requires an accurate estimation of the water reflectances (ρ_w) which mainly depends on the performance of the atmospheric correction applied. The highly turbid waters of the Río de la Plata estuary represent a challenge and an ideal scenario to test atmospheric correction algorithm performance. In December 2021 the hyperspectral radiometer HYPSTAR (HYperspectral Pointable System for Terrestrial and Aquatic Radiometry) with a pointing system and auxiliary sensors has been deployed at the end of a 1.1 km long jetty in the turbid waters of Río de la Plata, 60 km south of Buenos Aires (Argentina). This site is strategically located between a water intake and the active commercial harbour of La Plata city where intense phytoplankton blooms (including toxic Cyanobacteria) have been recorded frequently since 2020 presenting human health risks and causing temporal problems to the water intake site. The MultiSpectral Instrument (MSI) on board of Sentinel-2 mission provides high spatial resolution data which can be relevant for monitoring water quality parameters, like turbidity and chlorophyll-a concentration, around this site. In this study six month of automated hyperspectral in situ observations have been used to evaluate the standard Sen2Cor (SNAP) and the alternative DSF (ACOLITE) atmospheric correction algorithms for MSI. Furthermore, using in situ measurements collected during several field campaigns, a global turbidity algorithm and regionally tuned chlorophyll-a algorithms for S2/MSI bands have been evaluated and then applied to the S2/MSI time series showing its potential for water quality monitoring.

High-quality satellite-based ocean color products derived from Sentinel-2/MSI and Sentinel-3/OLCI provide valuable support and insights in the management and monitoring of coastal ecosystems. The primary ocean color variable is the spectral Remote Sensing Reflectance (RRS), obtained after applying atmospheric correction (AC) on satellite products. AC algorithms, such as C2RCC and ACOLITE/DSF are all well capable of generating RRS products over coastal waters. The question of which approach to choose is important and not obvious, especially considering different water (e.g. turbid, clear or CDOM rich waters) and atmospheric conditions (e.g. sun glint, low sun angles) which can occur in coastal waters. To improve the operational ability to achieve high quality RRS spectra for a maximum number of pixels and yet retain the ability to deal with both unusual water conditions and challenging atmospheric conditions, we present the merged use of two algorithms: C2RCC and ACOLITE/DSF. Combining the two approaches yet required a comprehensive, region independent and pixel-based automatic switching scheme, along with a technique for achieving a seamless transition between the two algorithms. We here used the green-NIR ratio, which offers a clear indication of the saturation of the C2RCC outputs for the most reflective band (i.e., the RRS560), at a level where ACOLITE/DSF typically performs accurately, combined with a weighted transition between the two methods. The approach was applied to both Sentinel-2/MSI and Sentinel-3/OLCI products and validated using autonomous WATERHYPERNET stations located in Oostende (RT1, Belgium) and Venice (AAOT, Italy), showing an improved quality of the RRS products compared to using the ACs independently. The best results are obtained for the merged approach in the bands 443nm to 709nm for both Sentinel-2/MSI (<21% MAPE with a 0.004 RMSD and slopes between 0.93 and 0.98) and Sentinel-3/OLCI (<23% MAPE with a 0.003 RMSD and slopes between 0.91 and 0.98) which have generally the highest reflectance range, and which are generally of interest to retrieve turbidity in low to moderately turbid waters.

The loss of satellite data over water because of sun glint contamination represents a high cost financially and scientifically. Although many glint removal algorithms have been developed, glint contamination can remain problematic, especially in turbid waters. In the present study, we propose a correction for sun glint in turbid waters in the absence of SWIR bands. This method could for example be applied to imagery from the Pléiades and Planetscope constellations. Our method has been developed and tested using (1) in situ multi-angle measurements of surface reflectance collected with a PANTHYR autonomous hyperspectral radiometer deployed near Ostend, and (2) a set of metre-scale Pléiades stereo imagery taken in the Belgian coastal zone, with one image of the stereo pair looking into the sun glint and one looking away from the sun glint. The method uses combinations of spectral bands for which a linear relationship is observed in water reflectance, and a constant band ratio for glint reflectance directly calculated from the glinted image. To be adapted to a high range of turbidity conditions, a switching approach between band combinations is used. Glint removal correction was successfully applied in association with the ACOLITE Dark Spectrum Fitting (DSF) atmospheric correction. Results show a good performance in terms of glint removal, and the average overestimation is reduced to less than 20 % in visible bands.

