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At least 199 records · Page 11

Remote sensing of chlorophyll concentrations in the northern Gulf of Mexico

During a 17 month period (November 1978 - March 1980), phytoplankton pigment concentrations were remotely sensed in the northern Gulf of Mexico using the Coastal Zone Color Scanner (CZCS). A total of 29 CZCS orbits were processed into pigment (chlorophyll a + phaeopigments) images and then geometrically warped to a Mercator projection. A correction factor of 1.67 was applied to the pigment concentrations to correct for the tendency of the standard fluorometric method to underestimate chlorophyll a concentrations. The spatial and temporal distributions of pigment fronts were quite variable during this time series. Constant features observed throughout the pigment imagery were the entrainment of coastal waters offshore. The most extensive entrainments occurred during intrusions of the Loop Current. For the 17 month survey, the mean HPLC-corrected pigment concentration was 3.30 + or - 1.45 mg/cu m.

Trees, Charles C.↗

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 (aboard both Aqua and Terra) and VIIRS OC products using 30 m 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 R(sub rs) products in coastal waters. Various OLI OC products representing different productivity levels and in-water spatial features were 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 R(sub rs)(443), R(sub rs)(482), R(sub rs)(561), R(sub rs)(655), Chla, K(sub d)(482), and b(sub bp)(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 station 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 7 km × 7 km areas, b) VIIRS observations, with improved consistency in cross-track spatial sampling, yield more precise calibration/validation statistics than that of MODIS, and c) use of a single pixel centered on in-situ coastal stations 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 ocean color missions and the associated calibration/validation exercises.

Coastal ocean color↗

Retrieval of Aerosol Optical Depth Under Thin Cirrus from MODIS: Application to an Ocean Algorithm

A strategy for retrieving aerosol optical depth (AOD) under conditions of thin cirrus coverage from the Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. We adopt an empirical method that derives the cirrus contribution to measured reflectance in seven bands from the visible to shortwave infrared (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 μm, commonly used for AOD retrievals) by using the correlations between the top-of-atmosphere (TOA) reflectance at 1.38 micron and these bands. The 1.38 micron band is used due to its strong absorption by water vapor and allows us to extract the contribution of cirrus clouds to TOA reflectance and create cirrus-corrected TOA reflectances in the seven bands of interest. These cirrus-corrected TOA reflectances are then used in the aerosol retrieval algorithm to determine cirrus-corrected AOD. The cirrus correction algorithm reduces the cirrus contamination in the AOD data as shown by a decrease in both magnitude and spatial variability of AOD over areas contaminated by thin cirrus. Comparisons of retrieved AOD against Aerosol Robotic Network observations at Nauru in the equatorial Pacific reveal that the cirrus correction procedure improves the data quality: the percentage of data within the expected error +/-(0.03 + 0.05 ×AOD) increases from 40% to 80% for cirrus-corrected points only and from 80% to 86% for all points (i.e., both corrected and uncorrected retrievals). Statistical comparisons with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals are also carried out. A high correlation (R = 0.89) between the CALIOP cirrus optical depth and AOD correction magnitude suggests potential applicability of the cirrus correction procedure to other MODIS-like sensors.

cirrus correction↗

Real Time HABs Mapping Using NASA Glenn Hyperspectral Imager

The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015- 2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 hours) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument calibration signals. A large asphalt parking lot near the Western Basin of Lake Erie was spectrally characterized and was determined to be a suitable correction target. Due to the HSI deployment aboard an aircraft, it is able to provide unique insights into water quality conditions not offered by space-based solutions. Aircraft can operate under cloud cover and flight paths can be chosen and changed on-demand, allowing for far more flexibility than space-based platforms. The HSI is also able to collect data at a high spatial resolution (~1 m), allowing for the monitoring of small water bodies, the ability to detect small patches of surface scum, and the capability to monitor the proximity of blooms to targets of interest such as water intakes. With this new rapid turnaround time, airborne data can serve as a complementary monitoring tool to existing satellite platforms, targeting critical areas and responding to bloom events on-demand.

