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This presentation will report on the status of several projects and initiatives under development by NASA LaRC's CEOS Systems Engineering Office (SEO). The content addresses work in support of agriculture, forestry, land imaging and the Open Data Cube project.
We have analyzed the data from a large-scale CO survey toward the northern region of the Small Magellanic Cloud (SMC) obtained with the Atacama Compact Array (ACA) stand-alone mode of ALMA. The primary aim of this study is to comprehensively understand the behavior of CO as an H2 tracer in a low-metallicity environment (Z ∼ 0.2 Zꙩ). The total number of mosaic fields is ∼8000, which results in a field coverage of 0.26 sq.deg (∼2.9 ×10^(5) sq.pc), corresponding to ∼10% of the area of the galaxy. The sensitive ∼2 pc resolution observations reveal the detailed structure of the molecular clouds previously detected in the single-dish NANTEN survey. We have detected a number of compact CO clouds within lower H2 column density (∼10^(20) per sq.cm) regions whose angular scale is similar to the ACA beam size. Most of the clouds in this survey also show peak brightness temperature as low as <1 K, which for optically thick CO emission implies an emission size much smaller than the beam size, leading to beam dilution. The comparison between an available estimation of the total molecular material traced by thermal dust emission and the present CO survey demonstrates that more than ∼90% of H(2) gas cannot be traced by the low-J CO emission. Our processed data cubes and 2D images are publicly available.
The software described in this document provides I/O functions to be used with Moderate Resolution Spectroradiometer (MODIS) level 1 and 2 data, and could be easily extended to other data sources. This data is in a scan cube data format: a 3-dimensional ragged array containing multiple bands which have resolutions ranging from 250 to 1000 meters. The complexity of the data structure is handled internally by the library. The I/O calls allow the user to access any pixel in any band through 'C' structure syntax. The high MODIS data volume (approaching half a terabyte per day) has been a driving factor in the library design. To avoid recopying data for user access, all I/O is performed through dynamic 'C' pointer manipulation. This manual contains background material on MODIS, several coding examples of library usage, in-depth discussions of each function, reference 'man' type pages, and several appendices with details of the included files used to customize a user's data product for use with the library.
MinMap has been selected by the Lunar Scout program to characterize and map the mineral composition of the Moon. The instrument will be built as a collaborative effort between Brown University, SETS Technology Inc., and Ball Aerospace Corp. MinMap is a visible to near-infrared imaging spectrometer that contains 192 spectral channels from 0.35-2.4 microns with signal to noise greater than 200 and 256 cross-track spatial elements. The spectrometer design has a 6 deg field of view (FOV) and utilizes grating dispersive elements and two dimensional detectors (no moving parts). An 'image cube' of data is produced that contains two dimensions of spatial information and one dimension of spectral information. All spectral channels and cross-track spatial elements are recorded simultaneously with spacecraft motion scanning the second spatial dimension. The high spectral resolution and continuous spectral range of MinMap are designed to measure the diagnostic absorption features of principal lunar minerals and their lithologic mixtures. Since the optical properties of lunar materials change in a regular manner upon exposure to the space environment, this spectral range is also quite sensitive to variations in exposure history (soil maturity). Nominal measurement stragegy is to obtain full global data of the Moon at 180 m/pixel from a 450 km polar orbit during the first month or two of operation. A 100 km orbit is anticipated for the remaining part of a 1 year mission allowing higher resolution data (approx. 80 m/pixel) to be obtained for targeted regions. MinMap exceeds LE x SWG's measurement recommendations and will provide the highest spatial resolution compositional map of lunar rocks and soils currently planned for orbital missions. Since all spectral channels are co-registered and obtained simultaneously, 'image cube' data swaths will be available for analysis almost immediately.