We report remote detection of oil using a flash Raman lidar system. The utilization of an expanding laser beam and an intensified CCD camera enabled the wide field-of-view observation, capturing the whole scene simultaneously. The second harmonic of a standard Q-switched Nd:YAG laser (532 nm) provided the illumination of the water and oil samples separately prepared under atmospheric conditions. We demonstrated the possibility of remote flash Raman lidar measurements using the interference filters at the water (649 nm) and oil (623 nm) Raman wavelengths.

A hyperspectral lidar system (HSL) dedicated to underwater detection is studied. Using a white light laser combined with a tunable filter as a light source, the integrated detection of ranging information and spectral information of underwater targets is realized. The system has the echo detection capability of 160 channels in 450nm-610nm wavelength, and the spectral resolution is 10nm. Substance differentiation was achieved by testing different underwater targets, including sponges, ferromanganese crusts, titanomagnetite, and apatite. The underwater application of hyperspectral lidar is initially explored.

In this study, CO₂ Raman lidar for marine drone installation is focused. Greenhouse gases such as CO₂, CH₄, N₂O, CFC cause serious global warning. Greenhouse gas mission trading is undergoing, while the new technology of Carbon Dioxide Capture and Storage; CCS is expected. CO₂ gases comes for human activity is stored in the seabed. There, gas leakage becomes problem. It will seriously influence to the surrounding ecosystem. To examine and evaluate the CO₂ concentration in seawater, Drone-based CO₂ Raman lidar is designed. Raman shift of CO₂, 1383/cm, is utilized for this purpose. To install the lidar optics into a marine drone, we designed the fiber-delivered transmitting and receiving optics. The laser system and receiving devices includes all electronics are on a vessel and the transmitting beam and receiving light are delivered to the drone via optical fibers. We conducted the fundamental experiment of Raman scattering signal detection under pure water and seawater with CO₂ gas of 100 – 5000 ppm concentration. The 3rd harmonic Nd:YAG laser of 355nm wavelength is used for incident beam. Its intensity changed from 1mJ to 60mJ. The detector is the spectrometer with electrically cooled ICCD camera. We get the successful linear relationship between Raman signal intensity and CO₂ gas concentration. Under the acknowledge of this fundamental experiment, we designed the drone-based CO₂ Raman lidar. The optics design is followed to the restriction of the casing of the marine drone. The output optical power is estimated with the coupling efficiency 70% of multi-mode UV optical fiber.

In certain areas of the world with large tidal ranges, rain and wind can cause the path of channels and estuaries to shift dramatically. Lifeboat rescue services must navigate through these areas in spite of the dangers it can entail. This work investigates the alternatives to provide regular mapping of the seabed, enabling these teams to reach casualties without becoming casualties themselves. Underwater Vehicles, SONAR systems and Unmanned Aerial Vehicles are all considered viable options but satellites equipped with synthetic aperture radar are proven to be the most advantageous. To map the path of the estuary, images must be taken during low tide, therefore, data availability is assessed by studying the revisit time and matching this to the tidal status of the area of interest. Different satellite options are examined, including commercial and non-commercial but a specific focus is given to Sentinel-1 due to its free accessibility. The periodicity of the satellite coupled with the tidal behaviour causes intervals during the month where no usable images can be taken. The maximum number of days between consecutive useful images is found to be 12, with an average of 6 useful images per month. The periods where these intervals happen are also identified. Therefore, to meet the user needs, an auxiliary system must be implemented to assist the satellite and increase the number of useful images taken per month. The area of interest of this study is the Solway Firth due to its fast tidal movements and ranges.

