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At least 703 records · Page 39

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NASA NTRS2001

SIMBIOS Project Data Processing and Analysis Results

The Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project is concerned with ocean color satellite sensor data intercomparison and merger for biological and interdisciplinary studies of the global oceans. Imagery from different ocean color sensors can now be processed by a single software package using the same algorithms, adjusted by different sensor spectral characteristics, and the same ancillary meteorological and environmental data. This enables cross-comparison and validation of the data derived from satellite sensors and, consequently, creates continuity in ocean color information on both the temporal and spatial scale. The next step in this process is the integration of in situ ocean and atmospheric parameters to enable cross-validation and further refinement of the ocean color methodology. The SIMBIOS Project Office accomplishments during 2000 year are summarized under satellite data processing, data product validation, SeaWiFS Bio-Optical Archive and Storage System (SeaBASS) database, supporting services, sun photometers and calibration activities, and calibration round robins. These accomplishments are described.

Ainsworth, Ewa↗

NASA NTRS1992

Atmospheric effects on crater growth on Venus

Laboratory experiments allow examining the consequences of complex processes operating over a wide range of scales (both temporal and spatial) and frequently reveal effects that are obvious only in hindsight. Even though all processes may not scale directly, isolation of the controlling variables allows assessing first-order effects through analytical approximations. This approach can be illustrated by the systematic sequence of ballistic ejection, the response of an atmosphere to a strong energy source, the scaling of ejecta thickness, and the role of secondary cratering. Here it is proposed that the effects of atmospheric pressure and density on crater growth (hence, scaling) observed in laboratory experiments has particular relevance for craters on Venus.

Schultz, Peter H.↗

NASA NTRS2010

Material condition assessment with eddy current sensors

Eddy current sensors and sensor arrays are used for process quality and material condition assessment of conducting materials. In an embodiment, changes in spatially registered high resolution images taken before and after cold work processing reflect the quality of the process, such as intensity and coverage. These images also permit the suppression or removal of local outlier variations. Anisotropy in a material property, such as magnetic permeability or electrical conductivity, can be intentionally introduced and used to assess material condition resulting from an operation, such as a cold work or heat treatment. The anisotropy is determined by sensors that provide directional property measurements. The sensor directionality arises from constructs that use a linear conducting drive segment to impose the magnetic field in a test material. Maintaining the orientation of this drive segment, and associated sense elements, relative to a material edge provides enhanced sensitivity for crack detection at edges.

Goldfine, Neil J.↗

NASA NTRSDate not supplied

New insights into PSCs from the nearly 17-year CALIPSO data record

Polar stratospheric clouds (PSCs) play important roles in stratospheric ozone depletion during winter and spring at high latitudes (e.g., the Antarctic ozone hole). PSC particles provide sites for heterogeneous reactions that convert stable chlorine reservoir species to radicals that destroy ozone catalytically. PSCs also prolong ozone depletion by delaying chlorine deactivation through the removal of gas-phase HNO3 and H2O by sedimentation of large nitric acid trihydrate (NAT) and ice particles. A more complete picture of PSC processes on vortex-wide scales has emerged from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) instrument on the CALIPSO satellite that has been observing PSCs at latitudes up to 82 degrees in both hemispheres since June 2006. This nearly 17-year data record has fundamentally improved our knowledge of PSC spatial and temporal distributions, composition, and formation processes. In this presentation, we provide a brief overview of the CALIOP PSC data record and highlight some of the recent advances in our understanding of PSC processes.

polar stratospheric clouds↗

NASA NTRS1989

Image processing using Gallium Arsenide (GaAs) technology

The need to increase the information return from space-borne imaging systems has increased in the past decade. The use of multi-spectral data has resulted in the need for finer spatial resolution and greater spectral coverage. Onboard signal processing will be necessary in order to utilize the available Tracking and Data Relay Satellite System (TDRSS) communication channel at high efficiency. A generally recognized approach to the increased efficiency of channel usage is through data compression techniques. The compression technique implemented is a differential pulse code modulation (DPCM) scheme with a non-uniform quantizer. The need to advance the state-of-the-art of onboard processing was recognized and a GaAs integrated circuit technology was chosen. An Adaptive Programmable Processor (APP) chip set was developed which is based on an 8-bit slice general processor. The reason for choosing the compression technique for the Multi-spectral Linear Array (MLA) instrument is described. Also a description is given of the GaAs integrated circuit chip set which will demonstrate that data compression can be performed onboard in real time at data rate in the order of 500 Mb/s.

