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NASA NTRS1980

Irrigation mapping in western Kansas using Landsat. I - Key parameters

The procedure used in the identification and mapping of irrigated lands in six counties of western Kansas is presented and key considerations for the identification of irrigated lands during the project are discussed. The procedure involved the compilation of a field-by-field map of irrigated lands on the basis of multi-date Landsat band 5 imagery, the entry of map data into a computer, and the retrieval of the data in the form of maps, tables and statistics. Comparison of the positional results of the image interpretation with statistical data for a single county was used to verify the mapping procedure, as accuracies of from 80-100% were obtained, depending on the type of crop. Considerations relevant to the identification of irrigated land on the basis of remote sensing data include the form of the final data, irrigation practices in the area, the soil moisture budget, the number and kinds of crops, the crop calendar, and the availability of usable imagery.

Poracsky, J.↗

NASA NTRS1981

Delineation of soil temperature regimes from HCMM data

Evaluation of LANDSAT and Heat Capacity Mapping Mission (HCMM) data as input into National Cooperative Soil Survey is discussed. Signature classification techniques were applied to 13 May 76 LANDSAT data. LANDSAT data was overlaid with HCMM data, revealing registration problems caused by a shortage of control points in LANDSAT data, and the WARP program developed to improve registration accuracy. Initial images for control point selection were produced using digital terrain elevation data. Statistical procedures for evaluating data classification and to describe spatial distribution of surface temperature and its correlation with soil surface conditions were investigated.

Day, R. L.↗

NASA NTRS1987

On the possibility of observing cosmic ray sources in high energy gamma rays

If cosmic rays are accelerated by strong shocks, then cosmic ray sources should be characterized by spectra, dN/dE alpha E exp -(2.0-2.2), reflecting the strength of those shocks. This is expected from the 'standard leaky box' model of cosmic ray propagation in which the source spectra are harder than the observed spectra because higher energy particles have shorter residence times in the galactic magnetic fields. Furthermore, data on cosmic ray nucleons suggest that these sources might be surrounded by material. If the latter is true, such sources should be observable in gamma rays at energies beyond 1 GeV where the angular resolution of gamma-ray telescopes is optimized and the background is significantly reduced. For identified sources, the source location accuracy can be shown to improve with increasing energy in spite of the decreasing statistics, as long as the gamma-ray spectrum is harder than dN/dE alpha E exp -gamma. A Monte Carlo model is used to predict the photon spectra which would be expected from cosmic ray sources under varying assumptions about the strength of the shocks in the acceleration region.

Ormes, J. F.↗

NASA NTRS1991

Young's fringe particle image velocimetry in the presence of random particle motions

In the Young's fringe approach to particle image velocimetry, random particle motions cause loss of fringe visibility by decorrelating the coherent interexposure particle separations responsible for fringe formation. Since the visibility reduction is determined by the random motion through a Fourier transform relation analogous to the Van Cittert Zernike Theorem, it has been proposed that the random motion can be characterized statistically by analyzing fringe visibility distributions in the transform plane. This paper assesses the accuracy of such measurements. In particular, the effects of finite particle population and of correlated random motion are evaluated. The theory applies to diffusive motion, turbulence, and to random motion caused by mean velocity inhomogeneities.

Rubinstein, R.↗

NASA NTRS1992

Measurement of two-dimensional fluid flow by digital correlation of scattered light

Digital correlation is a pattern matching procedure. This procedure has recently been used in two-dimensional fluid flow measurements. Two images of a seeded fluid are taken and the intensity distribution of a small window in the first image is matched in the second image using a statistical correlation method. A series of structure functions have been implemented to improve the accuracy and reliability of the correlation method and new algorithms have been developed to reduce the time required for the correlation computations.

