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At least 667 records · Page 37

Geonex: Land Surface Monitoring from a New Generation of Geostationary Sensors

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

Nemani, Ramakrishna R.↗

Optical Communication Link Assessment Utilizing a Modulated Retro-Reflector on Mars

This work proposes the duplexing of an optical free-space (FS) communication link while minimizing the required power and complexity by using a modulated retro-reflector (MRR) within a system that is shown for a Mars orbiter and rover scenario. The MRR is placed on a planet’s surface while the laser source is on the orbiter to achieve satellite communications with surface locations. The information, which varies from raw sensor data to multimedia files such as videos and other media, can be sent through this communication path. Due to the use of an MRR, an alternative modulating scheme is required to interpret a distorted signal. The arrangement suggested to prove the capabilities of the link is a nested pulse-position modulation (PPM) structure. A link budget was derived to show the link characteristics of this proposed system.

Link Power Budget↗

Earth Observations from Geostationary Satellites

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GeoNEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GeoNEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GeoNEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

Earth↗

Bounding Methods for Heterogeneous Lidar-derived Navigational Geofences

Safe Unmanned Aerial Vehicle (UAV) operations near the ground require navigation methods that avoid fixed obstacles such as buildings, power lines and trees. Aerial lidar surveys of ground structures are available with the precision and accuracy to geolocate obstacles, but the high volume of raw survey data can exceed the compute power of onboard processors and the rendering ability of ground-based flight planning maps. Representing ground structures with bounding polyhedra instead of point clouds greatly reduces the data size and can enable effective obstacle avoidance, as long as the bounding geometry envelopes the structures with high spatial fidelity. This report describes in detail four methods to compute bounding geometries of ground obstacles from lidar point clouds. The four methods are: 1) 2.5D Maximum Elevation Box, 2) 2.5D Ground Map Extrusion, 3) 3D Bounding Cylinder, and 4) 3D Bounding Box. The methods are applied to five point cloud datasets from lidar surveys of UAV flight research sites in Georgia and Virginia with an average point spacing that ranges from 0.1m to 0.6m. The methods are assessed using survey areas with geometrically heterogeneous ground structures: buildings, vegetation, power lines, and sub-meter structures such as road signs and guy wires. The 2.5D Maximum Elevation Box method is useful for simple structures. The 2.5D Ground Map Extrusion method efficiently encloses vegetation, but requires handdrawn ground footprints. The 3D Bounding Cylinder method excels at enclosing linear structures such as power lines and fences. The 3D Bounding Box method excels at enclosing planar structures such as buildings. The methods are compared on the basis of data compression and boundary fidelity on selected areas. The 2.5D methods yield the highest data compression but the polyhedra produced by them enclose significant amounts of empty space. Boundary fidelity is superior for the 3D methods, though this fidelity comes at the cost of a roughly thirtyfold lower data compression ratio than the 2.5D Maximum Elevation Box method. A mix of these output geometries is proposed for autonomous UAV navigation with limited on-board computing. Both the accuracy and spatial detail of emerging satellite-based survey technology lower than that of aerial lidar scanning survey technology. Sub-meter structures and thin linear structures are not reliably mapped at present by satellite-based surveys.

Moore, Andrew J.↗

GeoNEX: Land Monitoring from a New Generation of Geostationary Sensors

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

GeoNEX↗

Free Space Optical Link Utilizing a Modulated Retro-Reflector Intended for Planetary Duplex Communication Links Between an Orbiter and Surface Unit

Presented are simulation and experimental results that provide duplex optical-free space communication links with minimal power and pointing requirements by using a modulated retro-reflector (MRR) for planetary communications. The design is the MRR resides on the surface of a planet or moon, where energy is scarce, while the source of the communication laser resides on an orbiter to achieve satellite-to-ground communications. Also, a simulated scenario using the Mars Reconnaissance Orbiter (MRO) is provided for real world potential results. The information sent through this communication path can range from raw scientific data to multimedia files such as videos and pictures. Bidirectional communications is established with the MRR by using a nested pulse position modulation (PPM) structure. This modulation scheme is then evaluated for its validity in a proof-of-concept experiment. Initial results indicate a promising return-link performance of at least 300 kbps in the nested arrangement.

