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NASA NTRS2013

MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region

MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.

MODIS↗
NASA NTRS2017

Assessing Uncertainties in Gridded Emissions: A Case Study for Fossil Fuel Carbon Dioxide (FFCO2) Emission Data

Fossil fuel carbon dioxide (CO2) emissions (FFCO2) are the largest input to the global carbon cycle on a decadal time scale. Because total emissions are assumed to be reasonably well constrained by fuel statistics, FFCO2 often serves as a reference in order to deduce carbon uptake by poorly understood terrestrial and ocean sinks. Conventional atmospheric CO2 flux inversions solve for spatially explicit regional sources and sinks and estimate land and ocean fluxes by subtracting FFCO2. Thus, errors in FFCO2 can propagate into the final inferred flux estimates. Gridded emissions are often based on disaggregation of emissions estimated at national or regional level. Although national and regional total FFCO2 are well known, gridded emission fields are subject to additional uncertainties due to the emission disaggregation. Assessing such uncertainties is often challenging because of the lack of physical measurements for evaluation. We first review difficulties in assessing uncertainties associated with gridded FFCO2 emission data and present several approaches for evaluation of such uncertainties at multiple scales. Given known limitations, inter-emission data differences are often used as a proxy for the uncertainty. The popular approach allows us to characterize differences in emissions, but does not allow us to fully quantify emission disaggregation biases. Our work aims to vicariously evaluate FFCO2 emission data using atmospheric models and measurements. We show a global simulation experiment where uncertainty estimates are propagated as an atmospheric tracer (uncertainty tracer) alongside CO2 in NASA's GEOS model and discuss implications of FFCO2 uncertainties in the context of flux inversions. We also demonstrate the use of high resolution urban CO2 simulations as a tool for objectively evaluating FFCO2 data over intense emission regions. Though this study focuses on FFCO2 emission data, the outcome of this study could also help improve the knowledge of similar gridded emissions data for non-CO2 compounds with similar emission characteristics.

FFCO↗
NASA NTRS2016

Spatial and Temporal Antarctic Ice Sheet Mass Trends, Glacio-Isostatic Adjustment, and Surface Processes from a Joint Inversion of Satellite Altimeter, Gravity, and GPS Data

We present spatiotemporal mass balance trends for the Antarctic Ice Sheet from a statistical inversion of satellite altimetry, gravimetry, and elastic-corrected GPS data for the period 2003-2013. Our method simultaneously determines annual trends in ice dynamics, surface mass balance anomalies, and a time-invariant solution for glacio-isostatic adjustment while remaining largely independent of forward models. We establish that over the period 2003-2013, Antarctica has been losing mass at a rateof -84 +/- 22 Gt per yr, with a sustained negative mean trend of dynamic imbalance of -111 +/- 13 Gt per yr. West Antarctica is the largest contributor with -112 +/- 10 Gt per yr, mainly triggered by high thinning rates of glaciers draining into the Amundsen Sea Embayment. The Antarctic Peninsula has experienced a dramatic increase in mass loss in the last decade, with a mean rate of -28 +/- 7 Gt per yr and significantly higher values for the most recent years following the destabilization of the Southern Antarctic Peninsula around 2010. The total mass loss is partly compensated by a significant mass gain of 56 +/- 18 Gt per yr in East Antarctica due to a positive trend of surface mass balance anomalies.

Martin-Espanol, Alba↗
NASA NTRS1979

The effects of context on multidimensional spatial cognitive models

Spatial cognitive models obtained by multidimensional scaling represent cognitive structure by defining alternatives as points in a coordinate space based on relevant dimensions such that interstimulus dissimilarities perceived by the individual correspond to distances between the respective alternatives. The dependence of spatial models on the context of the judgments required of the individual was investigated. Context, which is defined as a perceptual interpretation and cognitive understanding of a judgment situation, was analyzed and classified with respect to five characteristics: physical environment, social environment, task definition, individual perspective, and temporal setting. Four experiments designed to produce changes in the characteristics of context and to test the effects of these changes upon individual cognitive spaces are described with focus on experiment design, objectives, statistical analysis, results, and conclusions. The hypothesis is advanced that an individual can be characterized as having a master cognitive space for a set of alternatives. When the context changes, the individual appears to change the dimension weights to give a new spatial configuration. Factor analysis was used in the interpretation and labeling of cognitive space dimensions.

