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A group of 38 experts specializing in hyperspectral remote-sensing methods for aquatic ecosystems attended an interactive Euromarine Foresight Workshop at the Flanders Marine Institute (VLIZ) in Ostend, Belgium, June 4–6, 2019. The objective of this workshop was to develop recommendations for comprehensive, efficient, and effective laboratory and field programs to supply data for development of algorithms and validation of hyperspectral satellite imagery for micro-, macro- and endosymbiotic algal characterization across the globe. The international group of researchers from Europe, Asia, Australia, and North and South America (see online Supplementary Materials) tackled how to develop global databases that merge hyperspectral optics and phytoplankton group composition to support the next generation of hyperspectral satellites for assessing biodiversity in the ocean and in food webs and for detecting water quality issues such as harmful algal blooms. Through stimulating discussions in breakout groups, the team formulated a host of diverse programmatic recommendations on topics such as how to better integrate optics into phytoplankton monitoring programs; approaches to validating phytoplankton composition with ocean color measurements and satellite imagery; new database specifications that match optical data with phytoplankton composition data; requirements for new instrumentation that can be implemented on floats, moorings, drones, and other platforms; and the development of international task forces. Because in situ observations of phytoplankton biogeography and abundance are scarce, and many vast oceanic regions are too remote to be routinely monitored, satellite observations are required to fully comprehend the diversity of micro-, macro-, and endosymbiotic algae and any variability due to climate change. Ocean color remote sensing that provides regular synoptic monitoring of aquatic ecosystems is an excellent tool for assessing biodiversity and abundance of phytoplankton and algae in aquatic ecosystems. However, neither the spatial, temporal, nor spectral resolution of the current ocean color missions are sufficient to characterize phytoplankton community composition adequately. The near-daily overpasses from ocean color satellites are useful for detecting the presence of blooms, but the spatial resolution is often too coarse to assess the patchy distribution of blooms, and the multiband spectral resolution is generally insufficient to identify different types of phytoplankton from each other, even if progress has undeniably been achieved during the last two decades (e.g., IOCGG, 2014). Moreover, the methods developed for multichannel sensor use are often highly tuned to a region but are inaccurate when applied broadly. New orbital imaging spectrometers are being developed that cover the full visible and near-infrared spectrum with a large number of narrow bands dubbed “hyperspectral” (e.g., TROPOMI, PRISMA, EnMAP, PACE, CHIME, SBG). Hyper-spectral methods have been explored for many years to assess phytoplankton groups and map seafloor habitats. However, the utility of hyperspectral imaging still needs to be demonstrated across diverse aquatic regimes. Aquatic applications of hyperspectral imagery have been limited by both the technology and the ability to validate products. Some of the past hyperspectral space-based sensors have suffered from calibration artifacts, low sensitivity in aquatic ecosystems (e.g., CHRIS, HICO), and very low spatial resolution (e.g., SCIAMACHY), but the next generation of sensors are planned to have high signal-to-noise ratio and improved performance over aquatic targets. Providing data to develop and validate hyperspectral approaches to characterize phytoplankton groups across the globe poses new challenges. Several recent studies have documented gaps that need to be filled in order to assess algal diversity across the globe (IOCCG, 2014; Mouw et al., 2015; Bracher et al., 2017), which promoted/inspired the formation of this workshop.

COVID-19 lockdown brought to a drastic reduction of anthropic impacts on the environment worldwide, including the marine-coastal system. Earth-Observation (EO) data have the potential to monitor and diagnose the effects of the lockdown in terms of water quality. Here we connect the dots among some coastal environmental changes that occurred during the Italian COVID-19 lockdown by using EO data, also seeking to assess connectivity between inland and marine systems. We present a holistic analysis of spatial and temporal variability of environmental parameters in the North Adriatic Sea, Mediterranean basin, exploiting the synergy of different satellite sensors, as well as hydrologic data from in situ observations. Our analysis indicates a favourable interplay of environmental variability that resulted in negative anomalies of Chlorophyll-a concentration, with respect to the climatologic values. Peculiar meteo-oceanographic and hydrological conditions made hard to disentangle potential anthropogenic effects. However, a multi-year hierarchical cluster analysis of riverine remote sensing reflectances groups together the optical properties of inland waters during the lockdown. This emergent cluster highlights the possibility of a second-order, anthropogenic effect that, superimposed to the (first-order) environmental natural causes, may have enhanced water quality during the lockdown., Graphical abstract Unlabelled Image

Particle scattering is an important process that determines both the light penetration through the water column and water-leaving light. Backscattering, in combination with absorption, determines the remote-sensing reflectance that is used in ocean color algorithms. Additionally, the wavelength dependence of the backscattering ratio can be related to the particle composition in seawater. Here, we examine the magnitude and the spectral behavior of the backscattering ratio against other bio-optical properties based on a comprehensive set of continuous measurements collected in coastal waters of the Great Barrier Reef over 3 years. The site is located offshore of a major river, and close to the cross-shelf transition of bottom sediments from terrigenous muds to marine carbonates. The backscattering ratio measured at 650 nm clearly clustered the data into two types. Type 1, which we identified as terrigenous mud with a low organic fraction, is characterized by backscattering ratio below 0.011 with a mean value of 0.005. Type 2, which we identified as marine carbonate with a higher organic fraction, has backscattering ratio above 0.011 with a mean value of 0.02. Within 3 years, study site was exposed to type 1-dominated particles 13% of the time, and type 2 87%. The observed changes in the backscattering ratio at this one coastal site are as large as the variability seen throughout the global ocean. This work provides a better understanding of processes determining the optical characteristics and insights into optical parameterizations that can be used in process-based optical modeling of the Great Barrier Reef.