Many imaging applications require quantitative determination of a scene's spectral radiance. This paper describes a new system capable of real-time spectroradiometric imagery. Operating at a full-spectrum update rate of 30Hz, this imager is capable of collecting a 30 point spectrum from each of three imaging heads: the first operates from 400 nm to 950 nm, with a 2% bandwidth; the second operates from 1.5 micro-m to 5.5 micro-m with a 1.5% bandwidth; the third operates from 5 micro-m to 12 micro-m, also at a 1.5% bandwidth. Standard image format is 256 x 256, with 512 x 512 possible in the VIS/NIR head. Spectra of up to 256 points are available at proportionately lower frame rates. In order to make such a tremendous amount of data more manageable, internal processing electronics perform four important operations on the spectral imagery data in real-time. First, all data in the spatial/spectral cube of data is spectro-radiometrically calibrated as it is collected. Second, to allow the imager to simulate sensors with arbitrary spectral response, any set of three spectral response functions may be loaded into the imager including delta functions to allow single wavelength viewing; the instrument then evaluates the integral of the product of the scene spectral radiances and the response function. Third, more powerful exploitation of the gathered spectral radiances can be effected by application of various spectral-matched filtering algorithms to identify pixels whose relative spectral radiance distribution matches a sought-after spectral radiance distribution, allowing materials-based identification and discrimination. Fourth, the instrument allows determination of spectral reflectance, surface temperature, and spectral emissivity, also in real-time. The spectral imaging technique used in the instrument allows tailoring of the frame rate and/or the spectral bandwidth to suit the scene radiance levels, i.e., frame rate can be reduced, or bandwidth increased to improve SNR when viewing low radiance scenes. The unique challenges of design and calibration are described. Pixel readout rates of 160 MHz, for full frame readout rates of 1000 Hz (512 x 512 image) present the first challenge; processing rates of nearly 600 million integer operations per second for sensor emulation, or over 2 billion per second for matched filtering, present the second. Spatial and spectral calibration of 66,536 pixels (262,144 for the 512 x 512 version) and up to 1,000 spectral positions mandate novel decoupling methods to keep the required calibration memory to a reasonable size. Large radiometric dynamic range also requires care to maintain precision operation with minimum memory size.
This is an annual report for the CEOS Systems Engineering Office to the CEOS group
Isosurface extraction is a common analysis and visualization technique for three-dimensional scalar data. Marching Cubes is the most commonly-used algorithm for finding polygonal representations of isosurfaces in such data. We extend Marching Cubes to produce geometry for data sets that lie in spherical and cylindrical coordinate systems as well as show the steps for derivation of transformations for other coordinate systems.
By developing and enhancing various services and tools, the GES DISC provides users with the capability to access and visualize data, and to make comparisons of data from multiple sensor and models via a number of cross-discipline projects. Discovering Data via Faceted Web Interface Web interface to data products and services Search and Download mechanisms Dataset Landing Pages Accessing Data through Interoperable Services: GDS – GrADS Data Server OPeNDAP - Open-source Project for a Network Data Access Protocol WMS – OGC service GIS connector – allowing IS tools to access data easier (coming soon) HTTPS -- direct online access Downloading Data Basics: Subset and egridding Service – Parameter, Spatial, Time, Vertical, Mean averaging, format conversion, and regridding for L3/L4 gridded data Swath Data Subsetter – Parameter, spatial subset of L2 /L1 data. Visualizing Data Online: Giovanni –Visualization and Analysis L3/L4 gridded data AIRS NRT Viewer – AIRS near-real-time DQVis – L2 data quality visualization
The optical alignment of the star trackers on the Global Precipitation Measurement (GPM) core spacecraft at NASA Goddard Space Flight Center (GSFC) was challenging due to the layout and structural design of the GPM Lower Bus Structure (LBS) in which the star trackers are mounted as well as the presence of the star tracker shades that blocked line-of-sight to the primary star tracker optical references. The initial solution was to negotiate minor changes in the original LBS design to allow for the installation of a removable item of ground support equipment (GSE) that could be installed whenever measurements of the star tracker optical references were needed. However, this GSE could only be used to measure secondary optical reference cube faces not used by the star tracker vendor to obtain the relationship information and matrix transformations necessary to determine star tracker alignment. Unfortunately, due to unexpectedly large orthogonality errors between the measured secondary adjacent cube faces and the lack of cube calibration data, we required a method that could be used to measure the same reference cube faces as originally measured by the vendor. We describe an alternative technique to theodolite auto-collimation for measurement of an optical reference mirror pointing direction when normal incidence measurements are not possible. This technique was used to successfully align the GPM star trackers and has been used on a number of other NASA flight projects. We also discuss alignment theory as well as a GSFC-developed theodolite data analysis package used to analyze angular metrology data.