Booth, Stephanie↗

First Measurements of Ambient PM2.5 in Kinshasa, Democratic Republic of Congo and Brazzaville, Republic of Congo Using Field-calibrated Low-cost Sensors

Estimates of air pollution mortality in sub-Saharan Africa are limited by a lack of surface observations of fine particulate matter (PM2.5). Despite being large metropolises, Kinshasa, Democratic Republic of the Congo (DRC), population 14.3 million, and Brazzaville, Republic of the Congo (ROC), population 2.4 million, have no reference air pollution monitors at the time of writing. Recently, a few reference monitors have been deployed in other parts of sub-Saharan Africa, including Kampala, Uganda. A low-cost PurpleAir PM2.5 monitor was collocated next to the Kampala US Embassy BAM-1020 (Met One Beta Attenuation Monitor) starting in August 2019. Raw PurpleAir data are strongly correlated with the BAM (r(exp 2) = 0.88), but have a mean absolute error of approximately 14 μg/cu.m. Two calibration models, multiple linear regression and a random forest approach, decrease mean absolute error (MAE) from 14.3 μg/cu.m to 3.4 µg/cu.m or less and improve the the r(exp 2) from 0.88 to 0.96. Given )the similarity in climate and emissions in Kampala, we apply the collocated field correction factors to four PurpleAir sensors in Kinshasa, DRC and one in neighboring Brazzaville, ROC deployed beginning April 2018. Annual average PM2.5 for 2019 in Kinshasa is estimated at 43.5 µg/cu.m, more than 4 times higher than WHO Interim Target 1 of 10 µg/cu.m. Surface PM2.5 and aerosol optical depth were each about 40% lower during the 2020 COVID19 lockdown period compared to the same time period in 2019, which cannot be explained by changes in meteorology or wildfire emissions alone. Our results highlight the need for clean air solutions implementation in the Congo.

Celeste McFarlane↗

Event Selection and Background Rejection in Time Projection Chambers Using Convolutional Neural Networks and a Specific Application to the AdEPT Gamma-ray Polarimeter Mission

The Advanced Energetic Pair Telescope gamma-ray polarimeter uses a time projection chamber for measuring pair production events and is expected to generate a raw instrument data rate four orders of magnitude greater than is transmittable with typical satellite data communications. GammaNet, a convolutional neural network, proposes to solve this problem by performing event classification on-board for pair production and background events, reducing the data rate to a level that can be accommodated by typical satellite communication systems. In order to train GammaNet, a set of 1.1 × 10(exp 6) pair production events and 10(exp 6) background events were simulated for the Advanced Energetic Pair Telescope using the Geant4 Monte Carlo code. An additional set of 10(exp 6) pair production and 10 background events were simulated to test GammaNet’s capability for background discrimination. With optimization, GammaNet has achieved the proposed background rejection requirements for Galactic Cosmic Ray proton events. Given the best case assumption for downlink speeds, signal sensitivity for pair production ranged between 1.1 ± 0.5% to 69 ± 2% for 5 and 250 MeV incident gamma rays. This range became 0.1 ± 0.1% to 17 ± 2% for the worst case scenario of downlink speeds. The application of a feature visualization algorithm to GammaNet demonstrated decreased response to electronic noise and events exiting or entering the frame and increased response to parallel tracks that are close in proximity. GammaNet has been successfully implemented and shows promising results.

Richard L. Garnett↗

Post-Flight Assessment Review (PFAR): Advanced Colloids Experiment (ACE) ACE-T7-1,2

The objective of this PFAR is to: • Provide closure to ZIN DO-237 ACE-T7work and close NASA NPR 7123.1 requirements as listed in the SpaceDOC-II (S2) contract (the S2 CDRL DID No. PM-09 calls for a SEMP which refers backto NPR 7123.1) • Provide closure of SEMP (ZIN’s P40025) requirements for Technical Reviews • Provide plan to complete Informatics requirements. • Provide milestone closure to sponsoring organization. • Document property re-use and transfer decisions. • Transfer raw science data to the designated repository at MSFC. • Transfer required documents to Informatics • Opens an Informatics folder at MSFC to officially receive ACE-T7 information. • Capture open action items. • Create a formal presentation in configuration control. • Provide directions (in a Project Manager Report) how to contact the Project and Science teams through NASA when follow-on grants are awarded by Informatics.

microgravity↗

Growth Curve Parameterization of Metabolic Activity of Yeast Cells for BioSentinel

The goal of the BioSentinel small satellite payload is to measure the effect of deep space radiation on the growth and metabolic activity of yeast cells. Raw test data is generated by fluidics cards containing yeast cells rehydrated at different periods, with metabolic activity measured by the reduction of alamarBlue. Each card well has a sensor array that measures the amount of red, green, and infrared light transmitted through the yeast culture. This illumination data is then converted to absorbance values, which are further converted into concentrations. The ultimate objective is to convert these concentrations into biologically-relevant metrics that can be compared against one another to determine changes due to differential radiation exposure. Beginning with IR absorbance data (corresponding to cell density) from ground studies, three parameters from a sigmoidal growth curve were extracted and analyzed: 𝜆 (lag phase), 𝜇 (max growth rate), and A (max cell growth). The data was fit to the Gompertz model of microbial growth using non-linear regression (Minitab), as the fit error was reduced compared to the simpler logistic growth curve. Graphs showed that the data contained a discrepancy (drift) in the lag phase that is attributable to a slow, constant loss of moisture. Correcting this discrepancy by fitting the first 25 hours of the data to a power function and subtracting these values from the absorbance readings obtained a better statistical fit to the growth curve in the lag phase. A power fit was selected over a linear fit because it reflected the effects of constant volume loss. This correction to the BioSentinel data analysis pipeline will enable quantitative statistical analysis of the effect of different levels of deep space radiation on yeast cells. Future work includes automation of drift correction and curve modeling to extract these parameters directly from data.