Dupnick, E. G.↗
NASA NTRS1983

A function space approach to state and model error estimation for elliptic systems

An approach is advanced for the concurrent estimation of the state and of the model errors of a system described by elliptic equations. The estimates are obtained by a deterministic least-squares approach that seeks to minimize a quadratic functional of the model errors, or equivalently, to find the vector of smallest norm subject to linear constraints in a suitably defined function space. The minimum norm solution can be obtained by solving either a Fredholm integral equation of the second kind for the case with continuously distributed data or a related matrix equation for the problem with discretely located measurements. Solution of either one of these equations is obtained in a batch-processing mode in which all of the data is processed simultaneously or, in certain restricted geometries, in a spatially scanning mode in which the data is processed recursively. After the methods for computation of the optimal estimates are developed, an analysis of the second-order statistics of the estimates and of the corresponding estimation error is conducted. Based on this analysis, explicit expressions for the mean-square estimation error associated with both the state and model error estimates are then developed.

Rodriguez, G.↗
NASA NTRS1985

Spatial variation of cosmic rays near the heliospheric current sheet

A quantitative comparison between theoretical predictions and observations of the intensity of galactic cosmic rays near the interplanetary current sheet is reported. Comparison of model calculations is made with a statistical analysis of observations of galactic cosmic rays at Earth and the simultaneous position of the current sheet. An ensemble of different current sheet inclinations is used, in order to make the analysis of the computations approximate the method used to analyses the data.

Jokipii, J. R.↗
NASA NTRS1983

A function space approach to state and model error estimation for elliptic systems

An approach is advanced for the concurrent estimation of the state and of the model errors of a system described by elliptic equations. The estimates are obtained by a deterministic least-squares approach that seeks to minimize a quadratic functional of the model errors, or equivalently, to find the vector of smallest norm subject to linear constraints in a suitably defined function space. The minimum norm solution can be obtained by solving either a Fredholm integral equation of the second kind for the case with continuously distributed data or a related matrix equation for the problem with discretely located measurements. Solution of either one of these equations is obtained in a batch-processing mode in which all of the data is processed simultaneously or, in certain restricted geometries, in a spatially scanning mode in which the data is processed recursively. After the methods for computation of the optimal esimates are developed, an analysis of the second-order statistics of the estimates and of the corresponding estimation error is conducted. Based on this analysis, explicit expressions for the mean-square estimation error associated with both the state and model error estimates are then developed. While this paper focuses on theoretical developments, applications arising in the area of large structure static shape determination are contained in a closely related paper (Rodriguez and Scheid, 1982).

Rodriguez, G.↗
NASA NTRS1989

Simulation studies of improved sounding systems

Two instrument designs for indirect satellite sounding of the atmosphere in the infrared are represented by the High Resolution Infra-Red Sounder, Model 2 (HIRS-2) and by the Advanced Meteorological Temperature Sounder (AMTS). The relative capabilities of the two instruments were tested by simulating satellite measurements from a group of temperature soundings, allowing the two participants to retrieve the temperature profiles from the simulated data, and comparing the results with the original temperature profiles. Four data sets were produced from radiosondes data extrapolated to a suitable altitude, representing continents and oceans, between 30S and 30N. From the information available, temperature profiles were retrieved by two different methods, statistical regression and inversion of the radiative transfer equation. Results show the consequence of greater spectral purity, concomitant increase in the number of spectral intervals, and the better spatial resolution in partly clouded areas. At the same time, the limitation of the HIRS-2 without its companion instrument leads to some results which should be ignored in comparing the two instruments. A clear superiority of AMTS results is shown.

Yates, H.↗
NASA NTRS1991

Property and microstructural nonuniformity in the yttrium-barium-copper-oxide superconductor determined from electrical, magnetic, and ultrasonic measurements

The purpose of this dissertation was the following: (1) to characterize the effect of pore fraction on a comprehensive set of electrical and magnetic properties for the yttrium-barium-copper-oxide (YBCO) high temperature ceramic superconductor; and (2) to determine the viability of using a room-temperature, nondestructive characterization method to aid in the prediction of superconducting (cryogenic) properties. The latter involved correlating ultrasonic velocity measurements at room temperature with property-affecting pore fraction and oxygen content variations. The use of ultrasonic velocity for estimating pore fraction in YBCO is presented, and other polycrystalline materials are reviewed, modeled, and statistically analyzed. This provides the basis for using ultrasonic velocity to interrogate microstructure. The effect of pore fraction (0.10-0.25) on superconductor properties of YBCO samples was characterized. Spatial (within-sample) variations in microstructure and superconductor properties were investigated, and the effect of oxygen content on elastic behavior was examined. Experimental methods used included a.c. susceptibility, electrical, and ultrasonic velocity measurements. Superconductor properties measured included transition temperature, magnetic transition width, transport and magnetic critical current density, magnetic shielding, a.c. loss, and sharpness of the voltage-current characteristics. An ultrasonic velocity image constructed from measurements at 1mm increments across a YBCO sample revealed microstructural variations that correlated with variations in magnetic shielding and a.c. loss behavior. Destructive examination using quantitative image analysis revealed pore fraction to be the varying microstructural feature.

