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At least 163 records · Page 9

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗

Next-Generation Sensing Technologies for Exploring Ocean Worlds

Dr. Ved Chirayath's plenary presentation will highlight two instrument technologies he invented at NASA including Fluid Lensing, the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions, and MiDAR (Multispectral Imaging, Detection and Active Reflectance), a next-generation active hyperspectral remote sensing and optical communications instrument. Fluid Lensing has been used to provide the first 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft, and underwater remotely operated vehicles (ROVs) as a new method to remotely sense living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an object's non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Finally, Chirayath will present preliminary results from NASA NeMO-Net (Neural Multi-Modal Observation and Training Network), the first neural network for global coral reef classification using fluid lensing and MiDAR.

Technologies↗

NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and aquatic organics.

fluid lensing↗

Daylight imagery of ocean surface waves for wave spectra

A simple second-order model is developed to describe the transformation between surface wave slope and radiance incident on an optical sensor. The model includes azimuth as well as elevation variations in the sky-radiance distribution and their effects on the imaging of wave slopes approaching the sensor azimuth from various directions. The model also includes upwelling radiance. Comparison between the exact transformation from wave slope to radiance and the second-order model suggests that they yield quantitatively similar results. The model is used in physical interpretations of how wave slopes are imaged and in indicating a way of optimizing the linearity and contrast of the transfer function relating wave slope to radiance for various sensor geometries, thereby minimizing sources of error. One-dimensional numerical simulations of the imaging of an analytically generated wave-slope profile demonstrate the utility of this technique in obtaining slope spectra.

Monaldo, F. M.↗

On the detection of underwater bottom topography by imaging radars

A theoretical model which explains basic properties of radar imaging of underwater bottom topography in tidal channels is presented. The surface roughness modulation is described by weak hydrodynamic interaction theory in the relaxation time approximation. In contrast to previous theories on short wave modulation by long ocean waves, a different approximation is used to describe short wave modulation by tidal flow over underwater bottom topography. The modulation depth is proportional to the relaxation time of the Bragg waves. The large modulation of radar reflectivity observed in SEASAT-SAR imagery of sand banks in the Southern Bight of the North Sea are explained by assuming that the relaxation time of 34 cm Bragg waves is of the order of 30-40 seconds.

Alpers, W.↗

Containerless Ripple Turbulence

One of the longest standing unsolved problems in physics relates to the behavior of fluids that are driven far from equilibrium such as occurs when they become turbulent due to fast flow through a grid or tidal motions. In turbulent flows the distribution of vortex energy as a function of the inverse length scale [or wavenumber 'k'] of motion is proportional to 1/k(sup 5/3) which is the celebrated law of Kolmogorov. Although this law gives a good description of the average motion, fluctuations around the average are huge. This stands in contrast with thermally activated motion where large fluctuations around thermal equilibrium are highly unfavorable. The problem of turbulence is the problem of understanding why large fluctuations are so prevalent which is also called the problem of 'intermittency'. Turbulence is a remarkable problem in that its solution sits simultaneously at the forefront of physics, mathematics, engineering and computer science. A recent conference [March 2002] on 'Statistical Hydrodynamics' organized by the Los Alamos Laboratory Center for Nonlinear Studies brought together researchers in all of these fields. Although turbulence is generally thought to be described by the Navier-Stokes Equations of fluid mechanics the solution as well as its existence has eluded researchers for over 100 years. In fact proof of the existence of such a solution qualifies for a 1 M$ millennium prize. As part of our NASA funded research we have proposed building a bridge between vortex turbulence and wave turbulence. The latter occurs when high amplitude waves of various wavelengths are allowed to mutually interact in a fluid. In particular we have proposed measuring the interaction of ripples [capillary waves] that run around on the surface of a fluid sphere suspended in a microgravity environment. The problem of ripple turbulence poses similar mathematical challenges to the problem of vortex turbulence. The waves can have a high amplitude and a strong nonlinear interaction. Furthermore, the steady state distribution of energy again follows a Kolmogorov scaling law; in this case the ripple energy is distributed according to 1/k (sup 7/4). Again, in parallel with vortex turbulence ripple turbulence exhibits intermittency. The problem of ripple turbulence presents an experimental opportunity to generate data in a controlled, benchmarked system. In particular the surface of a sphere is an ideal environment to study ripple turbulence. Waves run around the sphere and interact with each other, and the effect of walls is eliminated. In microgravity this state can be realized for over 2 decades of frequency. Wave turbulence is a physically relevant problem in its own right. It has been studied on the surface of liquid hydrogen and its application to Alfven waves in space is a source of debate. Of course, application of wave turbulence perspectives to ocean waves has been a major success. The experiment which we plan to run in microgravity is conceptually straightforward. Ripples are excited on the surface of a spherical drop of fluid and then their amplitude is recorded with appropriate photography. A key challenge is posed by the need to stably position a 10cm diameter sphere of water in microgravity. Two methods are being developed. Orbitec is using controlled puffs of air from at least 6 independent directions to provided the positioning force. This approach has actually succeeded to position and stabilize a 4cm sphere during a KC 135 segment. Guigne International is using the radiation pressure of high frequency sound. These transducers have been organized into a device in the shape of a dodecahedron. This apparatus 'SPACE DRUMS' has already been approved for use for combustion synthesis experiments on the International Space Station. A key opportunity presented by the ripple turbulence data is its use in driving the development of codes to simulate its properties.