COVID-19 lockdown measures brought to a drastic reduction of anthropic impacts on the environment, including the marine-coastal system. EO data have the potential to monitor and diagnose the subsequent effects of the lockdown in terms of water quality. The ESA-RACE project SOON aims to link complex patterns that may arise from the environmental changes due to COVID-19 lockdown by using EO data, also seeking to assess connectivity between inland and marine system. Within this frame, here we present a holistic, satellite-based analysis of the spatial-temporal variability of environmental parameters in the North Adriatic Sea (NAS; Mediterranean basin), exploiting the synergy of OC and SST products from different sensors, as well as in situ hydrologic data. Our analysis indicates a favorable interplay of environmental variability and reduction of anthropogenic activity that results in negative anomalies of Chlorophyll-a and Total Suspended Matter with respect to the climatologic values.

This study presents an assessment of PRISMA (PRecursore IperSpettrale della Missione Applicativa) for water applications, by including a general description of the mission and by focusing on the standard Level 1 (L1) and Level 2 (L2) products acquired on different aquatic systems. A preliminary analysis on the estimation of signal-to-noise ratio (SNR) from L1 PRISMA products in the visible near infrared spectra (VISNIR) is indicating values comparable to Sentinel-2 MSI from literature, apart at short wavelengths where PRISMA SNR is lower. Few examples of L2 products in terms of water reflectance are also presented to encourage the exploitation of PRISMA for aquatic ecosystem mapping. The results of this study are indicating that even if some applications might be developed with the standard L2 products, an ad-hoc processing might be necessary to include the specific requirements of atmospheric correction of water targets. Further analyses with a higher number of imagery data are however recommended to fully characterize the PRISMA products.

In order to control the spread of the pandemic of Corona-Virus Disease 2019 (COVID-19), lockdowns of various durations and intensities have been established in many countries over the world all through the year 2020. The trilateral dashboard jointly implemented by NASA, JAXA and ESA aims at exploiting remote-sensing data to evaluate the impact of these restrictions, and subsequent recovery phases on many different environmental, agriculture and economic indicators. More specifically, this paper presents the indicators implemented to monitor the impact of COVID-19 restrictions on Water Quality, together with preliminary analysis results over a few Areas of Interest.

Multiple approaches have been used by the Ocean Colour community for validating satellite-derived products using in situ data, with most of them derived from mainly two approaches, one suggested by Bailey and Werdell (2006) (BW06) and one suggested by Zibordi et al. (2009a) (Z09), each with a different set of quality checking and spatiotemporal collocation criteria. The question remains what sort of information is added or missed when choosing one over the other. In this work, the differences among validation approaches were determined by using a common dataset of in situ and satellite data. The match-up exercise was separated into two groups of datasets based on the spatial resolution of the sensors to be validated. Sentinel-3A/OLCI data were selected as a representation of medium spatial resolution sensors, and two validation approaches were selected to this match-up dataset. The high spatial resolution sensors were represented by Sentinel-2A/MSI data, and three validation approaches were tested. Data from the AERONET-OC network were chosen as the common in situ dataset. For Sentinel-3A/OLCI, the number of match-ups varies depending on the validation approach used. Bailey and Werdell (2006) produces 20% more match-ups for Sentinel-3A/OLCI due to its more relaxed filtering criteria compared to the criteria applied by Zibordi et al. (2009a) . The validation metrics vary between different validation methods giving a different impression of accuracy of the satellite products. Also, the satellite data selected by BW06 have a statistical distribution with a higher median and standard deviation when compared to Z09. Similar findings are also confirmed for the match-up analysis conducted for Sentinel-2A/MSI. Therefore, although a common reference dataset was used, the validation statistical results were influenced by the validation approach selected. This does not suggest that one validation protocol is better than the other, but it implies that validation statistics reported in different studies may not always be directly comparable. Additionally, it was determined that BW06 could be a better fit when trying to obtain a sufficient number of match-ups for calibration purposes in the shortest time.

This work describes a continuous sampling system that has been designed, implemented, and tested for the acquisition of Inherent Optical Properties (IOPs) during field campaigns. The major challenge of the work was to design and build a flow-through housing accounting for the complex sensing geometry of the ECO-VSF3, a backscattering meter, i.e., three sensor heads each of which measures the VSF at three angles. A detailed characterization of the ECO-VSF3 housing in terms of impact of the boundaries and overall system inertia is reported. A key feature of the system design is the possibility to easily detach the IOP package from the flow-through hydraulic circuit and use it in cast mode at fixed stations. This, to the best of authors' knowledge, is the first time the ECO-VSF3 is used in an underway system. Results from the comparison of continuous (Co) and cast (Ca) bb measurements show excellent agreement, with differences not exceeding 7%, thus proving the system to be reliable and highlighting the feasibility for increasing the spatio-temporal sampling of surface observations.