Roth, Don J.↗
NASA NTRS2000

BOREAS RSS-10 TOMS Circumpolar One-Degree PAR Images

The Boreal Ecosystem-Atmosphere Study (BOREAS) Remote Sensing Science (RSS)-10 team investigated the magnitude of daily, seasonal, and yearly variations of Photosynthetically Active Radiation (PAR) from ground and satellite observations. This data set contains satellite estimates of surface-incident PAR (400-700 nm, MJ/sq m) at one-degree spatial resolution. The spatial coverage is circumpolar from latitudes of 41 to 66 degrees north. The temporal coverage is from May through September for years 1979 through 1989. Eleven-year statistics are also provided: (1) mean, (2) standard deviation, and (3) coefficient of variation for 1979-89. The PAR estimates were derived from the global gridded ultraviolet reflectivity data product (average of 360, 380 nm) from the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS). Image mask data are provided for identifying the boreal forest zone, and ocean/land and snow/ice-covered areas. The data are available as binary image format data files. The PAR data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Dye, Dennis G.↗
NASA NTRS2014

Stereoscopic Retrieval of Smoke Plume Heights and Motion from Space-Based Multi-Angle Imaging, Using the MISR INteractive eXplorer(MINX)

Airborne particles desert dust, wildfire smoke, volcanic effluent, urban pollution affect Earth's climate as well as air quality and health. They are found in the atmosphere all over the planet, but vary immensely in amount and properties with season and location. Most aerosol particles are injected into the near-surface boundary layer, but some, especially wildfire smoke, desert dust and volcanic ash, can be injected higher into the atmosphere, where they can stay aloft longer, travel farther, produce larger climate effects, and possibly affect human and ecosystem health far downwind. So monitoring aerosol injection height globally can make important contributions to climate science and air quality studies. The Multi-angle Imaging Spectro-Radiometer (MISR) is a space borne instrument designed to study Earths clouds, aerosols, and surface. Since late February 2000 it has been retrieving aerosol particle amount and properties, as well as cloud height and wind data, globally, about once per week. The MINX visualization and analysis tool complements the operational MISR data products, enabling users to retrieve heights and winds locally for detailed studies of smoke plumes, at higher spatial resolution and with greater precision than the operational product and other space-based, passive remote sensing techniques. MINX software is being used to provide plume height statistics for climatological studies as well as to investigate the dynamics of individual plumes, and to provide parameterizations for climate modeling.

aerosols↗
NASA NTRS2008

Interpolating Fields of Carbon Monoxide Data Using a Hybrid Statistical-Physical Model

Atmospheric Carbon Monoxide (CO) is a pollutant gas of which the US congress has mandated regular monitoring, and satellite sensors can be used to retrieve regional concentrations of CO over several vertical layers. However, CO at cloudy locations cannot be observed and have to be estimated from the observed data set, resulting in an interpolation problem. The current state-of-the-art solution is to combine prior information, computed by a deterministic physical model, with observations. However, the deterministic model may introduce uncertainties that do not derive from the data. While sharing certain features with the physical model, this paper presents a Bayesian hierarchical model for interpolating CO on a 3-dimensional spatial grid, across time. To our knowledge such a model has not been considered before. The model is applied to a hypothetical air-quality monitoring scenario, and is compared to existing interpolation methods. The results provide motivation for the use of the statistical model for regional to local applications.