Space Coast Florida satellite and airborne multispectral and hyperspectral imagery hold the potential for discrimination of bottom features in water bodies. Automated bottom feature extraction techniques range from Principal Component Analysis (PCA), Discriminant Analysis and Canonical Correlation as well as the well know Minimum Noise Fraction (MNF) that is related to PCA. Application of these multivariate methods can be performed to reduce the dimensionality of the imagery (bands) as well as spatial (pixel) noise reduction and spectral noise reduction. The techniques can also help reduce spectral band intercorrelation. The MNF methods can thus be used for band selections or channels that contain known geophysical phenomena, such as “bottom type features” when used with ground validation or field sampling methods. Following application of the above noise reduction methods the selected bands can be used with feature analysis methods to perform training of neural network or artificial intelligent algorithms using selected pixel (raster data) in order to perform the creation of vector-based areas or regions based upon spectral shape similarity as demonstrated to select submerged water feature areas.

The new generation of spaceborne hyperspectral sensors offers the potential to provide new information on water quality, especially regarding phytoplankton groups. While phytoplankton species composition algorithms are easily demonstrated in model studies, the application of algorithms to spaceborne data may be much more challenging because of processing artefacts in the spectral vicinity of atmospheric absorption features. If not treated carefully, the unresolved spectral variability of radiance and irradiance can create spectral artefacts (“wiggles”) in water reflectance spectra with high second derivative and thus contaminates pigment detection algorithms. In this study one of the processes generating such spectral wiggles is explained for an in situ radiometer system with a wavelength offset between the radiance and irradiance measurements. The two measurements used to calculate reflectance are differently affected by narrow, unresolved atmospheric absorption bands. Removal or reduction of such wiggles could be achieved by physically-based weighting in the spectral interpolation of irradiance rather than the typical spectral averaging generally used to hide such problems when using linear interpolation. Although demonstrated here for in situ radiometry the need for careful treatment of unresolved spectral variability in spaceborne data is raised, particularly if such data is used for second derivative algorithms which are very sensitive to short wavelength scale variability.

Increased industrialization, urbanization, and population pose problems of wastewater disposal and pollution of oceanic and inland waters. The main contaminants in water include bacteria, viruses, parasites, fertilizers, pesticides, drugs, nitrates, phosphates, plastics, fecal waste, and even radioactive substances. Due to these contaminants, sensors have been implemented to monitor the physical, biological and chemical properties of water, in order to guarantee the protection of water resources and the health of the population in a given territory. However, this monitoring of the water is carried out with wired sensors or the use of acoustic communication that affects the marine fauna that inhabits the monitoring area. Therefore, the interest of this article is to monitor water quality from the implementation of a network architecture of mobile and static sensors, which use LoRa technology and radio frequency identification (RFID) at a frequency of 125 kHz, to be implemented in salt water. Said architecture implements mobile nodes that, when moving in the study area, monitor the water. When they are within a meter of the static nodes, they send the data to the static nodes for further analysis. In this way, data is obtained regarding the quality of the water, without affecting the fauna of the place. Likewise, the distance for data reception of the proposed architecture may be greater in marine environments if the characteristics of the RFID technology to be used are modified.