The lagoon of Venice has always been affected by the regional geomorphological evolution, anthropogenic stressors and global changes. Different morphological settings and variable biogeophysical conditions characterize this continuously evolving system that rapidly responds to the anthropic impacts. When the lockdown measures were enforced in Italy to control the spread of the SARS-CoV-2 infection on March 10th 2020, the ordinary urban water traffic around Venice, one of the major pressures in the lagoon, came to a halt. This provided a unique opportunity to analyse the environmental effects of restrictions to mobility on water transparency. Pseudo true-colour composites Sentinel-2 satellite imagery proved useful for qualitative visual interpretation, showing the reduction of the vessel traffic and their wakes from the periods before and during the SARS-CoV-2 outbreak. A quantitative analysis of suspended matter patterns, based on satellite-derived turbidity, in the absence of traffic perturbations, allowed to focus on natural processes and the residual stress from human activities that continued throughout the lockdown. We conclude that the high water transparency can be considered as a transient condition determined by a combination of natural seasonal factors and the effects of COVID-19 restrictions., Graphical abstract Unlabelled Image, Highlights • Lockdown measures in Venice restricted the mobility and stopped boat traffic, with a consequent decrease of wake waves. • An unprecedented water transparency in the city canals was determined by the absence of local boat traffic, however turbidity remained at usual levels in wind conditions. • Essential activities like fisheries and port traffic continued through the lockdown period thus revealing the extent of their impact on the lagoon ecosystem.

Inherent optical properties (IOPs) and concentrations of the sea water components are key quantities in supporting the monitoring of the water quality and the study of the ecosystem functioning. In coastal waters, those quantities have a large spatial and temporal variability, due to river discharges and meteo-marine conditions, such as wind, wave and current, and their interaction with shallow water bathymetry. This short term variability can be adequately captured only using Geostationary Ocean Colour (OC) satellites, absent over the European seas.In this study, to compensate the lack of an OC geostationary sensor over the North Adriatic Sea (NAS), the Virtual Geostationary Ocean Colour Sensor (VGOCS) dataset has been used. VGOCS contains data from several OC polar satellites, making available multiple images a day of the NAS, approaching the temporal resolution of a geostationary sensor.Generally, data from different satellite sensors are characterized by different uncertainty sources and consequently, looking at two satellite images, it is not easy to ascertain how much of the observed differences are due to real processes. In the VGOCS dataset, the inter-sensor differences are reduced, as the satellite data were adjusted with a multi-linear regression algorithm based on in situ reflectance acquired in the gulf of Venice. Consequently, the use of the adjusted spectra as input in the retrieval of the IOPs and the concentrations allows performing a reliable analysis of the short-time bio-optical variability of the basin.In this work, we demonstrate the suitability of VGOCS to better characterise the river-sea interaction and to understand the influence of the river forcing on the short time variability of IOPs and concentrations in the coastal areas. This variability will be analysed for different case studies characterised by a different regime of river discharges, using meteorological, hydrological, and oceanographic fields as ancillary variables. This new approach and the availability of this new set of data represent an opportunity for interdisciplinary studies, in support to and interacting also with modelling implementations in river-sea areas.

This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013–2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.

Technical advancements have widened the limits of remote sensing in mapping shallow water benthic habitats and bathymetry over the last decades. On the other hand, the needs of shallow water remote sensing have pushed instrument development. In this manuscript we provide 50-year retrospective of the developments in the field in terms of both instrumentation and methods. We also show that spectral features characteristic of the main benthic groups in shallow water are consistent from the tropics to sub-arctic regions and from salty to freshwaters. The fundamental limiting factor in both benthic mapping and bathymetry is absorption of light by water molecules. However, spectral absorption by water molecules is the key to bathymetry derivation. Variable backscattering by particles and absorption by dissolved organic matter is a confounding factor for all objectives. The combination of using the spectral and textural characteristics of bottom features and our knowledge about these features have now resulted in the ability to map habitats over large coastal systems. This manuscript has shown that optically shallow water remote sensing has reached levels where the satellite derived bathymetry and habitat maps are accepted by different end users (including the International Maritime Organisation) and are routinely used in ecological studies, monitoring and management of coastal environments.

New applications on global-scale plankton retrievals using the CALIOP (Cloud-Aerosol Lidar with orthogonal Polarization) lidar measurements on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite recently suggested that space-based lidars could provide information about the depth distribution of optical scattering. Assessing the oceanic surface layer’s optical properties through CALIOP is one of the reasons of the extension of the CALIOP mission for another 3 years (2018-2020). The objective of this work is the evaluation of the potential CALIOP ocean products in the Mediterranean and Black seas using the ocean color products provided by the Copernicus Marine Environment Monitoring Systems (CMEMS).

