150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean

Vandermeulen, Ryan; Mannino, Antonio; Craig, Susanne E.; Werdell, P. Jeremy

doi:10.1016/j.rse.2020.111900

Cited by 36 publications

(30 citation statements)

References 43 publications

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“…5 [31]. Because the above in situ a ph (λ) spectra were selected from more than 4000 SeaBASS spectra, and together with the random combination of optically active constituents, this synthetic data set was expected to cover all possible natural ocean water IOP-AOP scenarios [30,39], theoretically without duplicate data. This data set was used for the U-OWT scheme development and the IOPs analysis of each U-OWT class.…”

Section: Materials 211 Synthetic Datamentioning

confidence: 99%

“…Thus, there are some potential uncertainties when the in situ data-based OWT schemes are applied to satellite data. Second, the spatial and temporal distributions of the in situ or the pixel spectra affect the representativeness of water classifications [30,32]. For instance, the in situ data were mostly collected in the Northern Hemisphere, with few data points representing very oligotrophic gyre areas [33].…”

Section: Introductionmentioning

confidence: 99%

“…Third, with the development of hyperspectral remote sensing technology, some of the existing OWT schemes that initially were developed within limited multispectral bands may not encompass all characteristic bands reflecting the bio-optical features of water. Fourth, the existing OWT schemes were mostly designed for one specific ocean color instrument, such as SeaWiFS [11,13,14,17,22], MODIS [10,15], MERIS [15,16,19,20,30], or OLCI [18]; thus it is difficult to migrate these OWT schemes to other satellite sensors. Therefore, it is necessary to develop an OWT scheme that is measurement error-free, suitable for the global ocean waters, and multi-satellite sensors.…”

Section: Introductionmentioning

confidence: 99%

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A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans

2021

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The classification of natural waters is a way to generalize and systematize ocean color science. However, there is no consensus on an optimal water classification template in many contexts. In this study, we conducted an unsupervised classification of the PACE (Plankton, Aerosols, Cloud, and Ocean Ecosystem) synthetic hyperspectral data set, divided the global ocean waters into 15 classes, then obtained a set of fuzzy logic optical water type schemes (abbreviated as the U-OWT in this study) that were tailored for several multispectral satellite sensors, including SeaWiFS, MERIS, MODIS, OLI, VIIRS, MSI, and OLCI. The consistency analysis showed that the performance of U-OWT on different satellite sensors was comparable, and the sensitivity analysis demonstrated the U-OWT could resist a certain degree of input disturbance on remote sensing reflectance. Compared to existing ocean-aimed optical water type schemes, the U-OWT can distinguish more mesotrophic and eutrophic water classes. Furthermore, the U-OWT was highly compatible with other water classification taxonomies, including the trophic state index, the multivariate absorption combinations, and the Forel-Ule Scale, which indirectly demonstrated the potential for global applicability of the U-OWT. This finding was also helpful for the further conversion and unification of different water type taxonomies. As the fundamental basis, the U-OWT can be applied to many oceanic fields that need to be explored in the future. To promote the reproducibility of this study, an IDL®-based standalone U-OWT calculation tool is freely distributed.

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Section: Materials 211 Synthetic Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans

2021

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“…Indeed, several multispectral ocean color sensors are programmable spectrometers resampled onboard to specific wavebands (e.g., Sentinel-3 OLCI). Utilizing the full spectrum, even simple approaches that characterize the spectral dimensionality and variability can be used to identify and track subtle differences between water masses and over time that could not be tracked by bulk chlorophyll a estimates (Vandermeulen et al, 2020). Full-spectrum estimates of the diffuse attenuation coefficient (K d ) may lead to new insights about aquatic ecosystems and biodiversity processes like spectral niche partitioning and complementarity (Striebel et al, 2009), or behavior and evolutionary traits of aquatic invertebrates and vertebrates (Russell and Dierssen, 2015;Cummings and Endler, 2018).…”

Section: Introductionmentioning

confidence: 99%

Living up to the Hype of Hyperspectral Aquatic Remote Sensing: Science, Resources and Outlook

Dierssen

Ackleson

Joyce

et al. 2021

Front. Environ. Sci.