Matthys, Donald R.↗

NASA NTRS2002

Micro-Pulse Lidar Signals: Uncertainty Analysis

Micro-pulse lidar (MPL) systems are small, autonomous, eye-safe lidars used for continuous observations of the vertical distribution of cloud and aerosol layers. Since the construction of the first MPL in 1993, procedures have been developed to correct for various instrument effects present in MPL signals. The primary instrument effects include afterpulse, laser-detector cross-talk, and overlap, poor near-range (less than 6 km) focusing. The accurate correction of both afterpulse and overlap effects are required to study both clouds and aerosols. Furthermore, the outgoing energy of the laser pulses and the statistical uncertainty of the MPL detector must also be correctly determined in order to assess the accuracy of MPL observations. The uncertainties associated with the afterpulse, overlap, pulse energy, detector noise, and all remaining quantities affecting measured MPL signals, are determined in this study. The uncertainties are propagated through the entire MPL correction process to give a net uncertainty on the final corrected MPL signal. The results show that in the near range, the overlap uncertainty dominates. At altitudes above the overlap region, the dominant source of uncertainty is caused by uncertainty in the pulse energy. However, if the laser energy is low, then during mid-day, high solar background levels can significantly reduce the signal-to-noise of the detector. In such a case, the statistical uncertainty of the detector count rate becomes dominant at altitudes above the overlap region.

Welton, Ellsworth J.↗

NASA NTRS2004

A Comparison of Local Variance, Fractal Dimension, and Moran's I as Aids to Multispectral Image Classification

The accuracy of traditional multispectral maximum-likelihood image classification is limited by the skewed statistical distributions of reflectances from the complex heterogenous mixture of land cover types in urban areas. This work examines the utility of local variance, fractal dimension and Moran's I index of spatial autocorrelation in segmenting multispectral satellite imagery. Tools available in the Image Characterization and Modeling System (ICAMS) were used to analyze Landsat 7 imagery of Atlanta, Georgia. Although segmentation of panchromatic images is possible using indicators of spatial complexity, different land covers often yield similar values of these indices. Better results are obtained when a surface of local fractal dimension or spatial autocorrelation is combined as an additional layer in a supervised maximum-likelihood multispectral classification. The addition of fractal dimension measures is particularly effective at resolving land cover classes within urbanized areas, as compared to per-pixel spectral classification techniques.

Emerson, Charles W.↗

NASA NTRS2011

Thermal and Pressure Characterization of a Wind Tunnel Force Balance Using the Single Vector System

Wind tunnel research at NASA Langley Research Center s 31-inch Mach 10 hypersonic facility utilized a 5-component force balance, which provided a pressurized flow-thru capability to the test article. The goal of the research was to determine the interaction effects between the free-stream flow and the exit flow from the reaction control system on the Mars Science Laboratory aeroshell during planetary entry. In the wind tunnel, the balance was exposed to aerodynamic forces and moments, steady-state and transient thermal gradients, and various internal balance cavity pressures. Historically, these effects on force measurement accuracy have not been fully characterized due to limitations in the calibration apparatus. A statistically designed experiment was developed to adequately characterize the behavior of the balance over the expected wind tunnel operating ranges (forces/moments, temperatures, and pressures). The experimental design was based on a Taylor-series expansion in the seven factors for the mathematical models. Model inversion was required to calculate the aerodynamic forces and moments as a function of the strain-gage readings. Details regarding transducer on-board compensation techniques, experimental design development, mathematical modeling, and wind tunnel data reduction are included in this paper.

Lynn, Keith C.↗

NASA NTRS1984

Analysis of subpixel registration

The area of subpixel accuracy in image registration and edge detection was studied. Two main directions of research were pursued, edge detection and matching based on the digital geometry of edges, and random field models for probablistic analysis of registration error. In the edge detection approach, error bounds and error probabilities were computed using theoretical models. Algorithms were developed and tests on simulated imagery. The methods appear promising for high accuracy edge position estimation and registration, though further refinement of the procedures is required. Using random field models, a statistical measure of the quality of the cross correlation peak as an estimate of the offset between a sensed and a reference image was developed. Simulations were performed to determine the validity of this estimte with real imagery and to study the results of interpolating digital correlation functions to estimate the translation offset to subpixel accuracy.

