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NASA NTRS2012

Global Characterization and Monitoring of Forest Cover Using Landsat Data: Opportunities and Challenges

The compilation of global Landsat data-sets and the ever-lowering costs of computing now make it feasible to monitor the Earth's land cover at Landsat resolutions of 30 m. In this article, we describe the methods to create global products of forest cover and cover change at Landsat resolutions. Nevertheless, there are many challenges in ensuring the creation of high-quality products. And we propose various ways in which the challenges can be overcome. Among the challenges are the need for atmospheric correction, incorrect calibration coefficients in some of the data-sets, the different phenologies between compilations, the need for terrain correction, the lack of consistent reference data for training and accuracy assessment, and the need for highly automated characterization and change detection. We propose and evaluate the creation and use of surface reflectance products, improved selection of scenes to reduce phenological differences, terrain illumination correction, automated training selection, and the use of information extraction procedures robust to errors in training data along with several other issues. At several stages we use Moderate Resolution Spectroradiometer data and products to assist our analysis. A global working prototype product of forest cover and forest cover change is included.

Global↗

NASA NTRS2003

Hydrogen peroxide stimulates ubiquitin-conjugating activity and expression of genes for specific E2 and E3 proteins in skeletal muscle myotubes

Reactive oxygen species (ROS) are thought to promote muscle atrophy in chronic wasting diseases, but the underlying mechanism has not been determined. Here we show that H2O2 stimulates ubiquitin conjugation to muscle proteins through transcriptional regulation of the enzymes (E2 and E3 proteins) that conjugate ubiquitin to muscle proteins. Incubation of C2C12 myotubes with 100 microM H2O2 increased the rate of 125I-labeled ubiquitin conjugation to muscle proteins in whole cell extracts. This response required at least 4-h exposure to H2O2 and persisted for at least 24 h. Preincubating myotubes with cycloheximide or actinomycin D blocked H2O2 stimulation of ubiquitin-conjugating activity, suggesting that gene transcription is required. Northern blot analyses revealed that H2O2 upregulates expression of specific E3 and E2 proteins that are thought to regulate muscle catabolism, including atrogin1/MAFbx, MuRF1, and E214k. These results suggest that ROS stimulate protein catabolism in skeletal muscle by upregulating the ubiquitin conjugation system.

Non-NASA Center↗

NASA NTRS2011

4 Vesta in Color: High Resolution Mapping from Dawn Framing Camera Images

Rotational surface variations on asteroid 4 Vesta have been known from ground-based and HST observations, and they have been interpreted as evidence of compositional diversity. NASA s Dawn mission entered orbit around Vesta on July 16, 2011 for a year-long global characterization. The framing cameras (FC) onboard the Dawn spacecraft will image the asteroid in one clear (broad) and seven narrow band filters covering the wavelength range between 0.4-1.0 microns. We present color mapping results from the Dawn FC observations of Vesta obtained during Survey orbit (approx.3000 km) and High-Altitude Mapping Orbit (HAMO) (approx.950 km). Our aim is to create global color maps of Vesta using multi spectral FC images to identify the spatial extent of compositional units and link them with other available data sets to extract the basic mineralogy. While the VIR spectrometer onboard Dawn has higher spectral resolution (864 channels) allowing precise mineralogical assessment of Vesta s surface, the FC has three times higher spatial resolution in any given orbital phase. In an effort to extract maximum information from FC data we have developed algorithms using laboratory spectra of pyroxenes and HED meteorites to derive parameters associated with the 1-micron absorption band wing. These parameters will help map the global distribution of compositionally related units on Vesta s surface. Interpretation of these units will involve the integration of FC and VIR data.

