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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Discriminating Phytoplankton Functional Types (PFTs) in the Coastal Ocean Using the Inversion Algorithm Phydotax and Airborne Imaging Spectrometer Data

There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in-land water bodies. Results presented are from the 10 April 2013 overflight of the Monterey Bay region and focus primarily on the first objective - sensitivity to atmospheric correction. On-going and future work will continue to evaluate if PHYDOTax can be applied to historical (SeaWiFS and MERIS), existing (MODIS, VIIRS, and HICO), and future (PACE, GEO-CAPE, and HyspIRI) satellite sensors. Demonstration of cross-platform continuity may aid in calibration and validation efforts of these sensors.

Biological Oceanography↗
NASA NTRS2014

NASA COAST and OCEANIA Airborne Missions Support Ecosystem and Water Quality Research in the Coastal Zone

NASA has a continuing requirement to collect high-quality in situ data for the vicarious calibration of current and next generation ocean color satellite sensors and to validate the algorithms that use the remotely sensed observations. Recent NASA airborne missions over Monterey Bay, CA, have demonstrated novel above- and in-water measurement capabilities supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The results characterize coastal atmospheric and aquatic properties through an end-to-end assessment of image acquisition, atmospheric correction, algorithm application, plus sea-truth observations from state-of-the-art instrument systems. The primary goal is to demonstrate the following in support of calibration and validation exercises for satellite coastal ocean color products: 1) the utility of a multi-sensor airborne instrument suite to assess the bio-optical properties of coastal California, including water quality; and 2) the importance of contemporaneous atmospheric measurements to improve atmospheric correction in the coastal zone. The imaging spectrometer (Headwall) is optimized in the blue spectral domain to emphasize remote sensing of marine and freshwater ecosystems. The novel airborne instrument, Coastal Airborne In-situ Radiometers (C-AIR) provides measurements of apparent optical properties with high dynamic range and fidelity for deriving exact water leaving radiances at the land-ocean boundary, including radiometrically shallow aquatic ecosystems. Simultaneous measurements supporting empirical atmospheric correction of image data are accomplished using the Ames Airborne Tracking Sunphotometer (AATS-14). Flight operations are presented for the instrument payloads using the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter flown over Monterey Bay during the seasonal fall algal bloom in 2011 (COAST) and 2013 (OCEANIA) to support bio-optical measurements of phytoplankton for coastal zone research.

Airborne Instruments↗
NASA NTRS2015

NASA COAST and OCEANIA Airborne Missions in Support of Ecosystem and Water Quality Research in the Coastal Zone

Worldwide, coastal marine ecosystems are exposed to land-based sources of pollution and sedimentation from anthropogenic activities including agriculture and coastal development. Ocean color products from satellite sensors provide information on chlorophyll (phytoplankton pigment), sediments, and colored dissolved organic material. Further, ship-based in-water measurements and emerging airborne measurements provide in situ data for the vicarious calibration of current and next generation satellite ocean color sensors and to validate the algorithms that use the remotely sensed observations. Recent NASA airborne missions over Monterey Bay, CA, have demonstrated novel above- and in-water measurement capabilities supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The results characterize coastal atmospheric and aquatic properties through an end-to-end assessment of image acquisition, atmospheric correction, algorithm application, plus sea-truth observations from state-of-the-art instrument systems. The primary goal of the airborne missions was to demonstrate the following in support of calibration and validation exercises for satellite coastal ocean color products: 1) the utility of a multi-sensor airborne instrument suite to assess the bio-optical properties of coastal California, including water quality; and 2) the importance of contemporaneous atmospheric measurements to improve atmospheric correction in the coastal zone. Utilizing an imaging spectrometer optimized in the blue to green spectral domain enables higher signal for detection of the relatively dark radiance measurements from marine and freshwater ecosystem features. The novel airborne instrument, Coastal Airborne In-situ Radiometers (C-AIR) provides measurements of apparent optical properties with high dynamic range and fidelity for deriving exact water leaving radiances at the land-ocean boundary, including radiometrically shallow aquatic ecosystems. Simultaneous measurements supporting empirical atmospheric correction of image data were accomplished using the Ames Airborne Tracking Sunphotometer (AATS-14). Flight operations are presented for the instrument payloads using the CIRPAS Twin Otter flown over Monterey Bay during the seasonal fall algal bloom in 2011 (COAST) and 2013 (OCEANIA) to support bio-optical measurements of phytoplankton for coastal zone research. Further, this airborne capability can be responsive to first flush rain events that deliver higher concentrations of sediments and pollution to coastal waters via watersheds and overland flow.

