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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Hyperspectral Remote Sensing and Ecological Modeling Research and Education at Mid America Remote Sensing Center (MARC): Field and Laboratory Enhancement

The purpose of this project was to establish a new hyperspectral remote sensing laboratory at the Mid-America Remote sensing Center (MARC), dedicated to in situ and laboratory measurements of environmental samples and to the manipulation, analysis, and storage of remotely sensed data for environmental monitoring and research in ecological modeling using hyperspectral remote sensing at MARC, one of three research facilities of the Center of Reservoir Research at Murray State University (MSU), a Kentucky Commonwealth Center of Excellence. The equipment purchased, a FieldSpec FR portable spectroradiometer and peripherals, and ENVI hyperspectral data processing software, allowed MARC to provide hands-on experience, education, and training for the students of the Department of Geosciences in quantitative remote sensing using hyperspectral data, Geographic Information System (GIS), digital image processing (DIP), computer, geological and geophysical mapping; to provide field support to the researchers and students collecting in situ and laboratory measurements of environmental data; to create a spectral library of the cover types and to establish a World Wide Web server to provide the spectral library to other academic, state and Federal institutions. Much of the research will soon be published in scientific journals. A World Wide Web page has been created at the web site of MARC. Results of this project are grouped in two categories, education and research accomplishments. The Principal Investigator (PI) modified remote sensing and DIP courses to introduce students to ii situ field spectra and laboratory remote sensing studies for environmental monitoring in the region by using the new equipment in the courses. The PI collected in situ measurements using the spectroradiometer for the ER-2 mission to Puerto Rico project for the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS). Currently MARC is mapping water quality in Kentucky Lake and vegetation in the Land-Between-the Lakes (LBL) using Landsat-TM data. A Landsat-TM scene of the same day was obtained to relate ground measurements to the satellite data. A spectral library has been created for overstory species in LBL. Some of the methods, such as NPDF and IDFD techniques for spectral unmixing and reduction of effects of shadows in classifications- comparison of hyperspectral classification techniques, and spectral nonlinear and linear unmixing techniques, are being tested using the laboratory.

Cetin, Haluk↗
DOE OSTI2021

Assessing the Consistency of Estimated Ground Cover Fractions between the BLM AIM Method and Optical Remote Sensing Method

Since 2012, Argonne National Laboratory (Argonne) has supported the Bureau of Land Management (BLM) in developing remote sensing methodologies for long-term environmental monitoring of Palo Verde Mesa in eastern Riverside County, California, including methods for: detailed mapping of ephemeral streams, estimating fractional cover of desert-land surface components (e.g., trees, shrubs, litters, and bare ground), evaluating erosion risk or land stability, and characterizing vegetation alliances using spatial structure and geostatistical approaches. These studies showed the promise of remote sensing for monitoring changes in desert landscapes by providing information that would be difficult to obtain through field surveys. During this time the BLM has also worked to establish long-term monitoring protocols and compiled field-observation data collected using standardized protocols from the Assessment, Inventory, and Monitoring (AIM) strategy. The AIM data can be compared to data derived from remote sensing methods to evaluate their relative operational utility in monitoring landscape change. If ground cover estimated using remotely sensed imagery is comparable to AIM ground cover estimates, then remote sensing can be used to monitor whether any land cover change in desert landscapes may be related to solar energy development. Therefore, the goal of this study was to determine the consistency in ground cover estimates between AIM data and those derived from publicly- available remotely sensed imagery, such as that available through the U.S. Department of Agriculture, National Agricultural Imagery Program (NAIP), to examine feasibility of a remote sensing method for complementing AIM monitoring. Based on the image analysis in this study, we also provide recommendations for how small unmanned aerial system (sUAS) data may be used to complement BLM’s AIM data and NAIP imagery for future vegetation monitoring. The ground cover types we originally planned to investigate were trees, shrubs, and bare ground. However, the small sample size and a limited range of cover fraction of trees and shrubs in the AIM dataset (e.g., 33 samples with a maximum shrub cover of 18%, 14 samples with a maximum tree cover of 17%) did not allow for performing a meaningful evaluation for the remote sensing approach. Therefore, we conducted the study focusing on bare ground, foliar, and rock cover, all of which are indicators reported in the AIM remote sensing dataset.