In frame of the European Space Agency’s (ESA) “FLEXSense Campaign 2018” and the Copernicus Marine Environment Monitoring Service (CMEMS) project, the Global Ocean Satellite monitoring and marine ecosystem study group (GOS) of the Italian National Research Council (CNR) organized the oceanographic cruise “FLEX 2018”. The CNR research vessel “Dallaporta” provided a ground station for several bio-optical instruments to investigate the coastal waters of the Tyrrhenian Sea (central Italy) in June 2018. The field measurements were performed in time synchrony with spaceborne (i.e. Sentinel 3A and Sentinel 3B satellites) and airborne (i.e. HyPlant airborne imaging spectrometer) observations, with the intent to contribute to calibration/validation activities for existing and future space mission developments. Particularly, active and passive fluorescence were investigated at different scales in aquatic ecosystems, to support preparatory activities of the FLuorescence EXplorer (FLEX) satellite mission to be launched in 2022. Results provide new insight on the sensitivity of Solar Induced Fluorescence (SIF) retrievals for atmospheric disturbances and other scale related aspects, and will eventually facilitate the implementation of robust retrieval schemes for the FLEX mission products. In addition, active fluorescence signals acquired from a LIDAR fluorosensor show a good agreement with SIF pattern retrieved by HyPlant and Sentinel-3 Ocean and Land Colour Instrument (OLCI). Our results demonstrate that the combination of active and passive fluorescence, together with the synergistic measurements from integrated platforms, is a promising approach to support the retrieval and interpretation of SIF in aquatic environments.

Remote sensing observations show optical signatures to conform to the physical oceanographic patterns in the Tasman Sea. To test the link between physical oceanographic processes and bio-optical properties we investigated an in situ bio-optical dataset collected in the Tasman Sea. Analysis of in situ observations showed the presence of four different water masses in the Tasman Sea, formed by the relatively warm and saline East Australia Current (EAC) water, a mesoscale cold core eddy on the continental slope, cooler Tasman Sea water on the shelf and river plume water. The distribution of suspended substances and their inherent optical properties in these water masses were distinctly different. Light absorption and attenuation budgets indicate varying optical complexity between the water masses. Specific inherent optical properties of suspended particulate and dissolved substances in each group were different as they were influenced by physical and biogeochemical processes specific to that water mass. Remote sensing reflectance signature varied in response to changing bio-optical properties between the water masses; thus providing the link between physical oceanographic processes, bio-optical properties and the optical signature. Findings presented here extend our knowledge of the Tasman Sea, its optical environment and the role of physical oceanographic processes in influencing the inherent optical properties and remote sensing signature in this complex oceanographic region.

Assessing the oceanic surface layer's optical properties through CALIOP has been one of the reasons of the extension of the CALIOP mission for 3 more years (2018-2020). This is the first work evaluating the potential use of CALIOP for ocean applications at regional scale in mid-latitude regions (i.e. Mediterranean, MED, and Black Sea, BS) and investigating the added information on ocean particles given by the column integrated depolarization ratio (delta(T)) parameter. We implemented and refined a retrieval procedure to estimate this parameter at 1/4 degree of spatial resolution, comparing 7 years of CALIOP observations (2011-2017) to the corresponding Copernicus multi-sensor L3 ocean colour products of the surface particle backscattering coefficient (b(bp)) and chlorophyll-a concentration (Chl-a). This study pointed out that the current CALIOP sampling is inadequate to detect subtle day-night difference due to plankton diel variability for these basins. At a basin scale, delta(T) covaries with b(bp) for b(bp) >= 0.0015 m(-1). This is more evident for BS (R = 0.84) than for MED (R = 0.61). The analysis of seasonal distributions confirm this result for BS, where dT has a semi-annual cycle in very good agreement with bbp. In the MED, characterized by different trophic regimes, delta(T) shows also some similarities with Chl-a annual cycle. The combined characterization in the MED bioregions of the annual patterns of b(bp):Chl-a, delta(T):Chl-a and delta(T):b(bp) ratios suggested that delta(T) parameter can provide valuable information about the non-sphericity and the size of ocean particles.

This study presents a first assessment of the Top-Of-Atmosphere (TOA) radiances measured in the visible and near-infrared (VNIR) wavelengths from PRISMA (PRecursore IperSpettrale della Missione Applicativa), the new hyperspectral satellite sensor of the Italian Space Agency in orbit since March 2019. In particular, the radiometrically calibrated PRISMA Level 1 TOA radiances were compared to the TOA radiances simulated with a radiative transfer code, starting from in situ measurements of water reflectance. In situ data were obtained from a set of fixed position autonomous radiometers covering a wide range of water types, encompassing coastal and inland waters. A total of nine match-ups between PRISMA and in situ measurements distributed from July 2019 to June 2020 were analysed. Recognising the role of Sentinel-2 for inland and coastal waters applications, the TOA radiances measured from concurrent Sentinel-2 observations were added to the comparison. The results overall demonstrated that PRISMA VNIR sensor is providing TOA radiances with the same magnitude and shape of those in situ simulated (spectral angle dierence, SA, between 0.80 and 3.39; root mean square dierence, RMSD, between 0.98 and 4.76 [mW m􀀀2 sr􀀀1 nm􀀀1]), with slightly larger dierences at shorter wavelengths. The PRISMA TOA radiances were also found very similar to Sentinel-2 data (RMSD < 3.78 [mW m􀀀2 sr􀀀1 nm􀀀1]), and encourage a synergic use of both sensors for aquatic applications. Further analyses with a higher number of match-ups between PRISMA, in situ and Sentinel-2 data are however recommended to fully characterize the on-orbit calibration of PRISMA for its exploitation in aquatic ecosystem mapping.