Airborne Equipment↗
NASA NTRS2016

Airborne Mission Concept for Coastal Ocean Color and Ecosystems Research

NASA airborne missions in 2011 and 2013 over Monterey Bay, CA, demonstrated novel above- and in-water calibration and validation measurements supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The resultant airborne data characterize contemporaneous coastal atmospheric and aquatic properties plus sea-truth observations from state-of-the-art instrument systems spanning a next-generation spectral domain (320-875 nm). This airborne instrument suite for calibration, validation, and research flew at the lowest safe altitude (ca. 100 ft or 30 m) as well as higher altitudes (e.g., 6,000 ft or 1,800 m) above the sea surface covering a larger area in a single synoptic sortie than ship-based measurements at a few stations during the same sampling period. Data collection of coincident atmospheric and aquatic properties near the sea surface and at altitude allows the input of relevant variables into atmospheric correction schemes to improve the output of corrected imaging spectrometer data. Specific channels support legacy and next-generation satellite capabilities, and flights are planned to within 30 min of satellite overpass. This concept supports calibration and validation activities of ocean color phenomena (e.g., river plumes, algal blooms) and studies of water quality and coastal ecosystems. The 2011 COAST mission flew at 100 and 6,000 ft on a Twin Otter platform with flight plans accommodating the competing requirements of the sensor suite, which included the Coastal-Airborne In-situ Radiometers (C-AIR) for the first time. C-AIR (Biospherical Instruments Inc.) also flew in the 2013 OCEANIA mission at 100 and 1,000 ft on the Twin Otter below the California airborne simulation of the proposed NASA HyspIRI satellite system comprised of an imaging spectrometer and thermal infrared multispectral imager on the ER-2 at 65,000 ft (20,000 m). For both missions, the Compact-Optical Profiling System (Biospherical Instruments, Inc.), an in-water system with microradiometers matching C-AIR, was deployed to compare sea-truth measurements and low-altitude Twin Otter flights within Monterey Bay red tide events. This novel airborne and in-water sensor capability advances the science of coastal measurements and enables rapid response for coastal events.