Isosurface visualization is fundamental for exploring and analyzing 3D volumetric data. Marching cubes (MC) algorithms with linear interpolation are commonly used for isosurface extraction and visualization. Although linear interpolation is easy to implement, it has limitations when the underlying data is complex and high-order, which is the case for most real-world data. Linear interpolation can output vertices at the wrong location. Its inability to deal with sharp features and features smaller than grid cells can lead to an incorrect isosurface with holes and broken pieces. Despite these limitations, isosurface visualizations typically do not include insight into the spatial location and the magnitude of these errors. We utilize high-order interpolation methods with MC algorithms and interactive visualization to highlight these uncertainties. Our visualization tool helps identify the regions of high interpolation errors. It also allows users to query local areas for details and compare the differences between isosurfaces from different interpolation methods. In addition, we employ high-order methods to identify and reconstruct possible features that linear methods cannot detect. We showcase how our visualization tool helps explore and understand the extracted isosurface errors through synthetic and real-world data.
Here, in this paper, we study the propagation of data uncertainty through the marching cubes algorithm for isosurface visualization for correlated uncertain data. Consideration of correlation has been shown paramount for avoiding errors in uncertainty quantification and visualization in multiple prior studies. Although the problem of isosurface uncertainty with spatial data correlation has been previously addressed, there are two major limitations to prior treatments. First, there are no analytical formulations for uncertainty quantification of isosurfaces when the data uncertainty is characterized by a Gaussian distribution with spatial correlation. Second, as a consequence of the lack of analytical formulations,existing techniques resort to a Monte Carlo sampling approach, which is expensive and difficult to integrate into visualization tools. To address these limitations, we present a closed-form framework to efficiently derive uncertainty in marching cubes level-sets for Gaussian uncertain data with spatial correlation (MAGIC). To derive closed-form solutions, we leverage the Hinkley's derivation on the ratio of Gaussian distributions. With our analytical framework, we achieve a significant speed-up and enhanced accuracy of uncertainty quantification over classical Monte Carlo methods. We further accelerate our analytical solutions using many-core processors to achieve speed-ups up to 585× and integrability with production visualization tools for broader impact. We demonstrate the effectiveness of our correlation-aware uncertainty framework through experiments on meteorology, urban flow, and astrophysics simulation datasets.
A solution is obtained for the geodetic boundary value problem which defines height anomalies to + or - 5 cm, if the earth were rigid. The solution takes into account the existence of the earth's topography, together with its ellipsoidal shape and atmosphere. A relation is also established between the commonly used solution of Stokes and a development correct to order e cubed. The data requirements call for a complete definition of gravity anomalies at the surface of the earth and a knowledge of elevation characteristics at all points exterior to the geoid. In addition, spherical harmonic representations must be based on geocentric rather than geodetic latitudes.
Flight experiments on the importance of gravity to plant growth and behavior are reported. The following studies were undertaken: (1) hyperastic responses to incremental changes of an axially imposed centripetal force; (2) Spacelab-1 experiments, methods for preparing soil in flight hardware containers were impound, to ensure desired moisture content and minimal contamination probability; (3) mesocotyl growth patterns were established by Avena lore exposure to red light during early seedling outogency; (4) the development of flight hardware; (5) choice of member of seedlings in each cube; (6) data processing and reduction; (7) clinostat validation; circummutation in space was more vigorous than on Earth based clinostat.
The success of JPL's Next Generation Imaging Spectrometer (NGIS) in Earth remote sensing has inspired a follow-on instrument project, the MaRSPlus Sensor System (MSS). One of JPL's responsibilities in the MSS project involves updating the documentation from the previous JPL airborne imagers to provide all the information necessary for an outside customer to operate the instrument independently. As part of this documentation update, I created detailed electrical cabling diagrams to provide JPL technicians with clear and concise build instructions and a database to track the status of cables from order to build to delivery. Simultaneously, a distributed motor control system is being developed for potential use on the proposed 2018 Mars rover mission. This system would significantly reduce the mass necessary for rover motor control, making more mass space available to other important spacecraft systems. The current stage of the project consists of a desktop computer talking to a single "cold box" unit containing the electronics to drive a motor. In order to test the electronics, I developed a graphical user interface (GUI) using MATLAB to allow a user to send simple commands to the cold box and display the responses received in a user-friendly format.