47 OTHER INSTRUMENTATION↗
NASA NTRS1995

Innovative Imaging Spectrometer Calibration Techniques

A laboratory calibration of the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) allowed experimentation with several innovative calibration techniques that would improve calibration accuracy, provide independent checks for systematic errors, and reduce the time required to collect a calibration data set.

remote sensing AVIRIS Airborne Visible Infrared Im↗
NASA NTRS2015

The Role of the NASA Global Hawk Link Module as an Information Nexus For Atmospheric Mapping Missions

The Link Module described in this paper was developed for the NASA Uninhabited Aerial System (UAS) Global Hawk Pacific Mission (GloPAC) Airborne Science Campaign; four flights of 30 hour duration, supporting the Aura Validation Experiment (AVE). It was used again during the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth Science field experiment to better understand how tropical storms form and develop into major hurricanes. In these missions, the Link Module negotiated all communication over the high bandwidth Ku satellite link, archived all the science data from onboard experiments in a spatially enabled database, routed command and control of the instruments from the Global Hawk Operations Center, and re-transmitted select data sets directly to experimenters control and analysis systems. The availability of aggregated information from collections of sensors, and remote control capabilities, in real-time, is revolutionizing the way Airborne Science is being conducted. The Link Module NG now being flown in support of the NASA Earth Venture missions, the Hurricane and Severe Storm Sentinel (HS3) mission, and Airborne Tropical Tropopause Experiment (A TTREX) mission, has advanced data fusion technologies that are further advancing the Scientific productivity, flexibility and robustness of these systems. On-the-fly traffic shaping has been developed to allow the high definition video, used for critical flight control segments, to dynamically allocate variable bandwidth on demand. Historically, the Link Module evolved from the instrument and communication interface controller used by NASA's Pathfinder and Pathfinder plus solar powered UAS's in the late 1990' s. It later was expanded for use in the AIRDAS four channel scanner flown on the NASA Altus UAS, and then again to a module in the AMS twelve channel multispectral scanner flying on the NASA (Predator-b) Ikhana UAS. The current system is the answer to the challenges imposed by extremely long duration UASs, with on-board multi-instrument (>= 12) Sensor Webs.

Hurricanes↗
DOE OSTI2021

Transportation Hub Infrastructure Expansion: Decision Support Under Uncertainty

The Athena project (www.athena-mobility.org) has worked to investigate the relationship between the Dallas-Fort Worth Airport (DFW) and the greater Dallas area in order to better understand and therefore better inform future decision-making regarding the critical infrastructure that influence mobility between the airport and the city. Through this work, infrastructure related to curbside pickup and drop-off, parking, public transit, and the road network congestion were identified as critical to the operation of the DFW transportation hub. The infrastructure analysis and expansion aspect of the Athena project is focused on the restructuring of the CTA curb as a hierarchical curb and the building or repurposing of parking infrastructure as the interplay between these two areas. Many sources of uncertainty exist that may impact future airport and transportation hub operations, such as passenger volume growth, population demographic changes over time, electric vehicle (EV) adoption rates, and autonomous vehicle (AV) adoption rates. Due to these sources of uncertainty, we have selected for our research a modeling framework that can capture various types of uncertainty and hedge against those uncertainties in the optimization process. We analyze road network and curb congestion, the rise of transportation networking companies, trends in parking usage, existing policies around this infrastructure, airport revenue streams, and other contributing factors to enable infrastructure decision making with less uncertainty. To accomplish this wholistic analysis, we have developed a novel multi-stage, multi-period stochastic optimization model which considers the airport's decisions from 2025-2045 under different possible future macro trajectories and day-to-day variations in operational conditions captured as "annual representation of operations" scenarios with respective probabilities. This model has also been designed to leverage the outputs of various efforts under the Athena project to create a combined decision framework for infrastructure decisions. These various efforts include the route optimization model, the ASPIRES simulation, the mode choice model, and the SUMO traffic simulation. Our computational experiments of this system at scale have resulted in a working version of our infrastructure model which enables the explicit representation and consideration of various sources of uncertainty in the decision process to enable robust, flexible decision-making. This model has been effectively run on NREL's HPC system, Eagle, with large numbers of stochastic scenarios and shows promise as a scalable tool for robust consideration of uncertainties in airport planning. We have tested our model using 30,240 operational circumstances in total, resulting in a problem with more 200 million variables. This model was solved in several different configurations, and a workflow to simulate the performance of the infrastructure model results was developed and deployed. In general, our results indicate that a combination of remote parking, remote curb infrastructure, and dynamic pricing can generate revenue, reduce emissions, accommodate emerging technologies such as AVs and EVs, and manage airport passenger growth over time. We note the success of the proposed strategy depends on the data collection and forecasting abilities of DFW. We have also seen that the AV adoption by TNCs might necessitate larger amounts of remote curb. The results of this work inform strategies for airport infrastructure decision making, as well as demonstrate the value of an adaptable model, but also indicate that there are avenues remaining where further research would be of value.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

