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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Measuring and Modeling Shared Visual Attention

Multi-person teams are sometimes responsible for critical tasks, such as flying an airliner. Here we present a method using gaze tracking data to assess shared visual attention, a term we use to describe the situation where team members are attending to a common set of elements in the environment. Gaze data are quantized with respect to a set of N areas of interest (AOIs); these are then used to construct a time series of N dimensional vectors, with each vector component representing one of the AOIs, all set to 0 except for the component corresponding to the currently fixated AOI, which is set to 1. The resulting sequence of vectors can be averaged in time, with the result that each vector component represents the proportion of time that the corresponding AOI was fixated within the given time interval. We present two methods for comparing sequences of this sort, one based on computing the time-varying correlation of the averaged vectors, and another based on a chi-square test testing the hypothesis that the observed gaze proportions are drawn from identical probability distributions. We have evaluated the method using synthetic data sets, in which the behavior was modeled as a series of "activities," each of which was modeled as a first-order Markov process. By tabulating distributions for pairs of identical and disparate activities, we are able to perform a receiver operating characteristic (ROC) analysis, allowing us to choose appropriate criteria and estimate error rates. We have applied the methods to data from airline crews, collected in a high-fidelity flight simulator (Haslbeck, Gontar & Schubert, 2014). We conclude by considering the problem of automatic (blind) discovery of activities, using methods developed for text analysis.

attention↗
NASA NTRS2000

BOREAS RSS-15 SIR-C and Landsat TM Biomass and Landcover Maps of the NSA

As part of BOREAS, the RSS-15 team conducted an investigation using SIR-C, X-SAR, and Landsat TM data for estimating total above-ground dry biomass for the SSA and NSA modeling grids and component biomass for the SSA. Relationships of backscatter to total biomass and total biomass to foliage, branch, and bole biomass were used to estimate biomass density across the landscape. The procedure involved image classification with SAR and Landsat TM data and development of simple mapping techniques using combinations of SAR channels. For the SSA, the SIR-C data used were acquired on 06-Oct-1994, and the Landsat TM data used were acquired on 02-Sep-1995. The maps of the NSA were developed from SIR-C data acquired on 13-Apr-1994. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2018

Improving AIRS NRT Imagery for the Enhancement of Visualization Services in LANCE

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of processing, archiving, and distribution services for data from the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002. AIRS provides data enabling global observations of the atmospheric state. The GES DISC provides service to both AIRS standard products and Near Real-time (NRT) products. The AIRS NRT product is one important element in the Land, Atmosphere Near real-time Capability for EOS (LANCE). The LANCE processing of the AIRS NRT product and the generation of the imagery are performed at the GES DISC. The AIRS NRT imagery are generated by mosaicking and mapping the available AIRS 6-minute retrieval granules to a global cylindrical projection. The images are constantly refreshed when new granules are produced. The AIRS NRT Viewer and LANCE Worldview provide visualization services to online users for AIRS NRT imagery. The imagery include atmospheric temperature, humidity, precipitation, Dust Score, CO, and SO2. The AIRS Applications Development Team at NASA JPL developed a new orbit-based algorithm and software to improve the AIRS NRT imagery. The GES DISC is collaborating with the AIRS Applications Development Team for the implementation of the new algorithm and software. The improvements include image quality, new color palettes, and variable changes. In this presentation, we will detail the improvements and demonstrate visualization of the new imagery.

Ding, Feng↗
NASA NTRS2020

Fisher's Peak Ecological Forecasting: Mapping Biomass to Inform Conservation Planning of a Future State Park in Southern Colorado

Fisher’s Peak is a 77.5 km2 property southeast of Trinidad, Colorado that is planned to become Colorado’s newest state park. The area has experienced limited anthropogenic disturbance and is home to an abundance of unique habitats and species. A rapid, approximately 900 m change in elevation over the extent of the area nurtures a variety of plants and animals, including the endangered New Mexico meadow jumping mouse. In 2019, the State of Colorado obtained Fisher’s Peak with plans to make it Colorado’s second largest state park. A diverse group of collaborators, including the Colorado State Forest Service and The Nature Conservancy, worked closely to design the state park to maximize recreation opportunity while conserving the property’s rich habitats and biodiversity. The Fisher’s Peak Ecological Forecasting Team utilized Light Detection and Ranging (LiDAR) surveys, in situ forest inventory data, and Earth observations from Landsat8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Sentinel-2 Multispectral Instrument (MSI), Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and the Shuttle Radar Topography Mission (SRTM) to quantify and map biomass over the extent of the study area. The results from modeling biomass had an out-of-bag root mean square error of 55 Mg/ha and an R2 of 12. The resulting map indicates areas where carbon storage on the property is high, informing decision-making processes for future park development. While more in situ training data may improve modeling capacity for biomass in the Fisher’s Peak area, this work represents a feasible attempt to better understand biomass distribution using earth observation.