Growth Curve↗

Enhancing accessibility and usability of Algorithm Theoretical Basis Documents through the Algorithm Publication Tool

Effective communication of scientific theories is crucial for transforming raw instrument data into valuable Earth observation products. The NASA Earth science data community disseminates this knowledge through Algorithm Theoretical Basis Documents (ATBDs). Historically, these documents lacked a standardized format, were designed for human readability rather than machine interpretation, and were challenging to locate due to the absence of a centralized repository. The Algorithm Publication Tool (APT) transforms how ATBD content is presented, simplifying the processes of creating, updating, and locating these documents. APT offers authors the option to use its user-friendly cloud-based interface or standardized templates for ATBD development. The primary advantage of the interface is its capability to manage the entire ATBD creation process within a single environment, ensuring comprehensive tracking of all activities and facilitating user tasks. Conversely, the use of standardized ATBD templates allows users to create documents using familiar tools like Google Docs, Microsoft Word, or Overleaf for LaTeX. APT also provides a centralized repository, enabling easy search and discovery of published ATBDs. This presentation showcases APT's functionalities, illustrates its contributions to advancing open science, and highlights potential benefits for broader community adoption.

Bradley Baker↗

EOS MLS Level 1B Data Processing, Version 2.2

A computer program performs level- 1B processing (the term 1B is explained below) of data from observations of the limb of the Earth by the Earth Observing System (EOS) Microwave Limb Sounder (MLS), which is an instrument aboard the Aura spacecraft. This software accepts, as input, the raw EOS MLS scientific and engineering data and the Aura spacecraft ephemeris and attitude data. Its output consists of calibrated instrument radiances and associated engineering and diagnostic data. [This software is one of several computer programs, denoted product generation executives (PGEs), for processing EOS MLS data. Starting from level 0 (representing the aforementioned raw data, the PGEs and their data products are denoted by alphanumeric labels (e.g., 1B and 2) that signify the successive stages of processing.] At the time of this reporting, this software is at version 2.2 and incorporates improvements over a prior version that make the code more robust, improve calibration, provide more diagnostic outputs, improve the interface with the Level 2 PGE, and effect a 15-percent reduction in file sizes by use of data compression.

Perun, Vincent↗

Charge-coupled device data processor for an airborne imaging radar system

Processing of raw analog echo data from synthetic aperture radar receiver into images on board an airborne radar platform is discussed. Processing is made feasible by utilizing charge-coupled devices (CCD). CCD circuits are utilized to perform input sampling, presumming, range correlation and azimuth correlation in the analog domain. These radar data processing functions are implemented for single-look or multiple-look imaging radar systems.

Arens, W. E.↗

Quantifying Pilot Visual Attention in Low Visibility Terminal Operations

Quantifying pilot visual behavior allows researchers to determine not only where a pilot is looking and when, but holds implications for specific behavioral tracking when these data are coupled with flight technical performance. Remote eye tracking systems have been integrated into simulators at NASA Langley with effectively no impact on the pilot environment. This paper discusses the installation and use of a remote eye tracking system. The data collection techniques from a complex human-in-the-loop (HITL) research experiment are discussed; especially, the data reduction algorithms and logic to transform raw eye tracking data into quantified visual behavior metrics, and analysis methods to interpret visual behavior. The findings suggest superior performance for Head-Up Display (HUD) and improved attentional behavior for Head-Down Display (HDD) implementations of Synthetic Vision System (SVS) technologies for low visibility terminal area operations. Keywords: eye tracking, flight deck, NextGen, human machine interface, aviation

Ellis, Kyle K.↗

Reliable Transport over SpaceWire for James Webb Space Telescope (JWST) Focal Plane Electronics (FPE) Network