Reid W Sawtell↗

Real Time HABs Mapping Using NASA Glenn Hyperspectral Imager

The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015- 2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 hours) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument calibration signals. A large asphalt parking lot near the Western Basin of Lake Erie was spectrally characterized and was determined to be a suitable correction target. Due to the HSI deployment aboard an aircraft, it is able to provide unique insights into water quality conditions not offered by space-based solutions. Aircraft can operate under cloud cover and flight paths can be chosen and changed on-demand, allowing for far more flexibility than space-based platforms. The HSI is also able to collect data at a high spatial resolution (~1 m), allowing for the monitoring of small water bodies, the ability to detect small patches of surface scum, and the capability to monitor the proximity of blooms to targets of interest such as water intakes. With this new rapid turnaround time, airborne data can serve as a complementary monitoring tool to existing satellite platforms, targeting critical areas and responding to bloom events on-demand.

Reid W Sawtell↗

Correction of magnetooptic device phase errors in optical correlators through filter design modifications

We address the problem of optical phase errors in an optical correlator introduced by the input and filter plane spatial light modulators. Specifically, we study a laboratory correlator with magnetooptic spatial light modulator (MOSLM) devices. We measure and characterize the phase errors, analyze their effects on the correlation process, and discuss a means of correction through a design modification of the binary phase-only optical filter function. The phase correction technique is found to produce correlation results close to those of an error-free correlator.

Downie, John D.↗

Effect of atmospherics on beamforming accuracy

Two mathematical representations of noise due to atmospheric turbulence are presented. These representations are derived and used in computer simulations of the Bartlett Estimate implementation of beamforming. Beamforming is an array processing technique employing an array of acoustic sensors used to determine the bearing of an acoustic source. Atmospheric wind conditions introduce noise into the beamformer output. Consequently, the accuracy of the process is degraded and the bearing of the acoustic source is falsely indicated or impossible to determine. The two representations of noise presented here are intended to quantify the effects of mean wind passing over the array of sensors and to correct for these effects. The first noise model is an idealized case. The effect of the mean wind is incorporated as a change in the propagation velocity of the acoustic wave. This yields an effective phase shift applied to each term of the spatial correlation matrix in the Bartlett Estimate. The resultant error caused by this model can be corrected in closed form in the beamforming algorithm. The second noise model acts to change the true direction of propagation at the beginning of the beamforming process. A closed form correction for this model is not available. Efforts to derive effective means to reduce the contributions of the noise have not been successful. In either case, the maximum error introduced by the wind is a beam shift of approximately three degrees. That is, the bearing of the acoustic source is indicated at a point a few degrees from the true bearing location. These effects are not quite as pronounced as those seen in experimental results. Sidelobes are false indications of acoustic sources in the beamformer output away from the true bearing angle. The sidelobes that are observed in experimental results are not caused by these noise models. The effects of mean wind passing over the sensor array as modeled here do not alter the beamformer output as significantly as expected.

Alexander, Richard M.↗

A cloud classification scheme applied to the breakup region of marine stratocumulus

A major goal of the marine stratocumulus (MSc) segment of FIRE is to describe and explain the temporal and spatial variability in fractional cloud cover. The challenge from a theoretical standpoint is to correctly represent the mechanisms leading to the transitions between solid stratus, stratocumulus and trade wind cumulus. The development and testing of models accounting for fractional cloudiness require an observational data base that will come primarily from satellites. This, of course, is one of the missions of the ISCCP. There are a number of satellite cloud analysis programs that are being undertaken as part of FIRE. One that has already produced data from the FIRE MSc experiment is the spatial coherence method (COAKLEY and Baldwin, 1984). This method produces information on fractional cloud coverage and cloud heights. It may be possible, however, to extract more information on cloud structure from satellite data that might be of use in describing the transitions in the marine stratocumulus cloud deck. Potential applications are explored of a cloud analysis scheme relying on more detailed analysis of visible and infrared cloud radiance statistics. For this preliminary study, data is examined from three days during the 1987 FIRE MSc field work. These case studies provide a basis for comparison and evaluation of the technique.

Khalsa, Siri Jodha Singh↗

Direct and indirect methods for correcting the aerosol effect on remote sensing

Aspects of aerosol studies and remote sensing are reviewed. Aerosol scatters solar radiation before it reaches the surface and scatters and absorbs it again after it is reflected from the surface and before it reaches the satellite sensor. The effect is spectrally and spatially dependent. Therefore atmospheric aerosol (dust, smoke and air pollution particles) has a significant effect on remote sensing. Correction for the aerosol effect was never achieved on an operational basis though several case studies were demonstrated. Correction can be done in a direct way by deriving the aerosol loading from the image itself and correcting for it using the appropriate radiative transfer model or by an indirect way, by defining remote sensing functions that are less dependent on the aerosol loading. To some degree this was already achieved in global remote sensing of vegetation where a composite of several days of NDVI (Normalized Difference Vegetation Index) measurements, choosing the maximal value, was used instead of a single cloud screened value. The Atmospheric Resistant Vegetation Index (ARVI) introduced recently for the NASA Earth Observing System EOS-MODIS is the most appropriate example of indirect correction, where the index is defined in such a way that the atmospheric effect in the blue spectral channel cancels to a large degree the atmospheric in the red channel in computations of a vegetation index. Atmospheric corrections can also use aerosol climatology and ground based instrumentation.