In the coastal environment the optical properties can vary on temporal scales that are shorter than the near-polar orbiting satellite temporal resolution (~1 image per day), which does not allow capturing most of the coastal optical variability. The objective of this work is to fill the gap between the near-polar orbiting and geostationary sensor temporal resolutions, as the latter sensors provide multiple images of the same basin during the same day. To do that, a Level 3 hyper-temporal analysis-ready Ocean Color (OC) dataset, named Virtual Geostationary Ocean Color Sensor (VGOCS), has been created. This dataset contains the observations acquired over the North Adriatic Sea by the currently functioning near-polar orbiting sensors, allowing approaching the geostationary sensor temporal resolution. The problem in using data from different sensors is that they are characterized by different uncertainty sources that can introduce artifacts between different satellite images. Hence, the sensors have different spatial and spectral resolutions, their calibration procedures can have different accuracies, and their Level 2 data can be retrieved using different processing chains. Such differences were reduced here by adjusting the satellite data with a multi-linear regression algorithm that exploits the Fiducial Reference Measurements data stream of the AERONET-OC water-leaving radiance acquired at the Acqua Alta Oceanographic Tower, located in the Gulf of Venice. This work aims to prove the suitability of VGOCS in analyzing the coastal optical variability, presenting the improvement brought by the adjustment on the quality of the satellite data, the VGOCS spatial and temporal coverage, and the inter-sensor differences. Hence, the adjustment will strongly increase the agreement between the satellite and in situ data and between data from different near-polar orbiting OC imagers; moreover, the adjustment will make available data traditionally masked in the standard processing chains, increasing the VGOCS spatial and temporal coverage, fundamental to analyze the coastal optical variability. Finally, the fulfillment by VGOCS of the three conditions for a hyper-temporal dataset will be demonstrated in this work.

In coastal areas, the concentrations and the optical properties of the water components have a large spatial and temporal variability, due to river discharges and meteo-marine conditions, such as wind, wave and current, and their interaction with shallow water bathymetry. This large temporal variability cannot be captured using the standard Ocean Colour Radiometry (OCR) polar orbiting satellites, the latter providing almost one image per day. On the contrary, the use of OCR geostationary sensors, like the Geostationary Ocean Colour Imager (GOCI), centred above the Korean Peninsula, enable to capture the short-term variability of the optical properties. To compensate the lack of a geostationary sensor similar to GOCI over other coastal environments, like the North Adriatic Sea (NAS), the multiple observations provided during the same day by the Visible Infrared Imaging Radiometer Suite (VIIRS) mounted on the SUOMI NPP satellite, can be exploited. Indeed, due to its large swath of 3060 km, the VIIRS orbits can overlap over the NAS during the same day within 1 h and 42 min, an important feature that can be useful in capturing the short term variability of the optical properties. A large number of VIIRS overlaps in the NAS are characterized by high sensor zenith angle (SZA) of the observation, resulting in a large portion of images masked by the high satellite zenith flag. In order to make available those observations and, in general, to reduce the dependence of the VIIRS observations from the SZA, an adjustment based on a multi linear regression scheme, which exploits radiometric in situ observations, was here applied. This study aims to prove the suitability of the adjusted overlapping VIIRS in capturing the short time scale dynamics of particulate backscattering, and this was demonstrated by the analysis of a case study for the 21st and 22nd of March 2013. In order to evaluate the advantages in using multiple observations during the same day, also the ~24 h dynamics was analysed, comparing the overlapping VIIRS results with the ones obtained from the daily product.

Satellite imagery provides evidence of complex mixing dynamics in the coastal zone in front of multiple mouth deltas. One peculiar feature, identified in front of the Po Delta (Italy), consists in warmer water bulges present in some periods in the coastal zone between the river mouths. Such features are evident during both high and low river discharge. Through an integrated approach based on the analysis of satellite imagery, in situ field data and a high-resolution oceanographic model, representing the whole river-delta-sea system, we investigated the relative contribution of the different forcing in controlling coastal mixing of riverine waters. The results evidence that the occurrence of these warmer saltier water bulges is due to upwelling induced by the combined action of tides and wind regimes aligned along coastline. Winds from the land and along the coast drive the upwelling through the well-known mechanism described by Ekman. The presence of river discharge enhance the water column stratification, creating the conditions in which tidal action follows the tidal straining theory. Both processes are identified in modelling results. The occurrence of these localized coastal waters with peculiar thermohaline characteristics, detectable on satellite imagery of the area, can be relevant in the definition of the freshwater areas of influence and the mechanisms of riverine water mixing in the near coastal zone. This can shed some light, eventually, on characterizing the sediment dynamics, as well as the thermohaline properties of waters in the area, and also to identify eventual impacts on the local ecosystems and fishery.