DEVELOP Tech Paper↗
NASA NTRS2000

BOREAS HYD-9 Hourly and Daily Rainfall Maps for the Southern Study Area

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-9 team collected data on precipitation and streamflow over portions of the Northern Study Area (NSA) and Southern Study Area (SSA). This data set contains Cartesian maps of rain accumulation for one-hour and daily periods during the summer of 1994 over the SSA only (not the full view of the radar). A parallel set of one-hour maps for the whole radar view has been prepared and is available upon request from the HYD-09 personnel. An incidental benefit of the areal selection was the elimination of some of the less accurate data, because for various reasons the radar rain estimates degrade considerably outside a range of about 100 km. The data are available in tabular ASCII files. The HYD-09 hourly and daily radar rainfall maps for the SSA are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Eley, F. Joe↗
NASA NTRS2007

NIRSS Upgrades: Final Report

This year we were able to further the NIRSS program by re-writing the data ingest and display code from LabVIEW to C++ and Java. This was leveraged by a University of Colorado Computer Science Department Senior Project. The upgrade made the display more portable and upgradeable. Comparisons with research aircraft flights conducted during AIRS-2 were also done and demonstrate reasonable skill in determining cloud altitudes and liquid water distribution. Improvements can still be made to the cloud and liquid logic. The icing hazard index was not evaluated here since that represents work in progress and needs to be made compatible with the new CIP-Severity algorithm. CIP is the Current Icing Potential product that uses a combination decision tree/fuzzy logic algorithm to combine numerical weather model output with operational sensor data (NEXRAD, GOES, METARs and voice pilot reports) to produce an hourly icing diagnosis across the CONUS. The new severity algorithm seeks to diagnose liquid water production through rising, cooling air, and depletion by ice processes. The information used by CIP is very different from that ingested by NIRSS but some common ground does exist. Additionally, the role of NIRSS and the information it both needs and provides needs to be determined in context of the Next Generation Air Traffic System (NGATS). The Weather Integrated Products Team has a plan for an Initial Operating Capability (IOC) to take place in 2012. NIRSS is not explicitly a part of that IOC but should be considered as a follow-on as part of the development path to a 2025 full capability.

Politovich, Marcia K.↗
NASA NTRS2020

Fisher's Peak Ecological Forecasting - Mapping Biomass to Inform Conservation Planning of a Future State Park in Southern Colorado

Fisher’s Peak is a 77.5 km2 property southeast of Trinidad, Colorado that is planned to become Colorado’s newest state park. The area has experienced limited anthropogenic disturbance and is home to an abundance of unique habitats and species. A rapid, approximately 900 m change in elevation over the extent of the area nurtures a variety of plants and animals, including the endangered New Mexico meadow jumping mouse. In 2019, the State of Colorado obtained Fisher’s Peak with plans to make it Colorado’s second largest state park. A diverse group of collaborators, including the Colorado State Forest Service and The Nature Conservancy, worked closely to design the state park to maximize recreation opportunity while conserving the property’s rich habitats and biodiversity. The Fisher’s Peak Ecological Forecasting Team utilized Light Detection and Ranging (LiDAR) surveys, in situ forest inventory data, and Earth observations from Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Sentinel-2 Multispectral Instrument (MSI), Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and the Shuttle Radar Topography Mission (SRTM) to quantify and map biomass over the extent of the study area. The results from modeling biomass had an out-of-bag root mean square error of 55 Mg/ha and an R2 of 12. The resulting map indicates areas where carbon storage on the property is high, informing decision-making processes for future park development. While more in situ training data may improve modeling capacity for biomass in the Fisher’s Peak area, this work represents a feasible attempt to better understand biomass distribution using earth observation