Kaufman, Yoram J.↗

An Overview of LANDSAT-4 and the Thematic Mapper

The LANDSAT 4 satellite and its orbit, the Thematic Mapper (TM) sensor design, and the ground processing of TM data are discussed. The design of LANDSAT 4 incorporates several technological advancements which include the TM. The TM offers refinements over the familiar Multispectral Scanners (MSS's) aboard all of the LANDSAT satellites in terms of spatial, spectral, and radiometric resolutions. The TM data undergo radiometric and geometric corrections on the ground to provide investigators with pictorial and digital image data products.

Irons, J. R.↗

Nested neural networks

Nested neural networks, consisting of small interconnected subnetworks, allow for the storage and retrieval of neural state patterns of different sizes. The subnetworks are naturally categorized by layers of corresponding to spatial frequencies in the pattern field. The storage capacity and the error correction capability of the subnetworks generally increase with the degree of connectivity between layers (the nesting degree). Storage of only few subpatterns in each subnetworks results in a vast storage capacity of patterns and subpatterns in the nested network, maintaining high stability and error correction capability.

Baram, Yoram↗

Non-Gaussian microwave background fluctuations from nonlinear gravitational effects

Whether the statistics of primordial fluctuations for structure formation are Gaussian or otherwise may be determined if the Cosmic Background Explorer (COBE) Satellite makes a detection of the cosmic microwave-background temperature anisotropy delta T(sub CMB)/T(sub CMB). Non-Gaussian fluctuations may be generated in the chaotic inflationary model if two scalar fields interact nonlinearly with gravity. Theoretical contour maps are calculated for the resulting Sachs-Wolfe temperature fluctuations at large angular scales (greater than 3 degrees). In the long-wavelength approximation, one can confidently determine the nonlinear evolution of quantum noise with gravity during the inflationary epoch because: (1) different spatial points are no longer in causal contact; and (2) quantum gravity corrections are typically small-- it is sufficient to model the system using classical random fields. If the potential for two scalar fields V(phi sub 1, phi sub 2) possesses a sharp feature, then non-Gaussian fluctuations may arise. An explicit model is given where cold spots in delta T(sub CMB)/T(sub CMB) maps are suppressed as compared to the Gaussian case. The fluctuations are essentially scale-invariant.

Salopek, D. S.↗

Evaluating the design of an Earth Radiation Budget Instrument with systen simulations. Part 1: Instantaneous estimates

A set of system simulations has been performed to evaluate candidate scanner designs for an Earth Radiation Budget Instrument (ERBI) for the Earth Observing System (EOS) of the late 1990s. Five different instruments are considered: (1) the Active Cavity Array (ACA), (2) the Clouds and Earth's Radiant Energy System-Instrument (CERES-I), (3) the Conically Scanning Radiometer (CSR), (4) the Earth Radiation Budget Experiment Cross-Track Scanner (ERBE), and (5) the Nimbus-7 Biaxial Scanner (N7). Errors in instantaneous, top-of-the-atmosphere (TOA) satellite flux estimates are assumed to arise from two measurement problems: the sampling of space over a given geographic domain, and sampling in angle about a given spatial location. When angular sampling errors vanish due to the application of correct angular dependence models (ADMs) during inversion, the accuracy of each scanner design is determined by the instrument's ability to map the TOA radiance field in a uniform manner. In this regard, the instruments containing a cross-track scanning component (CERES-I and ERBE) do best. As errors in ADMs are encountered, cross-track instruments incur angular sampling errors more rapidly than biaxial instruments (N7, ACA, and CSR) and eventually overtake the biaxial designs in their total error amounts. A latitude bias (north-south error gradient) in the ADM error of cross-track instruments also exists. This would be objectionable when ADM errors are systematic over large areas of the globe. For instantaneous errors, however, cross-track scanners outperform biaxial or conical scanners for 2.5 deg latitude x 2.5 deg longitude target areas, providing that the ADM error is less than or equal to 30%. A key issue is the amount of systematic ADM error (departures from the mean models) that is present at the 2.5 deg resolution of the ERBE target areas. If this error is less than 30%, then the CERES-I, ERBE, and CSR, in order of increasing error, provide the most accurate instantaneous flux estimates, within 2-3 W/sq m of each other in reflected shortwave flux. The magnitude of this error is near the 10 W/sq m accuracy requirement of the user community. Longwave flux errors have been found to have the same space and time characteristics as errors in shortwave radiation, but only about 25% as large.