This is a report from the CEOS Systems Engineering Office for the Strategic Implementation Team Meeting
With the availability of Magnetic Resonance Imaging (MRI) technology in the medical field and the development of powerful graphics engines in the computer world the possibility now exists for the simulation of surgery using data obtained from an actual patient. This paper describes a surgical simulation system which will allow a physician or a medical student to practice surgery on a patient without ever entering an operating room. This could substantially lower the cost of medial training by providing an alternative to the use of cadavers. This project involves the use of volume data acquired by MRI which are converted to polygonal form using a corrected marching cubes algorithm. The data are then colored and a simulation of surface response based on springy structures is performed in real time. Control for the system is obtained through the use of an attached analog-to-digital unit. A remote electronic device is described which simulates an imaginary tool having features in common with both arthroscope and laparoscope.
The OVERFLOW Machine Learning Airfoil Performance (PALMO) database has been created to enable robust modeling of airfoil performance in a variety of applications. The database uses OVERFLOW simulation data second-order accurate in time and fourth-order accurate in space with Spalart-Allmaras turbulence closure. The foundation of the in-development PALMO database is the airfoil base cube. Each base cube includes simulation data parametrized over a range of Mach numbers, Reynolds numbers, and angles-of-attack. This first release of the database includes the NACA 4-series airfoils, with parametrization in airfoil thickness and camber from an NACA 0006 to an NACA 4424. In total, 52,480 NACA 4-series calculations were run on the NASA High-End Compute Capability (HECC) supercomputer and the corresponding airfoil performance coefficients are embedded in the Appendix of this document for public distribution. This provides high-order-accurate simulation data covering a wide range of aerospace design applications, which enables users to develop OVERFLOW-quality airfoil performance look-up tables without additional high-performance computing. In addition to engineering design and analysis of aerospace vehicles, PALMO is well suited to be a benchmark dataset for the development and testing of machine learning methods in aerospace engineering. Downstream surrogate models enable OVERFLOW- quality airfoil performance predictions for any arbitrary combination of camber, thickness, Mach number, Reynolds number, and angle-of-attack within the bounds of the database.
The OVERFLOW Machine Learning Airfoil Performance (PALMO) database has been created to enable robust modeling of airfoil performance in a variety of applications. The PALMO database uses OVERFLOW simulation data second-order accurate in time and fourth-order accurate in space with Spalart-Allmaras turbulence closure. The foundation of the in-development PALMO database is the airfoil base cube. Each base cube includes simulation data parametrized over a range of Mach numbers, Reynolds numbers, and angles-of-attack. This database includes the NACA 4-series airfoils, with parametrization in airfoil thickness and camber from an NACA 0006 to an NACA 4424. In total, 52,480 NACA 4-series OVERFLOW calculations were run on the NASA High-End Compute Capability (HECC) supercomputer. This provides high-order-accurate simulation data covering a wide range of aerospace design applications, which enables users to develop accurate airfoil performance look-up tables without additional high-performance computing. In addition to engineering design and analysis of aerospace vehicles, PALMO is well suited to be a benchmark dataset for the development and testing of machine learning methods in aerospace engineering. This work presents an example PALMO surrogate model that enables accurate airfoil performance predictions for any arbitrary combination of camber, thickness, Mach number, Reynolds number, and angle of attack within the bounds of the database. Airfoil performance tables predicted for an airfoil not used in training the model are used in three-dimensional OVERFLOW simulations to quantify the downstream accuracy on aggregate rotor performance metrics. For the NACA 3415 airfoil, which had no common thickness or camber with the training data, the surrogate predicted and CFD generated tables were within 2.1% of each other in the forward flight lift to drag metric. This suggests that performance tables generated for airfoils within the bounds of the PALMO database will yield aggregate rotor performance predictions on par with tables generated from directly running OVERFLOW airfoil calculations. The PALMO airfoil performance coefficients are available publicly.