Berenstein, C. A.↗

NASA NTRS1989

Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series

Two dimensions of a dynamical system given by experimental time series are distinguished. Statistical dimension gives a theoretical upper bound for the minimal number of degrees of freedom required to describe the attractor up to the accuracy of the data, taking into account sampling and noise problems. The dynamical dimension is the intrinsic dimension of the attractor and does not depend on the quality of the data. Singular Spectrum Analysis (SSA) provides estimates of the statistical dimension. SSA also describes the main physical phenomena reflected by the data. It gives adaptive spectral filters associated with the dominant oscillations of the system and clarifies the noise characteristics of the data. SSA is applied to four paleoclimatic records. The principal climatic oscillations and the regime changes in their amplitude are detected. About 10 degrees of freedom are statistically significant in the data. Large noise and insufficient sample length do not allow reliable estimates of the dynamical dimension.

Vautard, R.↗

NASA NTRS1992

Interval prediction in structural dynamic analysis

Methods for assessing the predictive accuracy of structural dynamic models are examined with attention given to the effects of modal mass, stiffness, and damping uncertainties. The methods are based on a nondeterministic analysis called 'interval prediction' in which interval variables are used to describe parameters and responses that are unknown. Statistical databases for generic modeling uncertainties are derived from experimental data and incorporated analytically to evaluate responses. Covariance matrices of modal mass, stiffness, and damping parameters are propagated numerically in models of large space structures by means of three methods. The test data tend to fall within the predicted intervals of uncertainty determined by the statistical databases. The present findings demonstrate the suitability of using data from previously analyzed and tested space structures for assessing the predictive accuracy of an analytical model.

Hasselman, Timothy K.↗

NASA NTRS1973

The influence of laser ranging on selenodetic control.

A mathematical model for performing an adjustment, using laser distances to improve coordinates of points on the earth and on the moon, as well as the orientation of these two bodies in space, is presented. The observation equations are given, and the orientation of the earth and the moon are defined in terms of three Eulerian angles. Numerical experiments were performed to investigate the expected accuracies of parameters in the adjustment model under differing conditions. The results indicate that the statistics both for the coordinates of points on earth and on the moon, and for the orientation parameters of the two bodies are favorable. However, very high correlations exist between some of the parameters; therefore, the recovery of these parameters from a simultaneous adjustment is questionable.

Mueller, I. I.↗

NASA NTRS2009

Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud characteristics. Each system provides a unique perspective. The WSR-88D operates in a surveillance mode, sampling cloud volumes of Rayleigh scatterers where reflectivity is proportional to the sixth moment of the size distribution of equivalent spheres. The CloudSat radar provides enhanced sensitivity to smaller cloud ice crystals aloft, as well as consistent vertical profiles along each orbit. However, CloudSat reflectivity signatures are complicated somewhat by resonant Mie scattering effects and significant attenuation in the presence of cloud or rain water. Here, both radar systems are applied to a case of light to moderate snowfall within the warm frontal zone of a cold season, synoptic scale storm. Radars allow for an evaluation of the accuracy of a single-moment scheme in replicating precipitation structures, based on the bulk statistical properties of precipitation as suggested by reflectivity signatures.