Lauren Lad↗
NASA NTRS2000

BOREAS HYD-8 1996 Gravimetric Moss Moisture Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-8 team made measurements of surface hydrological processes that were collected at the southern study area-Old Black Spruce (SSA-OBS) Tower Flux site in 1996 to support its research into point hydrological processes and the spatial variation of these processes. Data collected may be useful in characterizing canopy interception, drip, throughfall, moss interception, drainage, evaporation, and capacity during the growing season at daily temporal resolution. This particular data set contains the gravimetric moss moisture measurements from July to August 1996. To collect these data, a nested spatial sampling plan was implemented to support research into spatial variations of the measured hydrological processes and ultimately the impact of these variations on modeled carbon and water budgets. These data are stored in ASCII text files. The HYD-08 1996 gravimetric moss moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Fernandes, Richard↗
NASA NTRS2005

Space Technologies for Enhancing the Resilience and Sustainability of Indigenous Reindeer Husbandry in the Russian Arctic

To adapt successfully to the major changes - climate, environment, economic, social and industrial - which have taken place across the Arctic. in recent years, indigenous communities such as reindeer herders must become increasingly empowered with the best available technologies to add to their storehouse of traditional knowledge. Remotely-sensed data and observations are providing increased capabilities for monitoring, risk mapping, and surveillance of parameters critical to the characterization of pasture quality and migratory routes, such as vegetation distribution, snow cover, infrastructure development, and pasture damages due to fires. This paper describes a series of remote sensing capabilities, which are useful to reindeer husbandry, and gives the results of the first year of a project, "Reindeer Mapper", which is a remote sensing and GIs-based system to bring together space technologies with indigenous knowledge for sustainable reindeer husbandry in the Russian Arctic. In this project, reindeer herders and scientists are joining together to utilize technologies to create a system for collecting and sharing space-based and indigenous knowledge in the Russian Arctic. The "Reindeer Mapper" system will help make technologies more readily available to the herder community for observing, data collection and analysis, monitoring, sharing, communications, and dissemination of information - to be integrated with traditional, local knowledge. This paper describes some of the technologies which comprise the system including an intranet system to enable to the team members to work together and share information electronically, remote sensing data for monitoring environmental parameters important to reindeer husbandry (e.g., SAR, Landsat, AVHRR, MODIS), indigenous knowledge about important environmental parameters, acquisition of ground- based measurements, and the integration of all useful data sets for more informed decision-making.

Maynard, Nancy G.↗
NASA NTRS2022

Peru Health and Air Quality II: Leveraging Earth Observations and Health Data to Map Outbreak Risk and Inform Public Health Interventions for Zoonotic Disease Prevention

Peru's Madre de Dios region is a hotspot for dengue fever and leishmaniasis due to its tropical Amazonian climate. Though treatable, these zoonotic diseases are debilitating for under-resourced communities whose already close proximity to mosquito and sandfly vectors continues to increase via rapid urbanization and deforestation. Peru’s Ministries of Health (MINSA) and Environment (MINAM) are working to better understand the environmental factors amplifying the risk of dengue fever and leishmaniasis transmission. The first term of this project classified the land use and land cover of Madre de Dios’ 11 districts for 2010, 2015, and 2020 and identified a correlation between both diseases and urbanization. Our team expanded this analysis by creating urban-forest edge maps and incorporating climatic and topographic variables with data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), the Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG), and the Shuttle Radar Topography Mission (SRTM). We determined these variables’ impacts on disease incidence by assessing existing literature and running regression models. Dengue fever correlated with urban-forest edge, urban area, slope, temperature, and precipitation. Leishmaniasis primarily correlated with forest-edge area and elevation, but lacking additional statistical significance prevented further work, a decision supported by the literature. Thus, the risk matrix and risk map which we scripted in R to visualize the risk of disease posed to districts alongside health post locations addresses only dengue fever. The results and products will inform MINSA and MINAM in public health interventions, resource distribution, and policy initiatives.