Miller, Warner H.↗

NASA NTRS1979

Feasibility of automated dropsize distributions from holographic data using digital image processing techniques

An automated technique for measuring particle diameters and their spatial coordinates from holographic reconstructions is being developed. Preliminary tests on actual cold-flow holograms of impinging jets indicate that a suitable discriminant algorithm consists of a Fourier-Gaussian noise filter and a contour thresholding technique. This process identifies circular as well as noncircular objects. The desired objects (in this case, circular or possibly ellipsoidal) are then selected automatically from the above set and stored with their parametric representations. From this data, dropsize distributions as a function of spatial coordinates can be generated and combustion effects due to hardware and/or physical variables studied.

Feinstein, S. P.↗

NASA NTRS2010

Spatial Patterns of Snow Cover in North Carolina: Surface and Satellite Perspectives

Snow mapping is a common practice in regions that receive large amounts of snowfall annually, have seasonally-continuous snow cover, and where snowmelt contributes significantly to the hydrologic cycle. Although higher elevations in the southern Appalachian Mountains average upwards of 100 inches of snow annually, much of the remainder of the Southeast U.S. receives comparatively little snowfall (< 10 inches). Recent snowy winters in the region have provided an opportunity to assess the fine-grained spatial distribution of snow cover and the physical processes that act to limit or improve its detection across the Southeast. In the present work, both in situ and remote sensing data are utilized to assess the spatial distribution of snow cover for a sample of recent snowfall events in North Carolina. Specifically, this work seeks to determine how well ground measurements characterize the fine-grained patterns of snow cover in relation to Moderate- Resolution Imaging Spectroradiometer (MODIS) snow cover products (in this case, the MODIS Fractional Snow Cover product).

Fuhrmann, Christopher M.↗

DOE OSTI2024

Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO 2 v7.3

We describe the development of the tangent linear (TL) and adjoint models of the Model for Prediction Across Scales (MPAS)-CO 2 transport model, which is a global online chemical transport model developed upon the non-hydrostatic Model for Prediction Across Scales – Atmosphere (MPAS-A). The primary goal is to make the model system a valuable research tool for investigating atmospheric carbon transport and inverse modeling. First, we develop the TL code, encompassing all CO 2 transport processes within the MPAS-CO 2 forward model. Then, we construct the adjoint model using a combined strategy involving re-calculation and storage of the essential meteorological variables needed for CO 2 transport. This strategy allows the adjoint model to undertake a long-period integration with moderate memory demands. To ensure accuracy, the TL and adjoint models undergo vigorous verifications through a series of standard tests. The adjoint model, through backward-in-time integration, calculates the sensitivity of atmospheric CO 2 observations to surface CO 2 fluxes and the initial atmospheric CO 2 mixing ratio. To demonstrate the utility of the newly developed adjoint model, we conduct simulations for two types of atmospheric CO 2 observations, namely the tower-based in situ CO 2 mixing ratio and satellite-derived column-averaged CO 2 mixing ratio (X CO 2 ). A comparison between the sensitivity to surface flux calculated by the MPAS-CO 2 adjoint model with its counterpart from CarbonTracker–Lagrange (CT-L) reveals a spatial agreement but notable magnitude differences. These differences, particularly evident for X CO 2 , might be attributed to the two model systems' differences in the simulation configuration, spatial resolution, and treatment of vertical mixing processes. Moreover, this comparison highlights the substantial loss of information in the atmospheric CO 2 observations due to CT-L's spatial domain limitation. Furthermore, the adjoint sensitivity analysis demonstrates that the sensitivities to both surface flux and initial CO 2 conditions spread out throughout the entire Northern Hemisphere within a month. MPAS-CO 2 forward, TL, and adjoint models stand out for their calculation efficiency and variable-resolution capability, making them competitive in computational cost. In conclusion, the successful development of the MPAS-CO 2 TL and adjoint models, and their integration into the MPAS-CO 2 system, establish the possibility of using MPAS's unique features in atmospheric CO 2 transport sensitivity studies and in inverse modeling with advanced methods such as variational data assimilation.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2010

Experimental Investigation of Space Radiation Processing in Lunar Soil Ilmenite: Combining Perspectives from Surface Science and Transmission Electron Microscopy