HPC Campaign Management: Remote data access with user-defined error bound using ADIOS and ZFP

Remote access to large-scale scientific datasets, like those generated by combustion simulations or other high-performance computing (HPC) applications, presents a significant challenge. Downloading entire datasets is often impractical due to their size and the bandwidth limitations of typical networks. To address this challenge, we propose a novel approach that enables efficient remote access to large datasets distributed across multiple facilities. Our method enables technologies to download only the data values of a select variable, in a select region of interest, to a user-defined accuracy. For this purpose, we extended the ADIOS IO library to provide read functions with user-defined accuracy, a remote data server that understands multidimensional selections of specific variables, steps and accuracy from an ADIOS dataset, and which uses lossy compression on the remote site to reduce the data to be transferred back to the client. In addition, our extension of the ADIOS library collects metadata from multiple datasets in small files called Campaign Archives, which can be shared among project participants on any HPC, cloud or laptop, and which can easily facilitate the discovery of content and pointers to the data location as well as remote access to the data by local tools as if data was local. This feature called Campaign Management, enables a group of scientists to manage related datasets stored in multiple files, across multiple facilities as if it was in a single file/database. We demonstrate the effectiveness of our approach using a 1.5 TB dataset from the S3D combustion simulation on Frontier at the Oak Ridge Leadership Facility. Even a single variable from this dataset, at 64 GB, is too large to be processed on a standard laptop. We show two different reading patterns for 2D plots and 3D visualization, with careful settings that a scientist studying combustion data would do and show that running the same Python scripts on Frontier directly takes comparable time than running them on the local laptop with remote access to the data on Frontier.

Podhorszki, Norbert [ORNL] (ORCID:000000019647542X↗
DOE OSTI2021

Real-time and Autonomous Water Quality Monitoring System Based on Remotely Operated Vehicle

Existing water quality monitoring systems near hydropower facilities are limited by the lack of mobility of the sensors’ carrier platform. Most systems use a buoy, a mounting fixture attached to a solid structure, or a human worker, which significantly limits the selection of the sampling sites and poses safety risks during data collection and equipment maintenance. To improve on this technology, we developed an autonomous water quality monitoring system that can operate in dangerous water environments near hydropower facilities for water sampling at multiple locations. The goal is to enable safe, timely, and comprehensive water-quality data collection; maximize power generation revenue with improved operational control; and reduce Federal Energy Regulatory Commission and state water quality monitoring costs for compliance. The system incorporates a remotely operated vehicle as the mobile monitoring platform, a dissolved oxygen sensor for monitoring water quality, a tether management system for automatically winding the tether, a solar mobile docking platform for suppling power to the ROV, and a web-based graphical user interface for data post-processing and visualization. In addition, preliminary field research are presented to demonstrate the system capabilities.

Salalila, Aljon L.↗
NASA NTRS2012

An Information NEXUS: The NASA Global Hawk Link Module

The Link Module described in this paper was first developed for the NASA Global Hawk Pacific Mission (GloPAC), four flights of 30 hour duration, supporting the Aura Validation Experiment (AVE). Its second use was during the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth Science field experiment to better understand how tropical storms form and develop into major hurricanes. In these missions, the Link module negotiated all communication over the high bandwidth Ku satellite link, archived al the science data from onboard experiments in a spatially enable database, routed command and control of the instruments from the Global Hawk Operations Center, and retransmitted select data sets directly to experimenters control and analysis systems. The availability of aggregated information from collections of sensors, and remote control capabilities, in real-time, is revolutionizing the way Airborne Science is being conducted. Also described is the next generation Link Module now being designed and tested to support the NASA Earth Venture missions, the Hurricane and Severe Storm Sentinel (HS3) mission, and Airborne Tropical Tropopause Experiment (ATTREX) mission. Advanced data fusion technologies being developed will further advance the Scientific productivity, flexibility and robustness of these systems. Historically, the Link module evolved from the instrument and communication interface controller used by NASA's Pathfinder and Pathfinder plus solar powered UAS's in the late 1990's. It later was expanded for use in the AIRDAS four channel scanner flown on the NASA Altus UAS, and then again to a module in the AMS twelve channel multispectral scanner flying on the NASA (Predator-b) Ikhana UAS. The current system is the next step in the evolution, a multi board system packaged in a Curtiss Wright MIL-spec, flight qualified enclosure.