NASA's James Webb Space Telescope (JWST) faces difficult technical and budgetary challenges to overcome before it is scheduled launch in 2010. The Integrated Science Instrument Module (ISIM), shares these challenges. The major challenge addressed in this paper is the data network used to collect, process, compresses and store Infrared data. A total of 114 Mbps of raw information must be collected from 19 sources and delivered to the two redundant data processing units across a twenty meter deployed thermally restricted interface. Further data must be transferred to the solid-state recorder and the spacecraft. The JWST detectors are kept at cryogenic temperatures to obtain the sensitivity necessary to measure faint energy sources. The Focal Plane Electronics (FPE) that sample the detector, generate packets from the samples, and transmit these packets to the processing electronics must dissipate little power in order to help keep the detectors at these cold temperatures. Separating the low powered front-end electronics from the higher-powered processing electronics, and using a simple high-speed protocol to transmit the detector data minimize the power dissipation near the detectors. Low Voltage Differential Signaling (LVDS) drivers were considered an obvious choice for physical layer because of their high speed and low power. The mechanical restriction on the number cables across the thermal interface force the Image packets to be concentrated upon two high-speed links. These links connect the many image packet sources, Focal Plane Electronics (FPE), located near the cryogenic detectors to the processing electronics on the spacecraft structure. From 12 to 10,000 seconds of raw data are processed to make up an image, various algorithms integrate the pixel data Loss of commands to configure the detectors as well as the loss of science data itself may cause inefficiency in the use of the telescope that are unacceptable given the high cost of the observatory. This combination of requirements necessitates a redundant, fault tolerant, high- speed, low mass, low power network with a low Bit error Rate(1E-9- 1E-12). The ISIM systems team performed many studies of the various network architectures that meeting these requirements. The architecture selected uses the Spacewire protocol, with the addition of a new transport and network layer added to implement end-to-end reliable transport. The network and reliable transport mechanism must be implemented in hardware because of the high average information rate and the restriction on the ability of the detectors to buffer data due to power and size restrictions. This network and transport mechanism was designed to be compatible with existing Spacewire links and routers so that existing equipment and designs may be leveraged upon. The transport layer specification is being coordinated with European Space Agency (ESA), Spacewire Working Group and the Consultative Committee for Space Data System (CCSDS) PlK Standard Onboard Interface (SOIF) panel, with the intent of developing a standard for reliable transport for Spacewire. Changes to the protocol presented are likely since negotiations are ongoing with these groups. A block of RTL VHDL that implements a multi-port Spacewire router with an external user interface will be developed and integrated with an existing Spacewire Link design. The external user interface will be the local interface that sources and sinks packets onto and off of the network (Figure 3). The external user interface implements the network and transport layer and handles acknowledgements and re-tries of packets for reliable transport over the network. Because the design is written in RTL, it may be ported to any technology but will initially be targeted to the new Actel Accelerator series (AX) part. Each link will run at 160 Mbps and the power will be about 0.165 Watt per link worst case in the Actel AX.

Rakow, Glenn↗

A technique for the reduction and analysis of ocean spectral data

Some initial investigations of a method of reducing and analyzing raw ocean spectral data are presented. The method avoids most problems associated with atmospheric effects, and requires the application of little, if any, calibration information to the data.

White, P. G.↗

A real time dynamic data acquisition and processing system for velocity, density, and total temperature fluctuation measurements

The real time Dynamic Data Acquisition and Processing System (DDAPS) is described which provides the capability for the simultaneous measurement of velocity, density, and total temperature fluctuations. The system of hardware and software is described in context of the wind tunnel environment. The DDAPS replaces both a recording mechanism and a separate data processing system. DDAPS receives input from hot wire anemometers. Amplifiers and filters condition the signals with computer controlled modules. The analog signals are simultaneously digitized and digitally recorded on disk. Automatic acquisition collects necessary calibration and environment data. Hot wire sensitivities are generated and applied to the hot wire data to compute fluctuations. The presentation of the raw and processed data is accomplished on demand. The interface to DDAPS is described along with the internal mechanisms of DDAPS. A summary of operations relevant to the use of the DDAPS is also provided.

Clukey, Steven J.↗

Data Format Standardization of Space Weather Model Output at the Community Coordinated Modeling Center

The disparate nature of space weather model output provides many challenges with regards to the portability and reuse of not only the data itself, but also any tools that are developed for analysis and visualization. We are developing and implementing a comprehensive data format standardization methodology that allows heterogeneous model output data to be stored uniformly in any common science data format. We will discuss our approach to identifying core meta-data elements that can be used to supplement raw model output data, thus creating self-descriptive files. The meta-data should also contain information describing the simulation grid. This will ultimately assists in the development of efficient data access tools capable of extracting data at any given point and time. We will also discuss our experiences standardizing the output of two global magnetospheric models, and how we plan to apply similar procedures when standardizing the output of the solar, heliospheric, and ionospheric models that are also currently hosted at the Community Coordinated Modeling Center.

Maddox, M.↗