Putterman, Seth↗

Meridional component of oceanic Rossby wave propagation

A three-dimensional spectral analysis of Topex altimeter data reveals a large meridional component k(y) of the wavevector k for baroclinic Rossby waves of all timescales. Its existence necessitates some refinements in our estimates of certain basic properties of the Rossby wave field. In particular, by taking into account an actual off-zonal direction of k (often exceeding 70 degrees), one finds that the wavelength, phase speed, and group velocity of mid-latitude Rossby waves (with periods less than 2 years) are much smaller than they appear to be on the assumption of a purely zonal wavenumber vector. Because of a shorter wavelength (yielding U as high as 0.6, where L is the Rossby radius of deformation), these waves are essentially dispersive. Their group velocity vector may depart from zonal by more than 30 degrees. An important intrinsic feature of the wave spectrum confirmed by our analysis is a broadband distribution with respect to k(y). Some of the dynamical implications of the large k(y)/k(x), ratio are discussed.

Satellite altimetry↗

The effect of the degree of wave development on the sea state bias in radar altimetry measurement

The extent by which the wave development affects the sea state bias (SSB) in the Geosat altimeter height measurements is investigated. It is shown that the altimetric SSB is not a linear function of the wave height but that it also depends on other factors of wave development, particularly on the wave age (defined as the ratio of the phase speed of the dominant ocean waves to the ocean wind speed). The wave age can be estimated crudely, as the so-called 'pseudo-wave age', on the basis of the significant wave height H(1/3) and the wind speed measured by the altimeter. The analysis of 2.7 years' worth of Geosat data showed a general trend for the dependence of the SSB on the pseudo-wave age, which agrees well with the theoretical prediction that, for a given H(1/3), the SSB decreases as the pseudo-wave age increases.

Fu, Lee-Lueng↗

Ocean wind field measurement performance of the ERS-1 scatterometer

The Active Microwave Instrumentation (AMI), which will be implemented on the ERS-1, is a 5.3 GHz multipurpose radar for land surface imaging, ocean wave spectrum measurement and wind observations over oceans. The imaging and wave measurements apply Synthetic Aperture Radar (SAR) techniques, while wind field detection is performed by the Scatterometer as part of the AMI. The Scatterometer system design was developed and optimized with the aid of a performance simulator. This paper, aimed at giving an overview, is presented about the: (1) ERS-1 Scatterometer system design; (2) Error budget; and the (3) Overall calibration concept.

Hans, P.↗

An investigation of the modulation of capillary and short gravity waves in the open ocean

A preliminary investigation of the modulation of capillary and gravity waves by long ocean waves is described. A pressure transducer is used to obtain water surface displacements, and a high-response laser-optical system is used to detect short-wave slopes. Analytical techniques are developed to account for the orbital motion of long waves. The local mean squared wave slope is found to be maximum leeward of the long-wave crests. For the long waves studied here and for short waves from 1 cm to 1 m, the longer a short-wave component is, the more leeward its maximum tends to occur. Also, the shortest waves tend to modulate least. The modulation of short waves is found to be strong enough to be an important component of the synthetic aperture radar image formation mechanism for long ocean waves.