Molthan, Andrew↗

NASA NTRS2018

AMSR2 Soil Moisture Downscaling Using Temperature and Vegetation Data

Soil moisture (SM) applications in terrestrial hydrology require higher spatial resolution soil moisture products than those provided by passive microwave remote sensing instruments (grid resolution of 9 km or larger). In this investigation, an innovative algorithm that uses visible/infrared remote sensing observations to downscale Advanced Microwave Scanning Radiometer 2 (AMSR2) coarse spatial resolution SM products was developed and implemented for use with data provided by the Advanced Microwave Scanning Radiometer 2 (AMSR2). The method is based on using the Normalized Difference Vegetation Index (NDVI) modulated relationships between day/night SM and temperature change at corresponding times. Land surface model output variables from the North America Land Data Assimilation System (NLDAS), remote sensing data from the Moderate-Resolution Imaging Spectroradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) were used in this methodology. The functional relationships developed using NLDAS data at a grid resolution of 12.5 km were applied to downscale AMSR2 JAXA (Japan Aerospace Exploration Agency) SM product (25 km) using MODIS land surface temperature (LST) and NDVI observations (1 km) to produce the 1 km SM estimates. The downscaled SM estimates were validated by comparing them with ISMN (International Soil Moisture Network) in situ SM in the Black Bear-Red Rock watershed, central Oklahoma between 2015-2017. The overall statistical variables of the downscaled AMSR2 SM validation R2, slope, RMSE and bias, demonstrate good accuracy. The downscaled SM better characterized the spatial and temporal variability of SM at watershed scales than the original SM product.

AMSR2; passive microwave soil moisture; soil moist↗

NASA NTRS2019

Surface Height and Sea Ice Freeboard of the Arctic Ocean from ICESat-2: Characteristics and Early Results

We present the first winter season of surface height and sea ice freeboards of the Arctic Ocean from the new ICESat-2 (IS-2) mission. The Advanced Topographic Laser Altimeter System (ATLAS) onboard has six photon-counting beams for surface profiling with a 10-kHz pulse-rate (inter-pulse distance ~0.7m) and footprints of ~17m. Geolocated heights assigned to individual photons scattered from the surface allow significant flexibility in the construction of height distributions used in surface finding. For IS-2 sea ice products, a fixed 150-photon aggregate is used to control height precision and obtain better along-track resolution over high reflectance surfaces. Quasi-specular returns in openings as narrow as ~27m, crucial for freeboard calculations, are resolved. The fixed photon aggregate results in unique variable along-track resolutions and non-uniform sampling (17m x 27m to 17m x 200m for the strong beams) of the surface. The six profiling beams – three pairs separated by 3.3 km with a strong and weak beam in each pair – provide correlated statistics at regional length scales for assessment of beam-to-beam retrieval consistency and accuracy. Analysis shows along-track height precisions of ~2cm, and agreement in the monthly freeboard distributions across the strong beams to 1-2cm. In this paper, we describe briefly the approaches used in surface height and freeboard retrievals from ATLAS photon clouds, and detail the key features of these along-track sea ice products, focusing on the first release of data collected over the Arctic Ocean, which spans the period between October 14, 2018 – the start of data collection – and the end of March 2019.

R Kwok↗

NASA NTRS2012

Parametric Study of Decay of Homogeneous Isotropic Turbulence Using Large Eddy Simulation

Numerical simulations of decaying homogeneous isotropic turbulence are performed with both low-order and high-order spatial discretization schemes. The turbulent Mach and Reynolds numbers for the simulations are 0.2 and 250, respectively. For the low-order schemes we use either second-order central or third-order upwind biased differencing. For higher order approximations we apply weighted essentially non-oscillatory (WENO) schemes, both with linear and nonlinear weights. There are two objectives in this preliminary effort to investigate possible schemes for large eddy simulation (LES). One is to explore the capability of a widely used low-order computational fluid dynamics (CFD) code to perform LES computations. The other is to determine the effect of higher order accuracy (fifth, seventh, and ninth order) achieved with high-order upwind biased WENO-based schemes. Turbulence statistics, such as kinetic energy, dissipation, and skewness, along with the energy spectra from simulations of the decaying turbulence problem are used to assess and compare the various numerical schemes. In addition, results from the best performing schemes are compared with those from a spectral scheme. The effects of grid density, ranging from 32 cubed to 192 cubed, on the computations are also examined. The fifth-order WENO-based scheme is found to be too dissipative, especially on the coarser grids. However, with the seventh-order and ninth-order WENO-based schemes we observe a significant improvement in accuracy relative to the lower order LES schemes, as revealed by the computed peak in the energy dissipation and by the energy spectrum.