Stowe, Larry↗

Advanced Modeling of Micromirror Devices

The flexure-beam micromirror device (FBMD) is a phase only piston style spatial light modulator demonstrating properties which can be used for phase adaptive corrective optics. This paper presents a complete study of a square FBMD, from advanced model development through final device testing and model verification. The model relates the electrical and mechanical properties of the device by equating the electrostatic force of a parallel-plate capacitor with the counter-acting spring force of the device's support flexures. The capacitor solution is derived via the Schwartz-Christoffel transformation such that the final solution accounts for non-ideal electric fields. The complete model describes the behavior of any piston-style device, given its design geometry and material properties. It includes operational parameters such as drive frequency and temperature, as well as fringing effects, mirror surface deformations, and cross-talk from neighboring devices. The steps taken to develop this model can be applied to other micromirrors, such as the cantilever and torsion-beam designs, to produce an advanced model for any given device. The micromirror devices studied in this paper were commercially fabricated in a surface micromachining process. A microscope-based laser interferometer is used to test the device in which a beam reflected from the device modulates a fixed reference beam. The mirror displacement is determined from the relative phase which generates a continuous set of data for each selected position on the mirror surface. Plots of this data describe the localized deflection as a function of drive voltage.

Michalicek, M. Adrian↗

A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks

Retrieval of aquatic biogeochemical variables, such as the near-surface concentration of chlorophyll-a (Chla) in inland and coastal waters via remote observations, has long been regarded as a challenging task. This manuscript applies Mixture Density Networks (MDN) that use the visible spectral bands available by the Operational Land Imager (OLI) aboard Landsat-8 to estimate Chla. We utilize a database of co-located in situ radiometric and Chla measurements (N = 4,354), referred to as Type A data, to train and test an MDN model (MDN(A)). This algorithm’s performance, having been proven for other satellite missions, is further evaluated against other widely used machine learning models (e.g., support vector machines), as well as other domain-specific solutions (OC3), and shown to offer significant advancements in the field. Our performance assessment using a held-out test data set suggests that a 49% (median) accuracy with near-zero bias can be achieved via the MDN(A) model, offering improvements of 20 to 100% in retrievals with respect to other models. The sensitivity of the MDN(A) model and benchmarking methods to uncertainties from atmospheric correction (AC) methods, is further quantified through a semi-global matchup dataset (N = 3,337), referred to as Type B data. To tackle the increased uncertainties, alternative MDN models (MDN(B)) are developed through various features of the Type B data (e.g., Rayleigh-corrected reflectance spectra ρ(s)). Using held-out data, along with spatial and temporal analyses, we demonstrate that these alternative models show promise in enhancing the retrieval accuracy adversely influenced by the AC process. Results lend support for the adoption of MDN(B) models for regional and potentially global processing of OLI imagery, until a more robust AC method is developed. Index Terms—Chlorophyll-a, coastal water, inland water, Landsat-8, machine learning, ocean color, aquatic remote sensing.

Brandon Smith↗

Focal Gray Matter Plasticity as a Function of Long Duration Head Down Tilted Bed Rest: Preliminary Results