Evans, D. D.↗

Modulation of centimetric waves by long gravity waves - Progress report on field and laboratory results

Results are presented from laboratory and field experiments on the modulation of short waves by long waves. The field study employed a wave follower capable of tracking ocean waves with frequencies less than 1.0 Hz and heights less than 2.0 m. A high-response laser-optical system was used to detect upwind-downwind and cross-wind slopes of short waves. The laboratory study was conducted with wind over periodic long waves. The laboratory findings are discussed and compared with laboratory radar measurements and also short wave measurements obtained in the field. It is found that long waves significantly modulate the short wave dispersion by their orbital velocity, and that demodulation is necessary if the data collected by remote sensors are to be compared to surface penetrating devices. The modulation level is weak for wavelengths in the range 2.76-3.30 cm. Other relevant results are also presented.

Shemdin, O. H.↗

Observations of the polar regions from satellites using active and passive microwave techniques

Observations of the ocean ice, ice sheets, ice edges, and ocean waves in the Antarctic, performed by the Seasat and Nimbus-7 satellites are described. Specific features of the Seasat altimeter, the SAR, the Seasat-A Scatterometer System, and the Scanning Multichannel Microwave Radiometer (SMMR) are discussed, together with the advantages and limitations of each instrument as applied to the study of ice dynamics. The Nimbus-7 SMMR algorithm for calculating sea-ice concentrations is presented. In addition, the Seasat altimeter-derived data on wind speed and wave heights in the Southern Ocean, and on the ice sheets of the Antarctica and Greenland were evaluated.

Swift, C. T.↗

Combined High-Resolution Active and Passive Imaging of Ocean Surface Winds from Aircraft

A unique complement of passive and active microwave imaging and sensing instruments for observing ocean surface emission and scattering signatures were integrated onto the NASA Wallops Flight Facility's Orion P-3B aircraft (N426NA) for the purpose of studying the signature of ocean surface winds. The complement included: (1) a, four-band (X, K, Ka, and W) tri-polarimetric scanning radiometer (PSR), (2) a C-band ocean surface scatterometer (CSCAT), (3) a Ka-band conical-scanning polarimetric radiometer (KASPR), (4) a nadir-viewing Ka-band polarimetric radiometer, (KAPOL), (5) a 21- and 31-GHz zenith-viewing cloud and water vapor radiometer (CWVR), and (6) a radar ocean wave spectrometer (ROWS). The above Ocean Winds Imaging (OWI) complement was flown during January-March, 1997 over the Labrador Sea. Conically-scanned brightness temperature and backscatter imagery were observed over open ocean for a variety of wind speeds and cloud conditions. Presented herein are the results of a preliminary intercomparison of data from several of the OWI instruments.

Gasiewski, A. J.↗

Observations with the ROWS instrument during the Grand Banks calibration/validation experiments

As part of a global program to validate the ocean surface sensors on board ERS-1, a joint experiment on the Grand Banks of Newfoundland was carried out in Nov. 1991. The principal objective was to provide a field validation of ERS-1 Synthetic Aperture Radar (SAR) measurement of ocean surface structure. The NASA-P3 aircraft measurements made during this experiment provide independent measurements of the ocean surface along the validation swath. The Radar Ocean Wave Spectrometer (ROWS) is a radar sensor designed to measure direction of the long wave components using spectral analysis of the tilt induced radar backscatter modulation. This technique greatly differs from SAR and thus, provides a unique set of measurements for use in evaluating SAR performance. Also, an altimeter channel in the ROWS gives simultaneous information on the surface wave height and radar mean square slope parameter. The sets of geophysical parameters (wind speed, significant wave height, directional spectrum) are used to study the SAR's ability to accurately measure ocean gravity waves. The known distortion imposed on the true directional spectrum by the SAR imaging mechanism is discussed in light of the direct comparisons between ERS-1 SAR, airborne Canadian Center for Remote Sensing (CCRS) SAR, and ROWS spectra and the use of the nonlinear ocean SAR transform.

Vandemark, D.↗