Swanson, R. C.↗

NASA NTRS2024

Interpretable Machine Learning for Molecular Biosignatures: a Novel Single-Sample Feature Importance Method That Is Sensitive To Statistical Interactions

Isotope ratio mass spectrometry (IRMS) of volatiles (e.g., CO 2 ) promises to be a powerful tool for potential biosignature detection for future missions to ocean worlds (OW) such as Europa and Enceladus. Machine learning (ML) methods for IRMS data could enable science autonomy by onboard prediction of seawater chemistry and biosignature presence. However, ML models are likely to be complex and involve statistical interactions between features (variables), which can make predictions seem opaque and enigmatic. For ML predictions as significant as extraterrestrial biosignatures, we must place extraordinary confidence in models. It is therefore essential that these models make interpretable predictions (i.e., human-understandable) and include false-prediction diagnostics. We achieve high accuracy and interpretability in ML biosignature and seawater chemistry models for OW through a nearest-neighbors feature selection tool that detects statistical interactions between predictors, constructs interaction networks for visualization of selected features working together to make a prediction, and reports single-sample feature importance scores for false-detection diagnostics. Here we develop a novel single-sample nearest-neighbors projected distance regression(ssNPDR) feature selection method that improves upon existing single-sample algorithms through the inclusion of statistical interactions while providing false-prediction diagnostics for ML models.

geochemistry↗

NASA NTRS2019

Atmospheric Correction of Satellite Ocean-Color Imagery During the PACE Era

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will carry into space the Ocean Color Instrument (OCI), a spectrometer measuring at 5 nm spectral resolution in the ultraviolet (UV) to near infrared (NIR) with additional spectral bands in the shortwave infrared (SWIR), and two multi-angle polarimeters that will overlap the OCI spectral range and spatial coverage, i. e., the Spectrometer for Planetary Exploration (SPEXone) and the Hyper-Angular Rainbow Polarimeter (HARP2). These instruments, especially when used in synergy, have great potential for improving estimates of water reflectance in the post Earth Observing System (EOS) era. Extending the top-of-atmosphere (TOA) observations to the UV, where aerosol absorption is effective, adding spectral bands in the SWIR, where even the most turbid waters are black and sensitivity to the aerosol coarse mode is higher than at shorter wavelengths, and measuring in the oxygen A-band to estimate aerosol altitude will enable greater accuracy in atmospheric correction for ocean color science. The multi-angular and polarized measurements, sensitive to aerosol properties (e.g., size distribution, index of refraction), can further help to identify or constrain the aerosol model, or to retrieve directly water reflectance. Algorithms that exploit the new capabilities are presented, and their ability to improve accuracy is discussed. They embrace a modern, adapted heritage two-step algorithm and alternative schemes (deterministic, statistical) that aim at inverting the TOA signal in a single step. These schemes, by the nature of their construction, their robustness, their generalization properties, and their ability to associate uncertainties, are expected to become the new standard in the future. A strategy for atmospheric correction is presented that ensures continuity and consistency with past and present ocean-color missions while enabling full exploitation of the new dimensions and possibilities. Despite the major improvements anticipated with the PACE instruments, gaps/issues remain to be filled/tackled. They include dealing properly with whitecaps, taking into account Earth-curvature effects, correcting for adjacency effects, accounting for the coupling between scattering and absorption, modeling accurately water reflectance, and acquiring a sufficiently representative dataset of water reflectance in the UV to SWIR. Dedicated efforts, experimental and theoretical, are in order to gather the necessary information and rectify inadequacies. Ideas and solutions are put forward to address the unresolved issues. Thanks to its design and characteristics, the PACE mission will mark the beginning of a new era of unprecedented accuracy in ocean-color radiometry from space.

Robert J Frouin↗