Oceans↗
DOE OSTI2022

MBARI-WEC September and October 2022 Field Data

This data is needed to simulate a model of the MBARI-WEC (Monterey Bay Aquarium Research Institute, Wave Energy Converter device) in a simulation environment (e.g. Gazebo) for 56 observation dates in the time between September and October 2022, and to compare the simulation outputs to the corresponding field data of the physical MBARI-WEC. There were 50 observations chosen in Sept and 6 observations in Oct. To help understand terms below, a summary of the system can be found at the github link in the downloads section below. The Gazebo MBARI-WEC model is also provided, should users wish to simulate using this platform. There are 4 *mat files included. ................................................................................................................................................................................................................................... Spectrum and Simulation Inputs: September2022_spectrum_siminputs.mat and October2022_spectrum_siminputs.mat has data needed for simulation inputs in table format. These include the ocean spectrum for an observation and operating parameters of the MBARI-WEC during that observation. They are organized as rows representing an observation and columns representing data. For example, for the September *mat there are 50 rows. The first 7 columns are Datetime, sig_waveheight, peak_period, mean_period, heaveconedoor_status, pistonpos_mean, and scale_factor: - Datetime is the date and time the observation occurred in PST - sig_waveheight is the significant wave height of the ocean spectrum during that observation in meters - peak_period is the peak period of the ocean spectrum during that observation in seconds - mean_period is the mean period of the ocean spectrum during that observation in seconds - heaveconedoor_status is the status of the heave cone doors where 0 represents the doors are open and 1 represents they are closed - pistonpos_mean is the mean position of the PTO ram (piston) in meters - scale_factor is an additional factor of 0.5 --1.4 applied to a default damping relationship The next columns are data needed to represent the ocean spectrum. First are the frequencies [Hz] labeled as "f0-f38", then the variance density [m2/Hz] labeled as "vardens0-vardens38". October2022_spectrum_siminputs.mat follows as a similar format as above, but includes a larger amount of ocean spectrum frequencies and variance density elements. ................................................................................................................................................................................................................................... Field data: The field data is found in MBARIWEC_septdata.mat and MBARIWEC_octdata.mat for the observations of September and October, respectively. These contain data in a struct format. The struct contains the following fields for each observation: PC_BattCurr, PC_LoadCurr, PC_RPM, PC_Voltage, SC_Range, SC_Velocity, DateTime, where: - PC_BattCurr is the current flowing to or from the onboard batteries in Amps - PC_LoadCurr is the current flowing to the load dump in Amps - PC_RPM is the electric/hydraulic motor shaft speed (directly coupled) in RPM - PC_Voltage is the bus voltage at the power converter in Volts - SC_Range is the PTO ram (piston) position in meters where 0 is fully retracted and 2.03 is fully extended - SC_Velocity is the PTO ram (piston) velocity in meters/sec - DateTime is the date and time of the sampled field data in each observation in PST - Electric Power is equal to: PC_Voltage*(PC_BattCurr + PC_LoadCurr) in Watts For example, upon loading MBARIWEC_octdata.mat, the aforementioned fields would be loaded, each with {6x1} cells for the 6 observations chosen in October. Within the first cell of e.g. SC_Range would be sampled data representing the field data of the MBARIWEC PTO piston position for say, one hour, of the first October observation. The corresponding field DateTime would...

16 TIDAL AND WAVE POWER↗
NASA NTRS2002

Analysis of Salinity Intrusion in the San Francisco Bay-Delta using a GA- Optimized Neural Net, and Application of the Model to Prediction in the Elkhorn Slough Habitat

The San Francisco Bay Delta is a large hydrodynamic complex that incorporates the Sacramento and San Joaquin Estuaries, the Burman Marsh, and the San Francisco Bay proper. Competition exists for the use of this extensive water system both from the fisheries industry, the agricultural industry, and from the marine and estuarine animal species within the Delta. As tidal fluctuations occur, more saline water pushes upstream allowing fish to migrate beyond the Burman Marsh for breeding and habitat occupation. However, the agriculture industry does not want extensive salinity intrusion to impact water quality for human and plant consumption. The balance is regulated by pumping stations located alone the estuaries and reservoirs whereby flushing of fresh water keeps the saline intrusion at bay. The pumping schedule is driven by data collected at various locations within the Bay Delta and by numerical models that predict the salinity intrusion as part of a larger model of the system. The Interagency Ecological Program (IEP) for the San Francisco Bay/Sacramento-San Joaquin Estuary collects, monitors, and archives the data, and the Department of Water Resources provides a numerical model simulation (DSM2) from which predictions are made that drive the pumping schedule. A problem with this procedure is that the numerical simulation takes roughly 16 hours to complete a C:~ prediction. We have created a neural net, optimized with a genetic algorithm, that takes as input the archived data from multiple stations and predicts stage, salinity, and flow at the Carquinez Straits (at the downstream end of the Burman Marsh). This model seems to be robust in its predictions and operates much faster than the current numerical DSM2 model. Because the system is strongly tidal driven, we used both Principal Component Analysis and Fast Fourier Transforms to discover dominant features within the IEP data. We then filtered out the dominant tidal forcing to discover non-primary tidal effects, and used this to enhance the neural network by mapping input-output relationships in a more efficient manner. Furthermore, the neural network implicitly incorporates both the hydrodynamic and water quality models into a single predictive system. Although our model has not yet been enhanced to demonstrate improve pumping schedules, it has the possibility to support better decision-making procedures that may then be implemented by State agencies if desired. Our intention is now to use this model in the smaller Elkhorn Slough complex near Monterey Bay where no such hydrodynamic model currently exists. At the Elkhorn Slough, we are fusing the neural net model of tidally-driven flow with in situ flow data and airborne and satellite remote sensation data. These further constrain the behavior of the model in predicting the longer-term health and future of this vital estuary.

