Expanding the Application of Sentinel-2 Chlorophyll Monitoring across United States Lakes.

Eutrophication of inland lakes poses various societal and ecological threats, making water quality monitoring crucial. Satellites provide a comprehensive and cost-effective supplement to traditional in situ sampling. The Sentinel-2 MultiSpectral Instrument (S2 MSI) offers unique spectral bands positioned to quantify chlorophyll a, a water-quality and trophic-state indicator, along with fine spatial resolution, enabling the monitoring of small waterbodies. In this study, two algorithms-the Maximum Chlorophyll Index (MCI) and the Normalized Difference Chlorophyll Index (NDCI)-were applied to S2 MSI data. They were calibrated and validated using in situ chlorophyll a measurements for 103 lakes across the contiguous U.S. Both algorithms were tested using top-of-atmosphere reflectances (ρ t), Rayleigh-corrected reflectances (ρ s), and remote sensing reflectances (R rs ). MCI slightly outperformed NDCI across all reflectance products. MCI using ρ t showed the best overall performance, with a mean absolute error factor of 2.08 and a mean bias factor of 1.15. Conversion of derived chlorophyll a to trophic state improved the potential for management applications, with 82% accuracy using a binary classification. We report algorithm-to-chlorophyll-a conversions that show potential for application across the U.S., demonstrating that S2 can serve as a monitoring tool for inland lakes across broad spatial scales.

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality.

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring.

Integrating Inland and Coastal Water Quality Data for Actionable Knowledge.

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

Widespread global increase in intense lake phytoplankton blooms since the 1980s.

Freshwater blooms of phytoplankton affect public health and ecosystem services globally1,2. Harmful effects of such blooms occur when the intensity of a bloom is too high, or when toxin-producing phytoplankton species are present. Freshwater blooms result in economic losses of more than US$4 billion annually in the United States alone, primarily from harm to aquatic food production, recreation and tourism, and drinking-water supplies3. Studies that document bloom conditions in lakes have either focused only on individual or regional subsets of lakes4-6, or have been limited by a lack of long-term observations7-9. Here we use three decades of high-resolution Landsat 5 satellite imagery to investigate long-term trends in intense summertime near-surface phytoplankton blooms for 71 large lakes globally. We find that peak summertime bloom intensity has increased in most (68 per cent) of the lakes studied, revealing a global exacerbation of bloom conditions. Lakes that have experienced a significant (P < 0.1) decrease in bloom intensity are rare (8 per cent). The reason behind the increase in phytoplankton bloom intensity remains unclear, however, as temporal trends do not track consistently with temperature, precipitation, fertilizer-use trends or other previously hypothesized drivers. We do find, however, that lakes with a decrease in bloom intensity warmed less compared to other lakes, suggesting that lake warming may already be counteracting management efforts to ameliorate eutrophication10,11. Our findings support calls for water quality management efforts to better account for the interactions between climate change and local hydrological conditions12,13.

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems.

The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.

Revisiting short-wave-infrared (SWIR) bands for atmospheric correction in coastal waters.

The shortwave infrared (SWIR) bands on the existing Earth Observing missions like MODIS have been designed to meet land and atmospheric science requirements. The future geostationary and polar-orbiting ocean color missions, however, require highly sensitive SWIR bands (> 1550nm) to allow for a precise removal of aerosol contributions. This will allow for reasonable retrievals of the remote sensing reflectance (Rrs) using standard NASA atmospheric corrections over turbid coastal waters. Design, fabrication, and maintaining high-performance SWIR bands at very low signal levels bear significant costs on dedicated ocean color missions. This study aims at providing a full analysis of the utility of alternative SWIR bands within the 1600nm atmospheric window if the bands within the 2200nm window were to be excluded due to engineering/cost constraints. Following a series of sensitivity analyses for various spectral band configurations as a function of water vapor amount, we chose spectral bands centered at 1565 and 1675nm as suitable alternative bands within the 1600nm window for a future geostationary imager. The sensitivity of this band combination to different aerosol conditions, calibration uncertainties, and extreme water turbidity were studied and compared with that of all band combinations available on existing polar-orbiting missions. The combination of the alternative channels was shown to be as sensitive to test aerosol models as existing near-infrared (NIR) band combinations (e.g., 748 and 869nm) over clear open ocean waters. It was further demonstrated that while in extremely turbid waters the 1565/1675 band pair yields Rrs retrievals as good as those derived from all other existing SWIR band pairs (> 1550nm), their total calibration uncertainties must be < 1% to meet current science requirements for ocean color retrievals (i.e., Δ Rrs (443) < 5%). We further show that the aerosol removal using the NIR and SWIR bands (available on the existing polar-orbiting missions) can be very sensitive to calibration uncertainties. This requires the need for monitoring the calibration of these bands to ensure consistent multi-mission ocean color products in coastal/inland waters.

Uncertainties in Coastal Ocean Color Products: Impacts of Spatial Sampling.