Remote Sensing↗
NASA NTRS1981

Remote sensing of total dry-matter accumulation in winter wheat

Red and photographic-infrared spectral data collected on 21 dates over the growing season with a hand-held radiometer were quantitatively correlated with total dry-matter accumulation in winter wheat. The spectral data were found to be highly related to vigor and condition of the plant canopy. Two periods of drought stress and subsequent recovery from it were readily apparent in the spectral data. Simple ratios of the spectral radiance data compensated for variations in solar intensities and, when integrated over the growing season, explained 79% of the variation in total above-ground accumulation of dry matter. A satellite system is proposed to provide large-area assessment of total dry accumulation or net primary production from terrestrial vegetation.

Tucker, C. J.↗
NASA NTRS1975

Studies of recognition with multitemporal remote sensor data

Characteristics of multitemporal data and their use in recognition processing were investigated. Principal emphasis was on satellite data collected by the LANDSAT multispectral scanner and on temporal changes throughout a growing season. The effects of spatial misregistration on recognition performance with multitemporal data were examined. A capability to compute probabilities of detection and false alarm was developed and used with simulated distributions for misregistered pixels. Wheat detection was found to be degraded and false alarms increased by misregistration effects. Multitemporal signature characteristics and multitemporal recognition processing were studied to gain insights into problems associated with this approach and possible improvements. Recognition performance with one multitemporal data set displayed marked improvements over results from single-time data.

Malila, W. A.↗
NASA NTRS2023

South Slough Water Resources: Monitoring Changes in Water Quality to Identify Stressors in Eelgrass Extent Throughout the Coos Estuary

The Coos estuary in Southern Oregon supports a variety of habitats, including eelgrass (Zostera marina) meadows. Eelgrass meadows provide shelter and sustenance to local and migratory wildlife, including commercially important fishes, and cultural resources to local communities. These ecosystem services establish eelgrass as an ecologically, economically, and culturally important resource. However, the extent and density of eelgrass meadows within this estuary have declined substantially since 2005, threatening the ecosystem services they provide. NASA DEVELOP partnered with the South Slough National Estuarine Research Reserve and the Confederated Tribes of the Coos, Lower Umpqua, and Siuslaw Indians’ Department of Natural Resources to generate time-series maps of the water quality conditions (chlorophyll-a, turbidity) and eelgrass extent in the Coos estuary from 2016 to 2023 to better understand the conditions driving eelgrass decline. The DEVELOP team used NASA Earth observations including Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, and the European Space Agency’s Sentinel-2 Multispectral Instrument (MSI) to generate these time-series maps. The team faced limitations in the feasibility of detecting eelgrass within the Coos Estuary, including spectral resolution, tidal phase, and turbidity. These limitations indicate additional in situ data collection will be necessary for accurate eelgrass assessment. Meanwhile, the team determined it is feasible to assess turbidity and chlorophyll-a within the Coos Estuary using remote satellite data. These tools enabled the research partners to assess water quality characteristics within the Coos Estuary at a greater spatial scale and may provide a method of inexpensive preliminary investigation of eelgrass meadow locations.

eelgrass↗
NASA NTRS1999

Enhancement of Capabilities in Hyperspectral and Radar Remote Sensing for Environmental Assessment and Monitoring

The University of Utah, Department of Geography has developed a research and instructional program in satellite remote sensing and image processing. The University requested funds for the purchase of software licenses, mass storage for massive hyperspectral imager data sets, upgrades for the central data server to handle the additional storage capacity, a spectroradiometer for field data collection. These purchases have been made. This equipment will support research in one of the newest and most rapidly expanding areas of remote sensing.

Hepner, George F.↗
NASA NTRS1973

Discrimination techniques employing both reflective and thermal multispectral signals

Recent improvements in remote sensor technology carry implications for data processing. Multispectral line scanners now exist that can collect data simultaneously and in registration in multiple channels at both reflective and thermal (emissive) wavelengths. Progress in dealing with two resultant recognition processing problems is discussed: (1) More channels mean higher processing costs; to combat these costs, a new and faster procedure for selecting subsets of channels has been developed. (2) Differences between thermal and reflective characteristics influence recognition processing; to illustrate the magnitude of these differences, some explanatory calculations are presented. Also introduced, is a different way to process multispectral scanner data, namely, radiation balance mapping and related procedures. Techniques and potentials are discussed and examples presented.