Thompson, David E.↗
DOE OSTI2021

A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms

Abstract Increasing occurrence of harmful algal blooms across the land–water interface poses significant risks to coastal ecosystem structure and human health. Defining significant drivers and their interactive impacts on blooms allows for more effective analysis and identification of specific conditions supporting phytoplankton growth. A novel iterative Random Forests (iRF) machine-learning model was developed and applied to two example cases along the California coast to identify key stable interactions: (1) phytoplankton abundance in response to various drivers due to coastal conditions and land-sea nutrient fluxes, (2) microbial community structure during algal blooms. In Example 1, watershed derived nutrients were identified as the least significant interacting variable associated with Monterey Bay phytoplankton abundance. In Example 2, through iRF analysis of field-based 16S OTU bacterial community and algae datasets, we independently found stable interactions of prokaryote abundance patterns associated with phytoplankton abundance that have been previously identified in laboratory-based studies. Our study represents the first iRF application to marine algal blooms that helps to identify ocean, microbial, and terrestrial conditions that are considered dominant causal factors on bloom dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Wave Energy Converter Power Take-Off Modeling and Validation From Experimental Bench Tests

This article describes the implementation of a new numerical model of the power take-off system installed in the Monterey Bay Aquarium Research Institute wave energy converter, a device developed to provide power to various oceanic research missions. The simultaneous presence of hydraulic, pneumatic, and electrical subsystems in the power take-off system represents a significant challenge in forging an accurate model able to replicate the main dynamic characteristics of the system. The validation of the new numerical model is addressed by comparing simulations with the measurements obtained during a series of bench tests. Data from the bench tests show good agreement with the numerical model. The validated model provides deeper insights into the complex nonlinear dynamics of the power take-off system and will support further performance improvements in the future.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Distributed Acoustic Sensing for Whale Vocalization Monitoring: A Vertical Deployment Field Test

Abstract There is growing interest in floating offshore wind turbine (FOWT) technology, where turbines are installed on floating structures anchored to the seabed, allowing wind energy development in areas unsuitable for traditional fixed-platform turbines. Responsible development requires monitoring the impact of FOWTs on marine wildlife, such as whales, throughout the operational lifecycle of the turbines. Distributed acoustic sensing (DAS)—a technology that transforms fiber-optic cables into vibration sensor arrays—has been demonstrated for acoustic monitoring of whales using seafloor telecommunications cables. However, no studies have yet evaluated DAS performance in dynamic, engineered environments, such as floating platforms or moving vessels with complex, dynamic strain loads, despite their relevance to FOWT settings. This study addresses that gap by deploying DAS aboard a boat in Monterey Bay, California, where a fiber-optic cable was lowered using a weighted and suspended mooring line, enabling vertical deployment. Humpback whale vocalizations were captured and identified in the DAS data, noise sources were identified, and DAS data were compared to audio captured by a standalone hydrophone attached to the mooring line and a nearby hydrophone on a cabled observatory. This study is unique in: (1) deploying DAS in a vertical deployment mode, where noise from turbulence, cable vibrations, and other sources posed additional challenges compared to seafloor DAS applications; (2) demonstrating DAS in a dynamic, nonstationary setup, which is uncommon for DAS interrogators typically used in more stable environments; and (3) leveraging looped sections of the cable to reduce the noise floor and mitigate the effects of excessive cable vibrations and strain. This research demonstrates DAS’s ability to capture whale vocalizations in challenging environments, highlighting its potential to enhance underwater acoustic monitoring, particularly in the context of renewable energy development in offshore environments.