Above-water spectral measurements are a critical component of ocean remote sensing and provide essential information for validating and improving remote sensing algorithms for water quality analysis. The downwelling irradiance (Es) is an essential component of above-water spectral measurements and it is particularly important for water constituent concentration, sea surface temperature, and atmospheric correction algorithms. The atmosphere particles scatter and absorb the direct and diffusive components of the downwelling irradiance, creating a complex and distorted spectrum. We analyzed 6 years of the above-water hyperspectral measurements collected every 15 minutes at the Royal Netherlands Institute for Sea Research (NIOZ) Jetty Station (JNS) installed in the Marsdiep tidal inlet of the Dutch Wadden Sea. The minimum level of solar irradiance and spectral shape of Es(λ) were simulated using Radiative Transfer (RT) to identify optimal Es spectra that could be favorable for remote sensing applications. The RT models were adjusted for the study area using in-situ bio-optical measurements. The spectrum of Es(λ) at the 3-optical depths were simulated to identify the minimum level of Es(λ). The red-shifted spectrum of Es(λ), caused by intense atmospheric scattering and the reddish hue of dusk or dawn radiations, was identified by Support Vector Machine applied to the simulated Es(λ) components. The results indicated that the maximum spectral value of Es(λ)_max <= 25 mW m^-2 nm^-1 identifies the minimum level of above-water solar irradiance, and the ratios of Es(480)/Es(680) ≤ 1 mW m^-2 nm^-1 and Es(λ)_max/Es(865) ≤ 1.25 mW m^-2 nm^-1 show the red-shifted spectra.

Through the combination of active and passive detection, the marine science mission will realize the integrated remote sensing of marine dynamic and ecological parameters, fill the gap of sub-mesoscale perspective observation, and take a key step toward three-dimensional remote sensing of "transparent ocean". The satellite will operate in a sun-synchronous orbit and will be equipped with lidar and a light-weighted multispectral camera. Among them, the camera has 8 multispectral bands with a spatial resolution of 20m and a width of 160km. In this paper, the simulation calculation of the sun glints area is carried out for the two installation methods, which are formal and oblique, and the four typical simulation time nodes are spring equinox, summer solstice, autumn equinox, and winter solstice. The results show that the proportion of single-track sun glints area on the summer solstice is about 37.5% and 34.0%, respectively, which is the highest time point of the year, and the equator, tropic of Capricorn and tropic of cancer regions will produce 100% of the sun glints area at different time points. Compared with the formal form, the total proportion of sun glints area is reduced by about 10% for the oblique form, which will improve the effective data rate in orbit and improve the efficiency of satellite imaging. At the same time, this paper briefly describes the satellite calibration mode according to the combination of active and passive imaging. It will guide the subsequent satellite design and application.

This study collects phytoplankton absorption and chlorophyll a data and examines their correlation in coastal waters around China measured between 2003 and 2017. Single-parameter model is built to construct phytoplankton absorption from pigment concentration. Gaussian decomposition technique extracts center wavelengths and bandwidths of 13 Gaussian functions, which constitute the modified Gaussian model, or so-called multiple-parameter model. Both models can reproduce measured phytoplankton absorption very well. In terms of the mean absolute relative error, single-parameter model can reproduce measured absorption within 30% and 60% between 380nm and 700nm for 40% and 75% of data, respectively. Meanwhile, multiple-parameter model can reproduce measured absorption within 15% for 80% of data, and within 20% for the majority of wavelengths between 380nm and 700nm.

Space Coast Florida waters consist of shallow coastal turbid water along the southeastern United States and Florida’s east coast estuaries and tidal lagoon systems. The waters have become dominated by a bottom boundary sediment layer characterized by moving fluid mud near the bottom. Surface winds and their resulting water surface gravity waves result in the resuspension of the mud bottom boundary layer sediments and result in water columns with very low light visibility. The decreased light penetration as a function of depth and wavelength influences marine life that require light to function. The complex physical phenomena and associated underwater light fields can best be understand using Monte-Carlo models. Model results can be tuned to be applicable to specific satellites and channels for development of algorithms which make use of reflectance signatures measured by satellites as well as in-situ sensors. Recent model developments and model simulations are described with reference to WorldVeiw-3 satellite imagery and shape factors.

Access to free high resolution satellite imagery and open-source software provides a cheap, continuous and effective method of coral reef monitoring, providing a substitute for expensive field monitoring. A time series analysis of the Kenyan coastline is carried out with images from Landsat 8 and Sentinel 2 for the time period of 2013 to 2021. These images are processed for benthic classification, change detection, chlorophyll-a and total suspended matter. This provides information on bleaching events experienced in the area over time, whilst giving an insight on how various stressors impact the rates of bleaching and recovery different sites.