Jennifer Rogers↗
NASA NTRS2000

BOREAS RSS-18 Level-1B AVIRIS Imagery: At-Sensor Radiance in BIL Format

These data were collected and processed by the BOREAS RSS-18 team at NASA JPL. Data were acquired for BOREAS with NASA's AVIRIS. This optical sensor measures images that consist of spectra from 400 to 2500 nm at 10-nm sampling. These spectra are acquired as images with 20-meter spatial resolution, 11-km swath width and up to 800-km length. The measurements are spectrally, radiometrically, and geometrically calibrated. Spatially, the data are focused on the BOREAS NSA and SSA near Thompson, Manitoba, and Candle Lake, Saskatchewan, Canada, respectively. AVIRIS data were collected in 1994 during the Thaw campaign at the NSA and SSA, at the SSA in IFC-1, and at the NSA and SSA in both IFC-2 and IFC-3. In 1996, AVIRIS was deployed in the winter and summer campaigns in the SSA only. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Newcomer, Jeffrey A.↗
NASA NTRS2006

Comparison of Communication Architectures for Spacecraft Modular Avionics Systems

This document is a survey of publicly available information concerning serial communication architectures used, or proposed to be used, in aeronautic and aerospace applications. It focuses on serial communication architectures that are suitable for low-latency or real-time communication between physically distributed nodes in a system. Candidates for the study have either extensive deployment in the field, or appear to be viable for near-term deployment. Eleven different serial communication architectures are considered, and a brief description of each is given with the salient features summarized in a table in appendix A. This survey is a product of the Propulsion High Impact Avionics Technology (PHIAT) Project at NASA Marshall Space Flight Center (MSFC). PHIAT was originally funded under the Next Generation Launch Technology (NGLT) Program to develop avionics technologies for control of next generation reusable rocket engines. After the announcement of the Space Exploration Initiative, the scope of the project was expanded to include vehicle systems control for human and robotics missions. As such, a section is included presenting the rationale used for selection of a time-triggered architecture for implementation of the avionics demonstration hardware developed by the project team

Gwaltney, D. A.↗
NASA NTRS2000

BOREAS HYD-8 1994 Gravimetric Moss Moisture Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-8 team made measurements of surface hydrological processes that were collected at the Northern Study Area-Old Black Spruce (NSA-OBS) Tower Flux site in 1994 and at Joey Lake, Manitoba, to support its research into point hydrological processes and the spatial variation of these processes. The data collected may be useful in characterizing canopy interception, drip, throughfall, moss interception, drainage, evaporation, and capacity during the growing season at daily temporal resolution. This particular data set contains the gravimetric moss moisture measurements from June to September 1994. A nested spatial sampling plan was implemented to support research into spatial variations of the measured hydrological processes and ultimately the impact of these variations on modeled carbon and water budgets. These data are stored in tabular ASCII files. The HYD-08 1994 gravimetric moss moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Wang, Xuewen↗
NASA NTRS2000

BOREAS Landsat MSS Imagery: Digital Counts

The Boreal Ecosystem-Atmospheric Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. The Earth Resources Technology Satellite (ERTS) Program launched the first of a series of satellites (ERTS-1) in 1972. Part of the NASA Earth Resources Survey Program, the ERTS Program and the ERTS satellites were later renamed Landsat to better represent the civil satellite program's prime emphasis on remote sensing of land resources. Landsat satellites 1 through 5 carry the Multispectral Scanner (MSS) sensor. Canada for Remote Sensing (CCRS) and BOREAS personnel gathered a set of MSS images of the BOREAS region from Landsat satellites 1, 2, 4, and 5 covering the dates of 21 Aug 1972 to 05 Sep 1988. The data are provided in binary image format files of various formats. The Landsat MSS imagery is available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRSDate not supplied