Long duration spaceflight (i.e., 22 days or longer) has been associated with changes in sensorimotor systems, resulting in difficulties that astronauts experience with posture control, locomotion, and manual control. The microgravity environment is an important causal factor for spaceflight induced sensorimotor changes. Whether these sensorimotor changes are solely related to peripheral changes from reduced vestibular stimulation, body unloading, body fluid shifts or that they may be related to structural and functional brain changes is yet unknown. However, a recent study reported associations between microgravity and flattening of the posterior eye globe and protrusion of the optic nerve [1] possibly as the result of increased intracranial pressure due to microgravity induced bodily fluid shifts [3]. Moreover, elevated intracranial pressure has been related to white matter microstructural damage [2]. Thus, it is possible that spaceflight may affect brain structure and thereby cognitive functioning. Long duration head down tilt bed rest has been suggested as an exclusionary analog to study microgravity effects on the sensorimotor system [4]. Bed rest mimics microgravity in body unloading and bodily fluid shifts. In consideration of the health and performance of crewmembers both in- and post-flight, we are conducting a prospective longitudinal 70-day bed rest study as an analog to investigate the effects of microgravity on brain structure [5]. Here we present results of the first six subjects. Six subjects were assessed at 12 and 7 days before-, at 7, 30, and ~70 days in-, and at 8 and 12 days post 70 days of bed rest at the NASA bed rest facility in UTMB, Galveston, TX, USA. At each time point structural MRI scans (i.e., high resolution T1-weighted imaging and Diffusion Tensor Imaging (DTI)) were obtained using a 3T Siemens scanner. Focal changes over time in gray matter density were assessed using the voxel based morphometry 8 (VBM8) toolbox under SPM. Longitudinal processing in VBM8 includes linear registration of each scan to the mean of the subject and subsequently transforming all scans in to MNI space by applying the warp from the mean subject to MNI to the individual gray matter segmentations. Modulation was applied so that all images represented the volume of the original structure in native space. Voxel wise analysis was carried out on the gray matter images after smoothing, using a flexible factorial design with family wise error correction. Focal changes in white matter microstructural integrity were assessed using tract based spatial statistics (TBSS) as part of FMRIB software library (FSL). TBSS registers all DTI scans to standard space. It subsequently creates a study specific white matter skeleton of the major white matter tracts. For each subject, for each DTI metric (i.e. fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD)), the maximum value in a line perpendicular to the skeleton tract is projected to the skeleton. Non-parametric permutation based t-tests and ANOVA's were used for voxel-wise comparison of the skeletons. For both VBM and TBSS, comparison of pre bed rest measurements did not show significant differences. VBM analysis revealed decreased gray matter density in bilateral areas including the frontal medial cortex, the insular cortex and the caudate (see Figure) from 'pre to in bed rest'. Over the same time period, there was an increase in gray matter density in the cerebellum, occipital-, and parietal cortex, including the precuneus (see Figure). The majority of these changes did not recover from 'during to post bed rest'. TBSS analysis did not reveal significant changes in white matter microstructural integrity after correction for multiple comparisons. Uncorrected analyses (p<.015) revealed an increase in RD in the cerebellum and brainstem from pre bed rest to the first week in bed rest that did not recover post bed rest. Extended bed rest, which is an analog for microgravity, can result in gray matter changes and potentially in microstructural white matter changes in areas that are important for neuro motor behavior and cognition. These changes did not recover at two weeks post bed rest. Whether the effects of bed rest wear off at longer times post bed rest, and if they are associated with behavior are important questions that warrant further research.

Koppelmans, V.↗

Dynamic Black-Level Correction and Artifact Flagging in the Kepler Data Pipeline

Instrument-induced artifacts in the raw Kepler pixel data include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, manifestations of drifting moiré pattern as locally correlated nonstationary noise and rolling bands in the images which find their way into the calibrated pixel time series and ultimately into the calibrated target flux time series. Using a combination of raw science pixel data, full frame images, reverse-clocked pixel data and ancillary temperature data the Keplerpipeline models and removes the FGS crosstalk artifacts by dynamically adjusting the black level correction. By examining the residuals to the model fits, the pipeline detects and flags spatial regions and time intervals of strong time-varying blacklevel (rolling bands ) on a per row per cadence basis. These flags are made available to downstream users of the data since the uncorrected rolling band artifacts could complicate processing or lead to misinterpretation of instrument behavior as stellar. This model fitting and artifact flagging is performed within the new stand-alone pipeline model called Dynablack. We discuss the implementation of Dynablack in the Kepler data pipeline and present results regarding the improvement in calibrated pixels and the expected improvement in cotrending performances as a result of including FGS corrections in the calibration. We also discuss the effectiveness of the rolling band flagging for downstream users and illustrate with some affected light curves.

Clarke, B. D.↗

Atmospheric Correction for Remote Sensor Data

Mathematical model based on radiative transfer theory as applied to plane parallel, horizontally spatially homogeneous, isotropic atmosphere. Model includes effects of multiple scattering by gases and aerosols, and effects of absorption by ozone in near ultraviolet and visible parts of spectrum.

Turner, R. E.↗