Malila, W. A.↗
NASA NTRS1979

Voyager program. Voyager 1 encounter at Jupiter, 5 March 1979

Highlights of Voyager 1 activity during the observatory and far-encounter phases are summarized. Daily sequence of events for the spacecraft during the period of greatest encounter activity (Feb. 26 through Mar. 7) the near-encounter phase is given. Times shown designate the time of signal reception at Deep Space Network stations. Events listed emphasize activities pertaining to the four remote sensing instruments on the scan platforms. However, the other 7 experiments will continuously collect data throughout the encounter period.

Source record↗
NASA NTRS1984

Utilization of vegetation indices to improve microwave soil moisture estimates over agricultural lands

A technique is presented by means of which visible/near-IR data are used to develop corrections in remotely sensed microwave soil moisture signals, in order to account for vegetation effects. Visible/IR data collected with the NASA NS001 Thematic Mapper Simulator were used to calculate the Perpendicular Vegetation Index (PVI), which was then related to the change of sensitivity of the microwave measurement to surface soil moisture. Effective estimation of soil moisture in the presence of vegetation can be made with L-band microwave radiometers and visible/IR sensors when the PVI is lower than 4.3. This technique offers a means for the estimation of moisture from a space platform over many agricultural areas, without expensive ground data collection.

Theis, S. W.↗
NASA NTRS1985

Activities of the Pilot Land Data System project

The University of Maryland's Remote Sensing Systems Laboratory submitted to NASA/Goddard an interim progress report on the work being conducted within its Pilot Land Data System IPLDS project. The Remote Sensing Systems Laboratory addressed the following tasks: (1) identify data types and data sources needed to describe the selected test sites in collaboration with Goddard's Hydrological Sciences Branch; (2) define the procedures necessary to access/acquire this data; (3) conduct meetings with the PLDS Systems Engineering Group to identify functional specification priorities for PLDS development; (4) assemble documentation on historical remotely sensed imagery and transfer of such information to the PLDS Data Management Group; (5) collect data identified by Goodard's Hydrological Sciences Branch for data set inventory in PLD; (6) develop a Workstation-PLDS system interface over high speed lines, (7) develop and test through a Phase 1 demonstration of a micro workstation to access PLDS; and (8) establish interdepartmental agreement of development of computer link for electronic access of water resources data from USGS.

Sircar, J. K.↗
NASA NTRS1990

Autonomous Martian flying rover

A remotely programmable, autonomous flying rover is proposed to extensively survey the Martian surface environment. A Mach .3, solar powered, modified flying wing could cover roughly a 2000 mile range during Martian daylight hours. Multiple craft launched from an orbiting mother ship could provide near-global coverage. Each craft is envisioned to fly at about 1 km above the surface and measure atmospheric composition, pressure and temperature, map surface topography, and remotely penetrate the near subsurface looking for water (ice) and perhaps evidence of life. Data collected are relayed to Earth via the orbiting mother ship. Near surface guidance and control capability is an adaptation of current cruise missile technology. A solar powered aircraft designed to fly in the low temperature, low density, carbon dioxide Martian atmosphere near the surface appears feasible.

Source record↗
NASA NTRS1993

Space Applications Industrial Laser System (SAILS)

A program is underway to develop a YAG laser based materials processing workstation to fly in the cargo bay of the Space Shuttle. This workstation, called Space Applications Industrial Laser System (SAILS), will be capable of cutting and welding steel, aluminum, and Inconel alloys of the type planned for use in constructing the Space Station Freedom. As well as demonstrating the ability of a YAG laser to perform remote (fiber-optic delivered) repair and fabrication operations in space, fundamental data will be collected on these interactions for comparison with terrestrial data and models. The flight system, scheduled to fly in 1996, will be constructed as three modules using standard Get-Away-Special (GAS) canisters. The first module holds the laser head and cooling system, while the second contains a high peak power electrical supply. The third module houses the materials processing workstation and the command and data acquisition subsystems. The laser head and workstation cansisters are linked by a fiber-optic cable to transmit the laser light. The team assembled to carry out this project includes Lumonics Industrial Products (laser), Tennessee Technological University (structural analysis and fabrication), Auburn University Center for Space Power (electrical engineering), University of Waterloo (low-g laser process consulting), and CSTAR/UTSI (data acquisition, control, software, integration, experiment design). This report describes the SAILS program and highlights recent activities undertaken at CSTAR.

Mccay, T. D.↗