Several coastal regions on Earth have been increasingly affected by intense, often catastrophic, flash floods that deliver significant amounts of sediment along shorelines. One of the critical questions related to the impact of these impulsive runoffs is “are flash floods more efficient in delivering non-cohesive sandy sediment along the coasts?” Here we relate flow stages (i.e., from erratic to persistent) to the grain size distribution of the suspended load, by performing a synergic analysis of in-situ river discharge and satellite-retrieved grain size distribution, from 2002 to 2014, covering the 2012 Tiber River (Italy) exceptional flood event. Our analysis shows novel and promising results regarding the capability of remote sensing in characterizing suspended sediment in terms of grain size distribution and reveals that erratic stages favour delivering of non-cohesive sandy sediment more than the persistent stages. This conclusion is supported by numerical simulations and is consistent with previous studies on suspended sediment rating curves.

Imaging spectrometry of non-oceanic aquatic ecosystems has been in development since the late 1980s when the first airborne hyperspectral sensors were deployed over lakes. Most water quality management applications were, however, developed using multispectral mid-spatial resolution satellites or coarse spatial resolution ocean colour satellites till now. This situation is about to change with a suite of upcoming imaging spectrometers being deployed from experimental satellites or from the International Space Station. We review the science of developing applications for inland and coastal aquatic ecosystems that often are a mixture of optically shallow and optically deep waters, with gradients of clear to turbid and oligotrophic to hypertrophic productive waters and with varying bottom visibility with and without macrophytes, macro-algae, benthic micro-algae or corals. As the spaceborne, airborne and in situ optical sensors become increasingly available and appropriate for aquatic ecosystem detection, monitoring and assessment, the science-based applications will need to be further developed to an operational level. The Earth Observation-derived information products will range from more accurate estimates of turbidity and transparency measures, chlorophyll, suspended matter and coloured dissolved organic matter concentration, to more sophisticated products such as particle size distributions, phytoplankton functional types or distinguishing sources of suspended and coloured dissolved matter, estimating water depth and mapping types of heterogeneous substrates. We provide an overview of past science, current state of the art and future directions so that early career scientists as well as aquatic ecosystem managers and associated industry groups may be prepared for the imminent deluge of imaging spectrometry data.

Technical advancements have widened the limits of remote sensing in mapping shallow water benthic habitats and bathymetry over the last decades. On the other hand, the needs of shallow water remote sensing have pushed instrument development. In this manuscript we provide 50-year retrospective of the developments in the field in terms of both instrumentation and methods. We also show that spectral features characteristic of the main benthic groups in shallow water are consistent from the tropics to sub-arctic regions and from salty to freshwaters. The fundamental limiting factor in both benthic mapping and bathymetry is absorption of light by water molecules. However, spectral absorption by water molecules is the key to bathymetry derivation. Variable backscattering by particles and absorption by dissolved organic matter is a confounding factor for all objectives. The combination of using the spectral and textural characteristics of bottom features and our knowledge about these features have now resulted in the ability to map habitats over large coastal systems. This manuscript has shown that optically shallow water remote sensing has reached levels where the satellite derived bathymetry and habitat maps are accepted by different end users (including the International Maritime Organisation) and are routinely used in ecological studies, monitoring and management of coastal environments.

This paper presents an application of a physic-based method that relies on spectral inversion procedures to simultaneously estimate concentrations of water constituents, water column heights (cH) and benthic substrate types in Lake Trasimeno (Italy) from airborne imaging spectrometry. Complex waters of this lake are challenging due to the coexistence of optically-deep turbid waters and of optically-shallow waters, mostly characterised by dense submerged aquatic vegetation (SAV) beds. Airborne data acquired on 12 May 2009 by Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) were converted into remote sensing reflectance Rrs(λ) with the atmospheric correction code ATCOR. A spectral inversion procedure implementing a bio-optical model (namely BOMBER), parameterised with in situ data, was firstly run to retrieve concentrations of suspended particulate matter (SPM), chlorophyll-a (chl-a) and coloured dissolved organic matter (i.e. aCDOM(440)) in the optically-deep waters. The areas where the retrieved optimisation error was higher than 10% were instead assumed as optically-shallow. In these areas two maps depicting the linear unmixing of three substrate types (i.e., silty-clay, Chara ssp. and other hydrophyte) and the water column heights were produced. The MIVIS-derived products were validated with field data providing a reliable estimation of SPM, chl-a, aCDOM(440) and cH (determination coefficients always R2 > 0.7). SPM concentrations were also similar to a 5.4-km long transect of flow-through turbidity data, and the SAV map was comparable to in situ observations. Generally, the colonisation patterns of SAV were reflecting the spatial distribution of SPM concentrations. In particular, the positive role of Chara on keeping SPM concentrations low was observed. Future research should extend this application to remote sensing data acquired in other seasons to trace the dynamics of SAV and its effect on spatial water clarity.