Reddy, V.↗

NASA NTRS2017

Molecular Analyzer for Complex Refractory Organic-Rich Surfaces (MACROS)

The Molecular Analyzer for Complex Refractory Organic-rich Surfaces, MACROS, is a novel instrument package being developed at NASA Goddard Space Flight Center. MACROS enables the in situ characterization of a sample's composition by coupling two powerful techniques into one compact instrument package: (1) laser desorption/ionization time-of-flight mass spectrometry (LDMS) for broad detection of inorganic mineral composition and non-volatile organics, and (2) liquid-phase extraction methods to gently isolate the soluble organic and inorganic fraction of a planetary powder for enrichment and detailed analysis by liquid chromatographic separation coupled to LDMS. The LDMS is capable of positive and negative ion detection, precision mass selection, and fragment analysis. Two modes are included for LDMS: single laser LDMS as the broad survey mode and two step laser mass spectrometry (L2MS). The liquid-phase extraction will be done in a newly designed extraction module (EM) prototype, providing selectivity in the analysis of a complex sample. For the sample collection, a diamond drill front end will be used to collect rock/icy powder. With all these components and capabilities together, MACROS offers a versatile analytical instrument for a mission targeting an icy moon, carbonaceous asteroid, or comet, to fully characterize the surface composition and advance our understanding of the chemical inventory present on that body.

Getty, Stephanie A.↗

NASA NTRS2017

Status of the TESS Science Processing Operations Center

The Transiting Exoplanet Survey Satellite (TESS) science pipeline is being developed by the Science Processing Operations Center (SPOC) at NASA Ames Research Center based on the highly successful Kepler Mission science pipeline. Like the Kepler pipeline, the TESS science pipeline will provide calibrated pixels, simple and systematic error-corrected aperture photometry, and centroid locations for all 200,000+ target stars, observed over the 2-year mission, along with associated uncertainties. The pixel and light curve products are modeled on the Kepler archive products and will be archived to the Mikulski Archive for Space Telescopes (MAST). In addition to the nominal science data, the 30-minute Full Frame Images (FFIs) simultaneously collected by TESS will also be calibrated by the SPOC and archived at MAST. The TESS pipeline will search through all light curves for evidence of transits that occur when a planet crosses the disk of its host star. The Data Validation pipeline will generate a suite of diagnostic metrics for each transit-like signature discovered, and extract planetary parameters by fitting a limb-darkened transit model to each potential planetary signature. The results of the transit search will be modeled on the Kepler transit search products (tabulated numerical results, time series products, and pdf reports) all of which will be archived to MAST.

high performance computing↗

NASA NTRS2013

Analyzing Tropical Waves Using the Parallel Ensemble Empirical Model Decomposition Method: Preliminary Results from Hurricane Sandy

In this study, we discuss the performance of the parallel ensemble empirical mode decomposition (EMD) in the analysis of tropical waves that are associated with tropical cyclone (TC) formation. To efficiently analyze high-resolution, global, multiple-dimensional data sets, we first implement multilevel parallelism into the ensemble EMD (EEMD) and obtain a parallel speedup of 720 using 200 eight-core processors. We then apply the parallel EEMD (PEEMD) to extract the intrinsic mode functions (IMFs) from preselected data sets that represent (1) idealized tropical waves and (2) large-scale environmental flows associated with Hurricane Sandy (2012). Results indicate that the PEEMD is efficient and effective in revealing the major wave characteristics of the data, such as wavelengths and periods, by sifting out the dominant (wave) components. This approach has a potential for hurricane climate study by examining the statistical relationship between tropical waves and TC formation.