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the predictive simulation capability, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper will present the status of implementing and maturing particle-particle interaction constituent physics models essential in simulating the landing surface granular material flow under PSI effects. This gas-particle multi-phase interaction modeling of plume impingement flow on the extra-terrestrial soil material is performed with the Gas-Granular Flow Solver (GGFS) addressed in a companion paper. The response of regolith particle flow induced by lander PSI requires accurate representation of the regolith granular material fluidic behavior and gas-granular interactions. The lunar regolith, as the extreme example, is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking particle shapes for the very jagged particles. The combination of particle shape and size distribution has been identified as major drivers in the complex particle flow response and resulting crater shape characteristics of extraterrestrial granular material. Constituent models for spherical particles can be formulated directly from particle kinetics theory. Complex particle shapes can be modeled by gluing together elemental spherical shapes into composite particles, requiring a Discrete Element Model (DEM) particle kinetics modeling approach to extract data and formulate constituent models. Mixture constituent models for poly-disperse mixtures (i.e, containing distribution of particle sizes) have recently been developed. The required non-spherical particle mixture granular material response closure models are then obtained through small-scale unit physics DEM simulations for the range of particle shapes, mixtures and packing densities. The granular material response closure models are then implemented in the Eulerian granular flow formulation. This DEM-based constituent model extraction process and formulation of poly-disperse particle mixtures has been successfully developed by small business and academic partners in the development of the Gas-Granular Flow Solver (GGFS) simulation program simulation framework. The currently implemented capabilities have reached the capability level of modeling bi-disperse, non-spherical particle mixtures is being continuously extended towards computational modeling of full range irregular particle mixtures. Under the GCD project, this technology is being further developed, transferred to NASA analysts, and matured towards application readiness. The predictive simulation capability team under the GCD project has acquired the modeling tools and processes of the DEM based constituent model formulation from the GGFS development team and is developing the capability to replicate the existing process. This is the first important step towards the ability of the NASA team to independently perform such model development in a production setting. Further efforts are underway to migrate the DEM based model simulation process performed with the academic based tools to more capable Open Source, highly parallelized simulation tools for efficient operation on NASA HPC assets. Evaluation of the currently implemented (such as mono-disperse and bi-disperse spherical and irregular shape particle constituent model applications) and continuously evolving full-range particle physics models in the GGFS tool is performed by the NASA team to advance application readiness of the simulations. Application testing for complex PSI erosions and cratering scenarios such as the Apollo LM is performed for axi-symmetric and full 3D simulations to aid the tool developers in achieving practical application readiness for NASA projects. Important validation and application testing will further be performed against experimental data generated under the GCD PSI project experimental component.

Peter A Liever↗
NASA NTRS2000

BOREAS RSS-14 Level-2 GOES-7 Shortwave and Longwave Radiation Images

The BOREAS RSS-14 team collected and processed several GOES-7 and GOES-8 image data sets that covered the BOREAS study region. This data set contains images of shortwave and longwave radiation at the surface and top of the atmosphere derived from collected GOES-7 data. The data cover the time period of 05-Feb-1994 to 20-Sep-1994. The images missing from the temporal series were zero-filled to create a consistent sequence of files. The data are stored in binary image format files. Due to the large size of the images, the level-1a GOES-7 data are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of what data were collected. The level-1a GOES-7 image data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). See sections 15 and 16 for more information. The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗
NASA NTRS2000

BOREAS HYD-8 Throughfall Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-8 team made measurements of surface hydrological processes at the Southern Study Area (SSA) and Northern Study Area (NSA) Old Black Spruce (OBS) Tower Flux sites, supporting its research into point hydrological processes and the spatial variation of these processes. These data were collected during the 1994 and 1996 field campaigns. Data collected may be useful in characterizing canopy interception, drip, throughfall, moss interception, drainage, evaporation, and capacity during the growing season at daily temporal resolution. This particular data set contains the measurements of throughfall, which is the amount of precipitation that fell through the canopy. A nested spatial sampling plan was implemented to determine spatial variations of the measured hydrological processes and ultimately the impact of these variations on modeled carbon and water budgets. These data are stored in ASCII text files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Wang, Xue-Wen↗
NASA NTRS2000

BOREAS HYD-6 Aircraft Gamma Ray Soil Moisture Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-6 team collected several data sets related to the moisture content of soil and overlying humus layers. This data set contains percent soil moisture (by weight) (and/or water content if there is a moss/humus layer) measured from aircraft using a terrestrial gamma ray instrument. There are also data that indicate the location of the aircraft at the time it collected the terrestrial gamma ray data for the various flight lines and bins. The location information contains a list of coordinates that indicate the path of the aircraft for each bin. The data were collected during four time periods from September 1993 to September 1994 over the southern study area (SSA) and two time periods from February to August 1994 over the northern study area (NSA). The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Peck, Eugene L.↗