Saw, Jaewon↗
NASA NTRS1973

California coast nearshore processes study

The author has identified the following significant results. This report contains the techniques used for enhancing and analyzing nearshore processes from ERTS-1 and aircraft data. Four California nearshore sites are used as test cells including the San Francisco area, Monterey Bay, Santa Barbara Channel, and Los Angeles area. Techniques used for analyzing the test cells included direct photographic processing, computer compatible tape gain change enhancement, discrete point density analysis and plotting, and densitometer enhancement. Using these methods, it is possible to measure the seaward extent of the suspended sediment transport and to differentiate sediment levels within the individual sediment lobes. The movement of riverine discharged suspensates and coastal sediments by currents was an intricate part of the sediment transport analysis. The larger estuaries in the test cell areas were also studied for flushing characteristics.

Pirie, D. M.↗
NASA NTRS1973

California coast nearshore processes study

The author has identified the following significant results. Remote sensor aircraft flights took place simultaneously with ERTS-1 overpasses at the San Francisco, Monterey Bay, and Santa Barbara test cells. The cameras and scanners used were configured for detecting suspended sediment and for maximum water penetration. The Ektachrome/Wratten 12 photographs which were intentionally overexposed 1-1/2 stops were found to show the most extensive sediment transport detail. Minus blue/K 2 photographs illustrate nearshore underwater bottom detail including the head of the Mugu submarine canyon. The EMSIDE 9 channel scanner was employed to classify and differentiate suspended sediment, oil, kelp, and other materials found in the nearshore area. Processing of bulk ERTS-1 computer compatible tapes was utilized to enhance and analyze nearshore sediments. This technique was most successful in enhancing subtle nearshore features found to be faint or invisible on prints made from the supplied negatives. In addition to this continuing computer process, an effort was initiated to interface density values from the bulk tapes into contouring and mapping software.

Pirie, D. M.↗
NASA NTRS1973

Utilization of ERTS-1 data in the Houston area

The author has identified the following significant results. Using clustering techniques, several large lakes in Texas have been accurately delineated in computer printout graymaps. It was also found that small bodies of water (one to two acres in size) could be detected by searching for small reflectance values in the infrared data. A graymap printout of a lake described a shore outline that was not consistent with available maps. Field examination revealed that the actual level of the lake was below that for which the map was drawn. The current lake configuration agrees in shape and relative size with the ERTS-1 data printout. Water turbidity causes reflectance changes which are detectable in ERTS-1 band 7 data. A comparison has been made of the Monterey Bay, California area using 1971 aerial color infrared photography and a 1972 ERTS-1 band 7 infrared image. This comparison revealed that some event has occurred to impound a significant amount of water in the area since the infrared photography was taken. Data values in the ERTS-1 infrared image exhibit detectable changes in brightness at inflow points, where high turbidity would be present. Researchers had not expected to detect water turbidity patterns in band 7 (800 to 1100 nanometers).