Chlorophyll-a is an Essential Climate Variables in the global climate observation system, and thus it’s necessary to have long-term time series data without any gaps. Composite images are commonly produced by merging ocean-color satellite images from near-polar orbiting satellites or compositing over periods of more than 8 days. In this study, we generated chlorophyll-a daily composite data using a production method based on remote sensing reflectance of a multi-near-polar orbiting ocean color satellite, a technique provided by the European Space Agency Climate Change Initiative. In contrast to the European Space Agency Climate Change Initiative products based on multi-near-polar orbiting ocean color satellite sensors such as VIIRS, MODIS and OLCI, we used the GOCI (500 m resolution) and GOCI-II (250 m resolution) sensors on a geostationary satellite. These sensors can monitor around the Korean Peninsula eight to ten times per day. We merged remote sensing reflectance of five sensors at 443, 490, 510, and 555 nm between 01 and 05 UTC and applied the OC4 (Four-band Ocean Color) algorithm. Using this method, we compared the results of detecting a red tide event on the west coast of the East Sea in August 2013 using a single GOCI data and the OC-CCI data (4 km resolution).

The maritime safety and security of coastal regions is a crucial concern impacted by the dynamic growth and erosion processes shaping these areas. Coastal erosion can pose a safety risk to people living or working in these areas and the tourism industry. Furthermore, erosion can include hazards to maritime infrastructure, such as piers, ports, and other facilities, as well as to shipping and navigation in the area. Problems that can be identified from coastal erosion and accretion are changes in water depth, unpredictable currents, displacement of buoys and markers, increased risk of vessel grounding as well as changes in shoreline characteristics that can affect the direction and intensity of wind and waves, making it difficult for ships and boats to navigate safely. This paper uses Sentinel 1 satellite data to monitor Coastal Erosion patterns along the Southeast Cyprus coastlines. The findings of this study could help manage coastal resources and improve maritime safety and security in Cyprus. This study thereby contributes to the broader body of knowledge concerning coastal erosion monitoring using satellite-based remote sensing data, explicitly emphasising the application of Sentinel-1 SAR imagery. The study's methodologies and findings provide valuable insights that can be extended to other similar coastal regions in Cyprus.

Maritime surveillance plays a critical role in ensuring the safety and effective management of maritime activities. This study focuses on the use of Sentinel-1 Synthetic Aperture Radar (SAR) data for marine surveillance in Cyprus which offers all-weather imaging capabilities and enables monitoring of marine activities such as vessels detection, oil spill detection and wind speed direction. Also, the study includes the import and pre-processing of SAR data in the SNAP (Sentinel Application Platform) software as well as the application of advanced algorithms and techniques where vessels detection, oil spill detection on the water surface and wind speed and direction can be derived. Therefore, the results of this research have significant implications for maritime safety assessment, environmental protection and resource management in Cyprus. The use of Sentinel-1 SAR data for maritime surveillance in Cyprus enhances the island-wide surveillance capability to detect potential threats and to respond immediately.