PEEMD↗

NASA NTRS2020

Convolutional Neural Network for Transition Modeling Based on Linear Stability Theory

Transition prediction is an important aspect of aerodynamic design because of its impact on skin friction and potential coupling with flow separation characteristics. Traditionally, the modeling of transition has relied on correlation-based empirical formulas based on integral quantities such as the shape factor of the boundary layer. However, in many applications of computational fluid dynamics, the shape factor is not straightforwardly available or not well-defined. We propose using the complete velocity profile along with other quantities (e.g., frequency, Reynolds number) to predict the perturbation amplification factor. While this can be achieved with regression models based on a classical fully connected neural network, such a model can be computationally more demanding. We propose a novel convolutional neural network inspired by the underlying physics as described by the stability equations. Specifically, convolutional layers are first used to extract integral quantities from the velocity profiles, and then fully connected layers are used to map the extracted integral quantities, along with frequency and Reynolds number, to the output (amplification ratio). Numerical tests on classical boundary layers clearly demonstrate the merits of the proposed method. More importantly, we demonstrate that, for Tollmien-Schlichting instabilities in two-dimensional, low-speed boundary layers, the proposed network encodes information in the boundary layer profiles into an integral quantity that is strongly correlated to a well-known, physically defined parameter – the shape factor.

Laminar-turbulent transition↗

NASA NTRS2001

A Novel Approach for Reducing Rotor Tip-Clearance Induced Noise in Turbofan Engines

Rotor tip-clearance induced noise, both in the form of rotor self noise and rotor-stator interaction noise , constitutes a significant component of total fan noise. Innovative yet cost effective techniques to suppress rotor-generated noise are, therefore, of foremost importance for improving the noise signature of turbofan engines. To that end, the feasibility of a passive porous treatment strategy to positively modify the tip-clearance flow field is addressed. The present study is focused on accurate viscous flow calculations of the baseline and the treated rotor flow fields. Detailed comparison between the computed baseline solution and experimental measurements shows excellent agreement. Tip-vortex structure, trajectory, strength, and other relevant aerodynamic quantities are extracted from the computed database. Extensive comparison between the untreated and treated tip-clearance flow fields is performed. The effectiveness of the porous treatment for altering the rotor-tip vortex flow field in general and reducing the intensity of the tip vortex, in particular, is demonstrated. In addition, the simulated flow field for the treated tip clearly shows that substantial reduction in the intensity of both the shear layer roll-up and boundary layer separation on the wall is achieved.

Khorrami, Mehdi R.↗

NASA NTRS1995

Characterizing SOI Wafers By Use Of AOTF-PHI

Developmental nondestructive method of characterizing layers of silicon-on-insulator (SOI) wafer involves combination of polarimetric hyperspectral imaging by use of acousto-optical tunable filters (AOTF-PHI) and computational resources for extracting pertinent data on SOI wafers from polarimetric hyperspectral images. Offers high spectral resolution and both ease and rapidity of optical-wavelength tuning. Further efforts to implement all of processing of polarimetric spectral image data in special-purpose hardware for sake of procesing speed. Enables characterization of SOI wafers in real time for online monitoring and adjustment of production. Also accelerates application of AOTF-PHI to other applications in which need for high-resolution spectral imaging, both with and without polarimetry.

Cheng, Li-Jen↗

NASA NTRS2005

E-Nose Vapor Identification Based on Dempster-Shafer Fusion of Multiple Classifiers

Electronic nose (e-nose) vapor identification is an efficient approach to monitor air contaminants in space stations and shuttles in order to ensure the health and safety of astronauts. Data preprocessing (measurement denoising and feature extraction) and pattern classification are important components of an e-nose system. In this paper, a wavelet-based denoising method is applied to filter the noisy sensor measurements. Transient-state features are then extracted from the denoised sensor measurements, and are used to train multiple classifiers such as multi-layer perceptions (MLP), support vector machines (SVM), k nearest neighbor (KNN), and Parzen classifier. The Dempster-Shafer (DS) technique is used at the end to fuse the results of the multiple classifiers to get the final classification. Experimental analysis based on real vapor data shows that the wavelet denoising method can remove both random noise and outliers successfully, and the classification rate can be improved by using classifier fusion.