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Intensifying pressure on global aquatic resources and services due to population growth and climate change is inspiring new surveying technologies to provide science-based information in support of management and policy strategies. One area of rapid development is hyperspectral remote sensing: imaging across the full spectrum of visible and infrared light. Hyperspectral imagery contains more environmentally meaningful information than panchromatic or multispectral imagery and is poised to provide new applications relevant to society, including assessments of aquatic biodiversity, habitats, water quality, and natural and anthropogenic hazards. To aid in these advances, we provide resources relevant to hyperspectral remote sensing in terms of providing the latest reviews, databases, and software available for practitioners in the field. We highlight recent advances in sensor design, modes of deployment, and image analysis techniques that are becoming more widely available to environmental researchers and resource managers alike. Systems recently deployed on space- and airborne platforms are presented, as well as future missions and advances in unoccupied aerial systems (UAS) and autonomous in-water survey methods. These systems will greatly enhance the ability to collect interdisciplinary observations on-demand and in previously inaccessible environments. Looking forward, advances in sensor miniaturization are discussed alongside the incorporation of citizen science, moving toward open and FAIR (findable, accessible, interoperable, and reusable) data. Advances in machine learning and cloud computing allow for exploitation of the full electromagnetic spectrum, and better bridging across the larger scientific community that also includes biogeochemical modelers and climate scientists. These advances will place sophisticated remote sensing capabilities into the hands of individual users and provide on-demand imagery tailored to research and management requirements, as well as provide critical input to marine and climate forecasting systems. The next decade of hyperspectral aquatic remote sensing is on the cusp of revolutionizing the way we assess and monitor aquatic environments and detect changes relevant to global communities.

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“…Precise determination of true color requires the application of ocean colorimetry, which is the quantitative determination of the ocean's apparent color based on the underlying spectral distribution of the emergent water-leaving radiance [18][19][20]. We employ colorimetry because it is a useful tool to rapidly delineate changes in surface ocean optics and potential delineations between water mass boundaries without any a priori assumption regarding the potential optical constituents and their respective impact on surface reflectance signals [18,21]. True color may also provide information that is lost in the standard inversion product fields but is nonetheless indicative of physical ocean processes and water mass boundaries [22].…”

Section: Introductionmentioning

confidence: 99%

On the Potential Optical Signature of Convective Turbulence over the West Florida Shelf

et al. 2021

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Atmospheric cold front propagation across the northern Gulf of Mexico is characterized by elevated surface wind velocities and a ~10–15 °C drop in surface air temperatures. These meteorological conditions result in significant heat energy losses from the surface ocean to the overlying atmosphere. These seasonally recurring cold-air outbreak events may penetrate the southern portion of the West Florida continental shelf and initiate turbulent and convective overturn of the water column. Examination of true color images derived from ocean-viewing, satellite-based radiometer data reveals coincident and substantial surface water discolorations that are optically similar to smaller-scale “whiting events,” despite the regional-scale extent of the observed phenomenon (>25,000 km2). Coupled air–sea numerical simulations suggest the surface water discoloration occurs and is sustained where the entire water column is dynamically unstable. The simulation results indicate significant density (σt) inversions between the surface and bottom waters. Thus, the combined numerical model and remote sensing analysis suggest that convective turbulence may be contributing to the sustained ventilation of bottom waters containing a high concentration of suspended particulates. High-temporal resolution true color images rendered from the GOES-R Advanced Baseline Imager (ABI) data appear to support the surface water discoloration’s turbulent-driven nature.

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150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean

Cited by 36 publications

References 43 publications

A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans

A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans

Living up to the Hype of Hyperspectral Aquatic Remote Sensing: Science, Resources and Outlook

On the Potential Optical Signature of Convective Turbulence over the West Florida Shelf

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