Through the creation of a polar digital space and the data architecture in it, an attempt will be made to get as close as possible to the real possibilities of building a Digital Twin in the Antarctic or the polar region, and also to propose the European data policy in the Antarctic and the Arctic. The polar digital space www.destination-earth-antarctica.eu even local to Livingston Island will help to tackle complex environmental challenges by observe and simulate the development of the earth system (land, sea, atmosphere, biosphere) and human intervention; forecasting of environmental and extreme disasters and resulting crises, enable the development and testing of scenarios for increasingly sustainable development. These are great initiatives, but they need to accumulate data. Livingstone Island during the Antarctic summer has an extreme increase in human presence, but this is not necessarily a negative impact. Rather, it is necessary to track exchange and summarize data on any type of event in a timely manner. A differentiated monitoring approach has been used and hybrid monitoring models have already been created1. The data sources and instruments at many of the Antarctic bases are not interoperable, and this creates a major problem for comparison and simulation modeling even on a single island, let alone a larger area or the Antarctic mainland. In most of the polar summer, the optical data is not of good quality due to the presence of frequent cloud cover. This necessitates the mandatory use of in situ data in order to verify the others. The purpose of this type of research is to enforce certain standards for data dissemination such as Open Data, Open Science, and also to show the dynamics of certain territories on Livingstone Island based on research from the summer of 2022-2023 through various methods, indеxes Modified Soil-Adjusted Vegetation Index (MSAVI2), Normalized Differential Glacier Index (NDGI), Normalized Difference Water Index (NDWI), NDSI (Normalized Difference Snow Index), NDSII (Normalized Difference Snow and Ice Index, Moisture Stress Index (MSI). and SAR indexes. The data used are from a drone, in situ data from a SEKONIC spectrometer, data from a ground local weather station, GPS coordinates and satellite data A ground weather station AWG, powered by an environmentally friendly magnesium-air battery, was developed especially for a project of the Bulgarian Antarctic Base. The data and models will serve the Bulgarian initiative for the construction of the Digital Twins in Antarctica and Arctica or Digital polar space, which is being pilot developed in the department of Aerospace Information, Space Research and Technology Institute – Bulgarian Academy of Sciences.

Long-term monitoring of Water Constituent Concentrations (WCCs) is essential for water quality assessment in coastal waters, a priority for various government agencies and environmental organizations. However, utilizing satellite observations to track the extended spatial and temporal variations of WCCs, including Chlorophyll-a (Chla), Suspended Particulate Matters (SPMs), and Coloured Dissolved Organic Matters (CDOMs), remains challenging in coastal waters due to their optical complexity and the need for accurate atmospheric correction. In this study, we examined two decades of spatial and temporal variations in Chla [mg m^-3], SPM [g m^-3] concentrations, and CDOM absorption at 440nm [m^-1] using time series data from the Medium Resolution Imaging Spectrometer (MERIS) and the Ocean and Land Colour Instrument (OLCI) spanning from 2003 to 2023. Our research focused on the complex, shallow, and highly turbid waters of the Dutch Wadden Sea, the Netherlands. To achieve this, we employed a coupled atmospheric and water optical model known as MOD2SEA, enabling simultaneous atmospheric correction and WCC retrievals from MERIS images (2003-2012) and OLCI images (2018-2023) in the study area. Our findings reveal that SPM and CDOM variations followed a consistent seasonal pattern over the two-decade period, with SPM values ranging from 10 [g m^-3] to 60 [g m^-3] and CDOM absorption varying from 0 [m^-1] to 0.8 [m^-1]. Chla estimates, on the other hand, displayed a different trend, ranging from 5 [mg m^-3] to 25 [mg m^-3] until 2013. Subsequently, Chla concentrations increased, reaching 45 [mg m^-3] by 2023.

In recent years, more and more attention has been focused to the pollution of the seas and oceans with plastic waste. It is no coincidence that monitoring and prevention activities and measures to reduce the pollution of seas and oceans with plastic waste occupy a major role in the EU Marine Strategy Framework Directive (EU MSFD). In accordance with Descriptor 10, plastic waste must be monitored, collected and reported regularly at European Union level. This paper represents possibilities for monitoring of plastic waste on the sea surface, using aerial drones equipped with thermal and multispectral cameras.

The monitoring, sampling and mapping of plastic waste in the water column and on the sea bottom represents a serious challenge for both responsible government authorities and scientific researchers. Typically, these activities are performed by divers equipped with the necessary recording equipment and special breathing mixtures when working at depths greater than 30 meters or more. The complexity, risk, respectively budget and time required for deeper diving increases due to the neediness of complying with safety of life and diving decompression procedures. This paper represents an approach of using underwater drones (ROV) for monitoring, sampling and mapping of plastic waste in the port aquatories, coastal zone and sea bottom.