Li, Winston↗

NASA NTRS2004

AIRS Data Subsetting Service at the Goddard Earth Sciences (GES) DISC/DAAC

The AIRS mission, as a combination of the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), brings climate research and weather prediction into 21st century. From NASA' Aqua spacecraft, the AIRS/AMSU/HSB instruments measure humidity, temperature, cloud properties and the amounts of greenhouse gases. The AIRS also reveals land and sea- surface temperatures. Measurements from these three instruments are analyzed . jointly to filter out the effects of clouds from the IR data in order to derive clear-column air-temperature profiles and surface temperatures with high vertical resolution and accuracy. Together, they constitute an advanced operational sounding data system that have contributed to improve global modeling efforts and numerical weather prediction; enhance studies of the global energy and water cycles, the effects of greenhouse gases, and atmosphere-surface interactions; and facilitate monitoring of climate variations and trends. The high data volume generated by the AIRS/AMSU/HSB instruments and the complexity of its data format (Hierarchical Data Format, HDF) are barriers to AIRS data use. Although many researchers are interested in only a fraction of the data they receive or request, they are forced to run their algorithms on a much larger data set to extract the information of interest. In order to better server its users, the GES DISC/DAAC, provider of long-term archives and distribution services as well science support for the AIRS/AMSU/HSB data products, has developed various tools for performing channels, variables, parameter, spatial and derived products subsetting, resampling and reformatting operations. This presentation mainly describes the web-enabled subsetting services currently available at the GES DISC/DAAC that provide subsetting functions for all the Level 1B and Level 2 data products from the AIRS/AMSU/HSB instruments.

Vicente, Gilberto A.↗

NASA NTRS2020

Learning instrument invariant characteristics for generating high-resolution global coral reef maps

Coral reefs are one of the most biologically complex and diverse ecosystems within the shallow marine environment. Unfortunately, these underwater ecosystems are threatened by a number of anthropogenic challenges, including ocean acidification and warming, overfishing, and the continued increase of marine debris in oceans. This requires a comprehensive assessment of the world's coastal environments, including a quantitative analysis on the health and extent of coral reefs and other associated marine species, as a vital Earth Science measurement. However, limitations in observational and technological capabilities inhibit global sustained imaging of the marine environment. Harmonizing multimodal data sets acquired using different remote sensing instruments presents additional challenges, thereby limiting the availability of good quality labeled data for analysis. In this work, we develop a deep learning model for extracting domain invariant features from multimodal remote sensing imagery and creating high-resolution global maps of coral reefs by combining various sources of imagery and limited hand-labeled data available for certain regions. This framework allows us to generate, for the first time, coral reef segmentation maps at 2-meter resolution, which is a significant improvement over the kilometer-scale state-of-the-art maps. Additionally, this framework doubles accuracy and IoU metrics over baselines that do not account for domain invariance.

Domain Adaptation↗

NASA NTRS2019

Deep Learning Emulation of Atmospheric Correction for Geostationary Sensors

New generation geostationary satellites make reflectance observations available at a continental scale with unprecedented spatiotemporal resolution and spectral range. Generating Earth monitoring products from these observations requires retrieval of the basic parameter, surface reflectance (SR), by atmospheric correction (AC). Algorithms for atmospheric correction, including Multi-Angle Implementation of Atmospheric Correction (MAIAC), are adapted for each sensor and are too computationally complex to be run in real time, relying instead on look-up tables with precomputed values. Machine learning methods, including convolutional neural networks, have demonstrated performance in learning complex, nonlinear mappings and extracting insight from high-dimensional remote sensing data. In this work, we present a deep learning emulator of MAIAC to retrieve both SR and cloud products. Using this adaptation of deep learning-based emulation to remote sensing, we demonstrate stable SR retrieval over a variety of land covers and viewing conditions and accurate cloud detection. Further, a comparison of computation time suggests emulation as a compelling alternative for expensive physical simulation, especially for applications benefited by near-real time data, such as agricultural management and disaster response.