Energetic ions mostly from the solar wind play a major role in lunar space weathering because they contribute structural and chemical changes to the space-exposed surfaces of lunar regolith grains. In mature mare soils, ilmenite (FeTiO3) grains in the finest size fraction have been shown in transmission electron microscope (TEM) studies to exhibit key differences in their response to space radiation processing relative to silicates [1,2,3]. In ilmenite, solar ion radiation alters host grain outer margins to produce 10-100 nm thick layers that are microstructurally complex, but dominantly crystalline compared to the amorphous radiation-processed rims on silicates [1,2,3]. Spatially well-resolved analytical TEM measurements also show nm-scale compositional and chemical state changes in these layers [1,3]. These include shifts in Fe/Ti ratio from strong surface Fe-enrichment (Fe/Ti >> 1), to Fe depletion (Fe/Ti < 1) at 40-50 nm below the grain surface [1,3]. These compositional changes are not observed in the radiation-processed rims on silicates [4]. Several mechanism(s) to explain the overall relations in the ilmenite grain rims by radiation processing and/or additional space weathering processes were proposed by [1], and remain under current consideration [3]. A key issue has concerned the ability of ion radiation processing alone to produce some of the deeper- penetrating compositional changes. In order to provide some experimental constraints on these questions, we have performed a combined X-ray photoelectron spectroscopy (XPS) and field-emission scanning transmission electron (FE-STEM) study of experimentally ion-irradiated ilmenite. A key feature of this work is the combination of analytical techniques sensitive to changes in the irradiated samples at depth scales going from the immediate surface (approx.5 nm; XPS), to deeper in the grain interior (5-100 nm; FE-STEM).

Christoffersen, R.↗

NASA NTRS2018

Verification of an Icosahedral Grid for Strategic Center for Networking, Communications, and Integration User Interface Spatial Capabilities

Spatial communication analysis tools are incredibly useful resources to have when planning a space mission. Every single mission that leaves Earth needs a way to get its data back down and every mission's requirements on how that will get accomplished is different. Being able to analyze how existing assets can provide services independent of a specific mission can be key in that process. Most current commercial software packages contain spatial analysis capabilities but go about the analysis in a way that is not the most efficient and can skew the results provided. NASA's Space Communication and Navigation (SCaN) Center for Engineering Networks, Integration, and Communications (SCENIC) seeks to solve this problem and provide analysis capabilities using both internally developed and open-source software. This allows incredible flexibility, customization and hugely reduces licensing costs. Using MATLAB® and Orbit Determination Toolbox created by Goddard Space Flight Center (GSFC), SCENIC is able to perform many node-based functions currently. Analysis utilizing the spatial tools in SCENIC allows a meaningful analysis of the capability of communication network assets in a way not seen in current commercial software packages. This paper discusses the verification activities associated with generating the spatial grid point definition utilized in these analysis capabilities, within the SCENIC user interface (UI).

Jasper, Lindsey A.↗

NASA NTRS1989

An intelligent user interface for browsing satellite data catalogs

A large scale domain-independent spatial data management expert system that serves as a front-end to databases containing spatial data is described. This system is unique for two reasons. First, it uses spatial search techniques to generate a list of all the primary keys that fall within a user's spatial constraints prior to invoking the database management system, thus substantially decreasing the amount of time required to answer a user's query. Second, a domain-independent query expert system uses a domain-specific rule base to preprocess the user's English query, effectively mapping a broad class of queries into a smaller subset that can be handled by a commercial natural language processing system. The methods used by the spatial search module and the query expert system are explained, and the system architecture for the spatial data management expert system is described. The system is applied to data from the International Ultraviolet Explorer (IUE) satellite, and results are given.

Cromp, Robert F.↗

NASA NTRS1989

An intelligent user interface for browsing satellite data catalogs

Cromp, Robert F.↗

NASA NTRS2004

Automatic Assessment and Reduction of Noise using Edge Pattern Analysis in Non-Linear Image Enhancement

Noise is the primary visibility limit in the process of non-linear image enhancement, and is no longer a statistically stable additive noise in the post-enhancement image. Therefore novel approaches are needed to both assess and reduce spatially variable noise at this stage in overall image processing. Here we will examine the use of edge pattern analysis both for automatic assessment of spatially variable noise and as a foundation for new noise reduction methods.

Jobson, Daniel J.↗

NASA NTRS2004

The Automatic Assessment and Reduction of Noise Using Edge Pattern Analysis in Nonlinear Image Enhancement

Jobson, Daniel J.↗

NASA NTRS1984

Evidence accumulation for spatial reasoning

The evidence accumulation proces of an image understanding system is described enabling the system to perform top-down(goal-oriented) picture processing as well as bottom-up verification of consistent spatial relations among objects.