With increasing demands for ocean color (OC) products with improved accuracy and well characterized, per-retrieval uncertainty budgets, it is vital to decompose overall estimated errors into their primary components. Amongst various contributing elements (e.g., instrument calibration, atmospheric correction, inversion algorithms) in the uncertainty of an OC observation, less attention has been paid to uncertainties associated with spatial sampling. In this paper, we simulate MODIS and VIIRS OC products from 30m resolution OC products derived from the Operational Land Imager (OLI) aboard Landsat-8, to examine impacts of spatial sampling on both cross-sensor product intercomparisons and in-situ validations of Rrs products in coastal waters. The simulations were carried out for OLI scenes "scanned" for one full orbital-repeat cycle of each ocean color satellite. While some view-angle dependent differences in simulated Aqua-MODIS and VIIRS were observed, the average uncertainties (absolute) in product intercomparisons (due to differences in spatial sampling) at regional scales are found to be 1.8%, 1.9%, 2.4%, 4.3%, 2.7%, 1.8%, and 4% for the Rrs(443), Rrs(482), Rrs(561), Rrs(655), [Chla], Kd(482), and bbp(655) products, respectively. It is also found that, depending on in-water spatial variability and the sensor's footprint size, the errors for an in-situ validation location in coastal areas can reach as high as ±18%. We conclude that a) expected biases induced by the spatial sampling in product intercomparisons are mitigated when products are averaged over at least 7km×7km windows, b) VIIRS observations, with improved consistency in cross-track spatial sampling yields more precise calibration/validation results than MODIS, and c) use of a single pixel centered on in-situ coastal sites provides an optimal sampling size for validation efforts. These findings will have implications for enhancing our understanding of uncertainties in ocean color retrievals and for planning of future calibration/validation exercises.

Radiance transmittance measured at the ocean surface.

The radiance transmittance (Tr) is the ratio of the water-leaving radiance (Lw(0+)) to the sub-surface upwelling radiance (Lu(0-)), which is an important optical parameter for ocean optics and ocean color remote sensing. Historically, a constant value (~0.54) based on theoretical presumptions has been adopted for Tr and is widely used. This optical parameter, however, has never been measured in the aquatic environments. With a robust setup to measure both Lu(0-) and Lw(0+) simultaneously in the field, this study presents Tr in the zenith direction between 350 and 700 nm measured in a wide range of oceanic waters. It is found that the measured Tr values are generally consistent with the long-standing theoretical value of 0.54, with mean relative difference less than 10%. In particular, the agreement within the spectral domain of 400-600 nm is found to be the best (with the averaged difference less than 5%). The largest difference is observed for wavelengths longer than 600 nm with the average difference less than 15%, which is related to the generally very small values in both Lu(0-) and Lw(0+) and rough environmental conditions. These results provide a validation of the setup for simultaneous measurements of upwelling radiance and water-leaving radiance and confidence in the theoretical Tr value used in ocean optics studies at least for oceanic waters.

Diurnal remote sensing of coastal/oceanic waters: a radiometric analysis for Geostationary Coastal and Air Pollution Events.

Optical remote sensing systems aboard geostationary platforms can provide high-frequency observations of bio-optical properties in dynamical coastal/oceanic waters. From the end-user standpoint, it is recognized that the fidelity of daily science products relies heavily on the radiometric sensitivity/performance of the imaging system. This study aims to determine the theoretical detection limits for bio-optical properties observed diurnally from a geostationary orbit. The analysis is based upon coupled radiative transfer simulations and the minimum radiometric requirements defined for the GEOstationary Coastal and Air Pollution Events (GEO-CAPE) mission. The diurnal detection limits are found for the optically active constituents of water, including near-surface concentrations of chlorophyll-a (CHL) and total suspended solids (TSS), and the absorption of colored dissolved organic matter (aCDOM). The diurnal top-of-atmosphere radiance (Lt) is modeled for several locations across the field of regard (FOR) to investigate the radiometric sensitivity at different imaging geometries. It is found that, in oceanic waters (CHL=0.07 mg/m3), detecting changes smaller than 0.01 mg/m3 in CHL is feasible for all locations and hours except for late afternoon observations on the edge of the FOR. For more trophic/turbid waters (0.6

Robust approach to directly measuring water-leaving radiance in the field.

It has been a long-standing goal to precisely measure water-leaving radiance (L(w), or its equivalent property, remote-sensing reflectance) in the field, but reaching this goal is quite a challenge. This is because conventional approaches do not provide a direct measurement of L(w), but rather measure various related components and subsequently derive this core property from these components. Due to many uncontrollable factors in the measurement procedure and imprecise post-measurement processing routines, the resulting L(w) is inherently associated with various levels of uncertainties. Here we present a methodology called the skylight-blocked approach (SBA) to measure L(w) directly in the field, along with results obtained recently in the Laurentian Great Lakes. These results indicate that SBA can measure L(w) in high precision. In particular, there is no limitation of water types for the deployment of SBA, and the requirement of post-measurement processing is minimum; thus high-quality L(w) for a wide range of aquatic environments can be acquired.