The Sentinel-2A and 2B Multi-Spectral Instrument (MSI) offers a specification of potential value toward a number of objectives in remote sensing of coral reefs. Coral reefs represent a unique challenge for remote sensing, being highly heterogeneous at metre scales and occurring at variable depths and water clarity regimes. However, conservation initiatives, such as the United Nations Sustainable Development Goals, add urgency to the need for the large scale environmental monitoring information that remote sensing can provide. In the quest to meet this challenge a range of satellite instruments have been leveraged, from Landsat to high spatial resolution sensors such as WorldView-2, toward objectives such as: mapping of bottom types, bathymetry, change detection, and detection of coral bleaching events. Sentinel-2A and 2B offer a new paradigm of available instruments, with a 5-day revisit, 10 m multispectral spatial resolution and freely available data. Pre-launch simulation analyses by several of the authors suggested Sentinel-2 would have good performance for reef applications, in this paper we follow up on this study by reviewing the potential based on the substantial archive of actual data now available. First we determine to what extent the World's reefs are covered by Sentinel-2, since the mission requirements do not by default include all reefs. Secondly we review how a 5-day revisit translates to a usable acquisition rate of clear images, given that cloud and surface glint are common confounding factors. The usable acquisition rate is the real determinant of the objectives to which the data can be applied. Finally we apply current processing algorithms to Sentinel-2 data of several sites over the Great Barrier Reef, including physics-based bathymetry inversion and object-orientated benthic mapping. Landsat 8 OLI is most comparable current sensor to Sentinel-2 MSI, so direct comparisons and the possibilities for data synthesis are explored. Our findings confirm that Sentinel-2 has excellent performance for meeting several essential coral reef scientific and monitoring objectives. Taking into account cloud and sun glint, the usable acquisition rate for a large proportion of reefs is likely to be around 20 clear images a year on average, giving a new potential for evaluation of short time-scale disturbances and impacts. The spatial resolution of 10 m is a key threshold for delineating benthic features of interest such as coral structures, and there is evidence from image and field data that bleaching is detectable. Radiometrically Sentinel-2 data can support good results in physics-based methods, such as bathymetric mapping, comparable to Landsat 8 and WorldView-2. In addition the large scale acquisition area, provided by the 290 km wide swath, offers advantages over high spatial resolution imagery for mapping at multi-reef scales. Sentinel-2 data can be immediately leveraged with existing methods, to provide a new level of reef monitoring information compared to that previously available by remote sensing. Combined with Landsat 8 and the historical Landsat archive, the data collected today will be invaluable for decades or even centuries to come. In this context, the main downside of the Sentinel-2 mission is that approximately 12% of the World's reefs currently lie outside the acquisition plan and are not imaged. Surprisingly, for a European initiative, coral reefs in European governed territories are among the worst served globally. These omissions, approximately only 1/200th of the currently imaged area, limit the global scope which otherwise would be one of Sentinel-2's greatest strengths.

International audience; In the last few decades, phytoplankton biomass has been commonly studied from space. However, satellite analysis of non-algal particles (NAPs), including heterotrophic bacteria and viruses, is relatively recent. In this work, we estimate the backscattering coefficient associated with the NAP fraction that does not covary with chlorophyll based on satellite particulate backscattering coefficient and chlorophyll (b(bp)NAP). b(bp)NAP is computed at 100-km resolution using 19 years of monthly satellite data. We find clear differences in b(bp)NAP between northern and southern oceans. High b(bp)NAP values are found in the Arctic and Southern Oceans, the North Atlantic area influenced by the Gulf Stream current, as well as shelf regions (i.e., Patagonian shelf) affected by upwelling regimes. Low correlation between chlorophyll and backscattering prevents precise b(bp)NAP estimations in oligotrophic areas (e.g., subtropical gyres). These b(bp)NAP estimations lead to a reduction to half in satellite-based phytoplankton biomass estimates respect to previously published results. Plain Language Summary In the ocean, there are different seawater constituents that contribute to the inherent optical properties: Phytoplankton is a major constituent and one of the most studied in the last decade. Other important constituents are the colored dissolved organic matter and non-algal particles (NAPs). NAP includes (i) heterotrophic organisms such as bacteria, micrograzers, and viruses; (ii) detrital organic particles such as fecal pellets and cell debris; and (iii) mineral particles of both biogenic (e.g., calcite liths and shells) and terrestrial origin (e.g., clays and sand). This study is the first attempt to define the NAP from space, and its spatial variability, and how it contributes to refine the phytoplankton carbon biomass estimation. We estimate the backscattering coefficient associated with the NAP fraction that does not covary with chlorophyll from the satellite particulate backscattering coefficient and chlorophyll (bbpNAP). Our main results evidence a geographical variability of bbpNAP from northern to southern oceans with two distinct regimes: one associated with the productive areas in which bbpNAP and biomass are anticorrelated and another in which bbpNAP high values are in regions dominated by inorganic origin. We demonstrate that the spatial variability of bbpNAP should not be ignored.

In this study we evaluate the capabilities of three satellite sensors for assessing water composition and bottom depth in Lake Garda, Italy. A consistent physics-based processing chain was applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat-8 Operational Land Imager (OLI) and RapidEye. Images gathered on 10 June 2014 were corrected for the atmospheric effects with the 6SV code. The computed remote sensing reflectance (Rrs) from MODIS and OLI were converted into water quality parameters by adopting a spectral inversion procedure based on a bio-optical model calibrated with optical properties of the lake. The same spectral inversion procedure was applied to RapidEye and to OLI data to map bottom depth. In situ measurements of Rrs and of concentrations of water quality parameters collected in five locations were used to evaluate the models. The bottom depth maps from OLI and RapidEye showed similar gradients up to 7 m (r = 0.72). The results indicate that: (1) the spatial and radiometric resolutions of OLI enabled mapping water constituents and bottom properties, (2) MODIS was appropriate for assessing water quality in the pelagic areas at a coarser spatial resolution, and (3) RapidEye had the capability to retrieve bottom depth at high spatial resolution. Future work should evaluate the performance of the three sensors in different bio-optical conditions.