Arellano, A. A.↗
NASA NTRS2018

Integrating Cloud-Based Workflows in Continental-Scale Cropland Extent Classification

Accurate information on cropland spatial distribution is required for global-scale assessments and agricultural land use policies. Cloud computing platforms such as Google Earth Engine (GEE) provide unprecedented opportunities for large-scale classifications of Landsat data. We developed a novel method to fuse pixel-based random forest classification of continental-scale Landsat data on GEE and an object-based segmentation approach known as recursive hierarchical segmentation (RHSeg). Using our fusion method, we produced a continental-scale cropland extent map for North America at 30m spatial resolution for the nominal year 2010. The total cropland area for North America was estimated at 275.18 million hectares (Mha). The overall accuracies of the map are>90% across the continent. This map also compares well with the United States Department of Agriculture (USDA) cropland data layer (CDL), Agriculture and Agri-food Canada (AAFC) annual crop inventory (ACI), and the Mexican government agency Servicio de Informacion Agroalimentaria y Pesquera (SIAP)'s agricultural boundaries. Furthermore, our map compared well with sub-country statistics including state-wise and county-wise cropland statistics in regression models resulting in R2 > 0.84. This key contribution paves the way for more detailed products such as crop intensity, crop type, and crop irrigation, and provides a method for creating high-resolution cropland extent maps for other countries where spatial information about croplands are not as prevalent.

Massey, Richard↗
NASA NTRS2000

Visual detection of spatial contrast patterns: evaluation of five simple models

The ModelFest Phase One dataset is a collection of luminance contrast thresholds for 43 two-dimensional monochromatic spatial patterns confined to an area of approximately two by two degrees. These data were collected by a collaboration among twelve laboratories, and were designed to provide a common database for calibration and testing of spatial vision models. Here I report fits of the ModelFest data with five models: Peak Contrast, Contrast Energy, Generalized Energy, a Gabor Channels model, and a Discrete Cosine Transform model. The Gabor Channels model provides the best fit, though the other, simpler models, with the exception of Peak Contrast, provide remarkably good fits as well. Though there are clear individual differences, regularities in the data suggest the possibility of constructing a standard observer for spatial vision. c2000 Optical Society of America.

NASA Discipline Space Human Factors↗
NASA NTRS1990

Statistical analysis of near-wall structures in turbulent channel flow

The two-point correlation tensor is used to analyze near-wall structures in turbulent channel flow. Simulation results have been utilized to obtain the correlation tensor with sufficient spatial resolution to permit accurate differentiation for computing the vorticity correlation, and the resolution of sharp features such as the shear layer and its corresponding region of spanwise vorticity. Proper orthogonal decomposition and stochastic estimation were observed to yield similar results when appropriate conditions were employed for the estimation. Resulting structures were such that they would be detected by standard conditional sampling methods. The results of decomposing the vorticity field and the velocity field were significantly different, indicating that if a coherent structure is found that dominates the velocity fields, the curl of that velocity structure will not dominate the vorticity field.

Moser, Robert D.↗
NASA NTRS1991

A statistical analysis of gamma-ray bursts detected by the Konus Experiment on Venera 11 and 12

We discuss the advantages of using the V/V sub max method to test well-defined samples of gamma-ray bursts for the spatial uniformity of their parent population. We have applied the V/V sub max test to gamma ray bursts of duration longer than 1 second recorded by the Konus experiment aboard Venera 11 and 12. Based on a sample of 123 bursts, we find V/V sub max equals 0.46 plus or minus 0.03, consistent with a uniform distribution in space. We urge that experimenters give careful attention to the detection limit for each recorded gamma ray burst, and that quantitative data for burst properties and detection limits be published.

Schmidt, Maarten↗
NASA NTRS1977

The application of satellite data in monitoring strip mines

Strip mines in the New River Drainage Basin of Tennessee were studied through use of Landsat-1 imagery and aircraft photography. A multilevel analysis, involving conventional photo interpretation techniques, densitometric methods, multispectral analysis and statistical testing was applied to the data. The Landsat imagery proved adequate for monitoring large-scale change resulting from active mining and land-reclamation projects. However, the spatial resolution of the satellite imagery rendered it inadequate for assessment of many smaller strip mines, in the region which may be as small as a few hectares.

Sharber, L. A.↗
NASA NTRS1979

Radiometric correction and equalization of satellite digital data

Satellite digital data from Landsat and NOAA satellites is often marred by striping or streaking errors due to variations in the response of the radiometric sensors. In this paper, we discuss the equalization of the digital data as a preprocessing step, prior to image enhancement or automatic classification. The methods described make use of statistics of the data itself to generate nonlinear or linear memory-less equalization algorithms. These algorithms, by contrast to multidimensional filtering, do not result in a loss of spatial resolution. Examples of applications to Landsat and NOAA-3 thermal infrared data are given and illustrated.

Algazi, V. R.↗