Erb, R. B.↗
NASA NTRS1973

Editing ERTS-1 data to exclude land aids cluster analysis of water targets

The author has identified the following significant results. It has been determined that an increase in the number of spectrally distinct coastal water types is achieved when data values over the adjacent land areas are excluded from the processing routine. This finding resulted from an automatic clustering analysis of ERTS-1 system corrected MSS scene 1002-18134 of 25 July 1972 over Monterey Bay, California. When the entire study area data set was submitted to the clustering only two distinct water classes were extracted. However, when the land area data points were removed from the data set and resubmitted to the clustering routine, four distinct groupings of water features were identified. Additionally, unlike the previous separation, the four types could be correlated to features observable in the associated ERTS-1 imagery. This exercise demonstrates that by proper selection of data submitted to the processing routine, based upon the specific application of study, additional information may be extracted from the ERTS-1 MSS data.

Erb, R. B.↗
NASA NTRS1973

The results of an agricultural analysis of the ERTS-1 MSS data at the Johnson Space Center

The initial analysis of the ERTS-1 multispectral scanner (MSS) data at the Johnson Space Center (JSC), Houston, Texas is discussed. The primary data set utilized was the scene over Monterey Bay, California, on July 25, 1972, NASA ERTS ID No. 1002-18134. It was submitted to both computerized and image interpretative processing. An area in the San Joaquin Valley was submitted to an intensive evaluation of the ability of the data to (1) discriminate between crop types and (2) to provide a reasonably accurate area measurement of agricultural features of interest. The results indicate that the ERTS-1 MSS data is capable of providing the identifications and area extent of agricultural lands and field crop types.

Bizzell, R. M.↗
NASA NTRS1973

California coast nearshore processes study

The author has identified the following significant results. Large scale sediment plumes from intermittent streams and rivers form detectable seasonal patterns on ERTS-1 imagery. The ocean current systems, as plotted from three California coast ERTS mosaics, were identified. Offshore patterns of sediment in areas such as the Santa Barbara Channel are traceable. These patterns extend offshore to heretofore unanticipated ranges as shown on the ERTS-1 imagery. Flying spot scanner enhancements of NASA tapes resulted in details of subtle and often invisible (to the eye) nearshore features. The suspended sediments off San Francisco and in Monterey Bay are emphasized in detail. These are areas of extremely changeable offshore sediment transport patterns. Computer generated contouring of radiance levels resulted in maps that can be used in determining surface and nearsurface suspended sediment distribution. Tentative calibrations of ERTS-1 spectral brightness against sediment load have been made using shipboard measurements. Information from the combined enhancement and interpretation techniques is applicable to operational coastal engineering programs.

Pirie, D. M.↗
NASA NTRS1974

Geologic structure in California: Three studies with ERTS-1 imagery

Results are presented of three early applications of imagery from the NASA Earth Resources Technology Satellite to geologic studies in California. In the Coast Ranges near Monterey Bay, numerous linear drainage features possibly indicating unmapped fracture zones were mapped within one week after launch of the satellite. A similar study of the Sierra Nevada near Lake Tahoe revealed many drainage features probably formed along unmapped joint or faults in granitic rocks. The third study, in the Peninsular Ranges, confirmed existence of several major faults not shown on published maps. One of these, in the Sawtooth Range, crosses in Elsinore fault without lateral offset; associated Mid-Cretaceous structures have also been traced continuously across the fault without offset. It therefore appears that displacement along the Elsinore fault has been primarily of a dip-slip nature, at least in this area, despite evidence for lateral displacement elsewhere.

Lowman, P. D., Jr.↗
NASA NTRS1977

Determination of ocean wave heights from synthetic aperture radar imagery

A calculation is presented for the cross-correlation of the radar images obtained by processing the same signal data over different portions of the chirp spectrum bandwidth as a function of the center frequency spacings for these portions. This is shown to be proportional to the square of the product of the characteristic function for ocean wave heights and the pupil function describing the chirp spectrum bandwidth used in the processing. Measurements of this function for ocean wave imagery over the coast of Alaska, the North Atlantic, and Monterey Bay, California, and correlation with the significant wave heights reported from ground truth data indicate that the synthetic aperture radar instrument can be used for providing wave height information in addition to the ocean wave imagery.

Jain, A.↗