This paper outlines a methodology for the estimation of the environmental noise equivalent reflectance in aquatic remote sensing imagery using an object-based segmentation approach. Noise characteristics of remote sensing imagery directly influence the accuracy of estimated environmental variables and provide a framework for a range of sensitivity, sensor specification, and algorithm design studies. The proposed method enables estimation of the noise equivalent reflectance covariance of remote sensing imagery through homogeneity characterization using image segmentation. The method is first tested on a synthetic data set with known noise characteristics and is successful in estimating the noise equivalent reflectance under a range of segmentation structures. Testing on a Portable Hyperspectral Imager for Low-Light Spectroscopy (PHILLS) hyperspectral image in a coral reef environment shows the method to produce comparable noise equivalent reflectance estimates in an optically shallow water environment to those previously derived in optically deep water. This method is of benefit in aquatic studies where homogenous regions of optically deep water were previously required for image noise estimation. The ability of the method to characterize the covariance of an image is of significant benefit when developing probabilistic inversion techniques for remote sensing.

The variability in the optical properties of a coastal region influenced by river runoff and multiple ocean currents in a southern hemisphere setting has been studied. The study area, Tasmanian coastal waters, is influenced by subtropical currents such as the East Australian Current (EAC) and the Zeehan Current (ZC) mix with cooler sub-Antarctic water (SAW). Freshwater discharges from rivers around the island and their mixing with the ocean currents also influence Tasmanian coastal waters. This study was performed to understand the influence of hydrodynamic processes on coastal optical properties and underwater light propagation. Physical, biogeochemical and optical properties were measured in Tasmanian coastal water during the austral autumn of 2007. In this study we found that physical properties have a good correlation with optical properties indicating the role played by hydrodynamic processes in distribution of optically active substances, optical properties of the water mass and underwater light propagation. Analysis of in situ salinity and temperature confirmed the presence of relatively cooler ZC in the South-West region, a cooler mixture of the ZC and SAW in the South-East, warm and saline EAC waters along the East coast and relatively cooler and fresh Bass straight waters along the North coast. In Tasmanian coastal waters light absorption in the water column is controlled by Coloured Dissolved Organic Matter (CDOM) with regionally varying contributions from Non-Algal Particulate (NAP) matter and phytoplankton. Absorption due to CDOM and NAP show a conservative mixing behaviour indicating that these biogeochemical components were delivered by the river and diluted in the coastal water. Suspended particulate matter in Tasmanian coastal water are highly scattering in nature and the beam attenuation is mainly due to light scattering. Variability in probability of light backscattering was mainly due to varying availability of non-algal particulate matter in the surface waters, which is controlled by river discharges in the region. Beam attenuation was high in coastal waters that are influenced by river runoff and increasing beam attenuation had constrained the underwater light propagation in these coastal waters. In the absence of major rivers along the East coast, optical properties were mainly influenced by the EAC water mass. Optical properties of the East coast were clearly different from the rest of the Tasmanian regions. In other regions the influence of ocean currents is subtle due to strong mixing between river discharges and ocean water mass. Overall, analysis of bio-optical properties shows that optical properties are constrained by regional hydrodynamic processes. Results presented highlight importance of using hydrodynamic process specific bio-optical properties and parameterisation in modelling light propagation in coastal ecosystems that are influenced by multiple ocean currents and river discharges.

The need for more effective environmental monitoring of the open and coastal ocean has recently led to notable advances in satellite ocean color technology and algorithm research. Satellite ocean color sensors’ data are widely used for the detection, mapping and monitoring of phytoplankton blooms because earth observation provides a synoptic view of the ocean, both spatially and temporally. Algal blooms are indicators of marine ecosystem health; thus, their monitoring is a key component of effective management of coastal and oceanic resources. Since the late 1970s, a wide variety of operational ocean color satellite sensors and algorithms have been developed. The comprehensive review presented in this article captures the details of the progress and discusses the advantages and limitations of the algorithms used with the multi-spectral ocean color sensors CZCS, SeaWiFS, MODIS and MERIS. Present challenges include overcoming the severe limitation of these algorithms in coastal waters and refining detection limits in various oceanic and coastal environments. To understand the spatio-temporal patterns of algal blooms and their triggering factors, it is essential to consider the possible effects of environmental parameters, such as water temperature, turbidity, solar radiation and bathymetry. Hence, this review will also discuss the use of statistical techniques and additional datasets derived from ecosystem models or other satellite sensors to characterize further the factors triggering or limiting the development of algal blooms in coastal and open ocean waters.

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS), and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales, their role in marine biogeochemistry, the global carbon cycle, the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean, and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration, since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency, the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA), and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.