Matsuyama, T.↗

DOE OSTI2022

Using aircraft measurements to characterize subgrid-scale variability of aerosol properties near the Atmospheric Radiation Measurement Southern Great Plains site

Abstract. Complex distributions of aerosol properties evolve in space and time as a function of emissions, new particle formation, coagulation, condensational growth, chemical transformation, phase changes, turbulent mixing and transport, removal processes, and ambient meteorological conditions. The ability of chemical transport models to represent the multi-scale processes affecting the life cycle of aerosols depends on their spatial resolution since aerosol properties are assumed to be constant within a grid cell. Subgrid-scale-dependent processes that affect aerosol populations could have a significant impact on the formation of particles, their growth to cloud condensation nuclei (CCN) sizes, aerosol–cloud interactions, dry deposition and rainout and hence their burdens, lifetimes, and radiative forcing. To address this issue, we characterize subgrid-scale variability in terms of measured aerosol number, size, composition, hygroscopicity, and CCN concentrations made by repeated aircraft flight paths over the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystem (HI-SCALE) campaign. Subgrid variability is quantified in terms of both normalized frequency distributions and percentage difference percentiles using grid spacings of 3, 9, 27, and 81 km that represent those typically used by cloud-system-resolving models as well as the current and next-generation climate models. Even though the SGP site is a rural location, surprisingly large horizontal gradients in aerosol properties were frequently observed. For example, 90 % of the 3, 9, and 27 km cell mean organic matter concentrations differed from the 81 km cell around the SGP site by as much as ∼ 46 %, large spatial variability in aerosol number concentrations and size distributions were found during new particle formation events, and consequently 90 % of the 3, 9, and 27 km cell mean CCN number concentrations differed from the 81 km cell mean by as much as ∼ 38 %. The spatial variability varied seasonally for some aerosol properties, with some having larger spatial variability during the spring and others having larger variability during the late summer. While measurements at a single surface site cannot reflect the surrounding variability of aerosol properties at a given time, aircraft measurements that are averaged within an 81 km cell were found to be similar to many, but not all, aerosol properties measured at the ground SGP site. This analysis suggests that it is reasonable to directly compare most ground SGP site aerosol measurements with coarse global climate model predictions. In addition, the variability quantified by the aircraft can be used as an uncertainty range when comparing the surface point measurements with model predictions that use coarse grid spacings.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2019

Technology Development Roadmap for Habitable-Zone Exoplanet Observatory (HabEx) Baseline 4-M Primary Mirror

The Habitable Exoplanet Observatory (HabEx) is one of four mission concepts under study for the 2020 Astrophysics Decadal Survey. Its goal is to directly image and spectroscopically characterize planetary systems in the habitable zone around nearby sun-like stars. Additionally, HabEx will perform a broad range of general astrophysics science enabled by 115 to 2500 nm spectral range and 3 x 3 arc-minute FOV. Critical to achieving the HabEx science goals is a large, ultra-stable UV/Optical/Near-IR (UVOIR) telescope. The baseline HabEx telescope is 4-meter off-axis unobscured, diffraction limited at 400 nm with wavefront stability on the order of a few 10s of picometers. The technology readiness level (TRL) to manufacture and test the HabEx baseline primary mirror is assessed to be at TRL-6 for all but two TRL-4 technologies: 1) non-destructive process to quantify CTE homogeneity of a 4-m mirror substrate with a spatial sampling of at least 100 x 100 to better than +/- 1 ppb/K; and, 2) process to quantify self-weight gravity deflection to better than 4-nm rms over a 100 x 100 spatial sampling. This paper reviews the technology needs to manufacture the HabEx primary mirror, assesses their TRL and proposes a roadmap to mature the two remaining technologies to TRL-6.

Space Telescope Technology↗

NASA NTRS1976

Hadamard transform imager and imaging spectrometer

An imager and a spectrometric imager, which achieve multiplexing by the use of binary optical encoding masks, have been built and tested. The masks are based on orthogonal, pseudorandom digital codes derived from Hadamard matrices. The spatial (and/or spectral) data are therefore obtained in the form of a Hadamard transform of the spatial (and/or spectral) scene. Computer algorithms are used to decode the data and reconstruct images of the original scene. The hardware, algorithms processing and display facility are described. A number of spatial and spatial/spectral images, obtained in the laboratory, are presented.

Swift, R. D.↗