Duffy, Kate↗

NASA NTRS2012

Boundary-Layer Stability Analysis of the Mean Flows Obtained Using Unstructured Grids

Boundary-layer stability analyses of mean flows extracted from unstructured-grid Navier- Stokes solutions have been performed. A procedure has been developed to extract mean flow profiles from the FUN3D unstructured-grid solutions. Extensive code-to-code validations have been performed by comparing the extracted mean ows as well as the corresponding stability characteristics to the predictions based on structured-grid solutions. Comparisons are made on a range of problems from a simple at plate to a full aircraft configuration-a modified Gulfstream-III with a natural laminar flow glove. The future aim of the project is to extend the adjoint-based design capability in FUN3D to include natural laminar flow and laminar flow control by integrating it with boundary-layer stability analysis codes, such as LASTRAC.

Liao, Wei↗

NASA NTRS2003

Thermal Property Measurement of Semiconductor Melt using Modified Laser Flash Method

This study further developed standard laser flash method to measure multiple thermal properties of semiconductor melts. The modified method can determine thermal diffusivity, thermal conductivity, and specific heat capacity of the melt simultaneously. The transient heat transfer process in the melt and its quartz container was numerically studied in detail. A fitting procedure based on numerical simulation results and the least root-mean-square error fitting to the experimental data was used to extract the values of specific heat capacity, thermal conductivity and thermal diffusivity. This modified method is a step forward from the standard laser flash method, which is usually used to measure thermal diffusivity of solids. The result for tellurium (Te) at 873 K: specific heat capacity 300.2 Joules per kilogram K, thermal conductivity 3.50 Watts per meter K, thermal diffusivity 2.04 x 10(exp -6) square meters per second, are within the range reported in literature. The uncertainty analysis showed the quantitative effect of sample geometry, transient temperature measured, and the energy of the laser pulse.

Lin, Bochuan↗

NASA NTRS1992

The effects of radiation drag on radial, relativistic hydromagnetic winds

The effects of drag on an idealized relativistic MHD wind of radial geometry are studied. The astrophysical motivation is to understand the effects of radiation drag on the dynamics of a jet or wind passing through the intense radiation field of an accreting compact object. From a critical point analysis, it is found that a slow magnetosonic point can appear in a dragged flow even in the absence of gravitational force, as a result of a balance between the drag force and the combination of thermal pressure and centrifugal forces. As in the undragged case, the Alfven point does not impose any constraints on the flow. Although it is formally possible for a dragged flow to possess more than one fast magnetosonic point, it is shown that this is unlikely in practice. In the limit of a 'cold', centrifugally driven flow, it is shown that the fast magnetosonic point moves to infinite radius, just as in the drag-free case. For a given mass flux, the total energy output carried to infinity, and the final partition between the kinetic energy and the Poynting flux, are the same for the dragged and the drag-free flows. The main effects of radiation drag are to increase the amount of energy and angular momentum extracted from the source and to redistribute the regions where acceleration occurs in the flow. This is accomplished through the storage and release of magnetic energy, as a result of additional winding and compression of the field caused by the action of the drag. For a relativistic wind, the dissipated energy can exceed the final kinetic energy of the flow and may be comparable to the total flow energy (which is dominated by Poynting flux). The energy lost to radiation drag will appear as a Doppler-boosted beam of scattered radiation, which could dominate the background radiation if the flow is well-collimated.

Li, Zhi-Yun↗

NASA NTRS2005

Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data

An object tracking technique is provided which, given: (i) a potentially large data set; (ii) a set of dimensions along which the data has been ordered; and (iii) a set of functions for measuring the similarity between data elements, a set of objects are produced. Each of these objects is defined by a list of data elements. Each of the data elements on this list contains the probability that the data element is part of the object. The method produces these lists via an adaptive, knowledge-based search function which directs the search for high-probability data elements. This serves to reduce the number of data element combinations evaluated while preserving the most flexibility in defining the associations of data elements which comprise an object.

Hill, Matthew L.↗

NASA NTRS2008

Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data

Hill, Matthew L.↗