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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Remote sensing programs and courses in engineering and water resources

The content of typical basic and advanced remote sensing and image interpretation courses are described and typical remote sensing graduate programs of study in civil engineering and in interdisciplinary environmental remote sensing and water resources management programs are outlined. Ideally, graduate programs with an emphasis on remote sensing and image interpretation should be built around a core of five courses: (1) a basic course in fundamentals of remote sensing upon which the more specialized advanced remote sensing courses can build; (2) a course dealing with visual image interpretation; (3) a course dealing with quantitative (computer-based) image interpretation; (4) a basic photogrammetry course; and (5) a basic surveying course. These five courses comprise up to one-half of the course work required for the M.S. degree. The nature of other course work and thesis requirements vary greatly, depending on the department in which the degree is being awarded.

Kiefer, R. W.↗
NASA NTRSDate not supplied

WET Water Resources: A Google Earth Engine Python API Tool to Automate Wetland Extent Mapping Using Radar Satellite Sensors for Wetland Management and Monitoring

Wetland ecosystems are annually or seasonally wet transition zones between land and water. They provide a range of ecosystem services such as water filtration, flood mitigation, and carbon sequestration, as well as hosting biodiversity hotspots. Although they fulfill fundamental physical and natural processes, wetland extent and health are threatened by anthropogenic influences related to urbanization, population increase, pollution, and climate change. Recognizing the need to quantitatively monitor changes in these recently threatened ecosystems in a timely and cost-effective way, we developed a Google Earth Engine (GEE) Python API tool for automated wetland extent mapping using optical and radar satellite sensors that can be applied globally. The tool will significantly improve wetland change analysis and monitoring as the optical and SAR data proves high resolution (5-10 m) imagery, and SAR data is unaffected by cloud cover and light availability (day vs. night), which are common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a MODIS snow mask product to mask global snow coverage, which would affect land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd watershed located in central Sudan. The tool was the first of its kind, as it enables NISAR data processing through an open-source GEE repository, further expanding and improving the utility of NASA Earth observations and contributing to NASA Open Science initiatives. We anticipate the tool will be used by researchers and practitioners interested in wetland monitoring and management..

Lori Berberian↗
NASA NTRS2023

WET Water Resources: A Google Earth Engine Python API Tool to Automate Wetland Extent Mapping Using Radar Satellite Sensors for Wetland Management and Monitoring

Wetland ecosystems are annually or seasonally wet transition zones between land and water. They provide a range of ecosystem services such as water filtration, flood mitigation, and carbon sequestration, as well as hosting biodiversity hotspots. Although they fulfill fundamental physical and natural processes, wetland extent and health are threatened by anthropogenic influences related to urbanization, population increase, pollution, and climate change. Recognizing the need to quantitatively monitor changes in these recently threatened ecosystems in a timely and cost-effective way, we developed a Google Earth Engine (GEE) Python API tool for automated wetland extent mapping using optical and radar satellite sensors that can be applied globally. The tool will significantly improve wetland change analysis and monitoring as SAR data provides high resolution (5-10 m) imagery, unaffected by cloud cover and light availability (day vs. night), common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band (once operational and available on the GEE repository) synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a Terra Moderate Resolution Imaging Spectroradiometer (MODIS) snow product to determine regional snow coverage, which affects land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd wetland located in central Sudan. The tool was the first of its kind, as it enables NISAR data processing through an open-source GEE repository, further expanding and improving the utility of NASA Earth observations and contributing to NASA Open Science initiatives. We anticipate the tool will be used by researchers and practitioners interested in wetland monitoring and management.

Inundation↗
NASA NTRS1978

A manual for inexpensive methods of analyzing and utilizing remote sensor data

Instructions are provided for inexpensive methods of using remote sensor data to assist in the completion of the need to observe the earth's surface. When possible, relative costs were included. Equipment need for analysis of remote sensor data is described, and methods of use of these equipment items are included, as well as advantages and disadvantages of the use of individual items. Interpretation and analysis of stereo photos and the interpretation of typical patterns such as tone and texture, landcover, drainage, and erosional form are described. Similar treatment is given to monoscopic image interpretation, including LANDSAT MSS data. Enhancement techniques are detailed with respect to their application and simple techniques of creating an enhanced data item. Techniques described include additive and subtractive (Diazo processes) color techniques and enlargement of photos or images. Applications of these processes, including mappings of land resources, engineering soils, geology, water resources, environmental conditions, and crops and/or vegetation, are outlined.

Elifrits, C. D.↗
NASA NTRS1976

Water resources planning for rivers draining into Mobile Bay

The application of remote sensing, automatic data processing, modeling and other aerospace related technologies to hydrological engineering and water resource management are discussed for the entire river drainage system which feeds the Mobile Bay estuary. The adaptation and implementation of existing mathematical modeling methods are investigated for the purpose of describing the behavior of Mobile Bay. Of particular importance are the interactions that system variables such as river flow rate, wind direction and speed, and tidal state have on the water movement and quality within the bay system.

April, G. C.↗
NASA NTRS2020

Great Lakes Water Resources II: A Google Earth Engine Tool to Automate Wetland Extent Mapping Using Optical and Radar Satellite Sensors in the Great Lakes Basin for Wetland Management and Monitoring

The Great Lakes Basin is one of the world’s largest freshwater ecosystems. The Basin harbors over 200,000 acres of wetlands that provide a variety of environmental, ecological, and recreational functions to over 30 million people in the region. Some of these functions include improving water quality, mitigating flood impacts, providing wildlife habitat, and housing recreational activities. However, due to anthropogenic activities, habitat conversion and degradation threaten to disrupt or destroy remaining wetland ecosystems. Maps of wetland distribution based on ground surveys are costly and labor-intensive, prohibiting timely evaluations of wetland loss and gain. The Great Lakes Water Resources II team at the NASA Jet Propulsion Laboratory developed the Wetlands Extent Tool 2.0 (WET 2.0) in Google Earth Engine to automate mapping of wetland distribution in the Great Lakes Basin. The team partnered with the US Fish and Wildlife Service, Environmental Protection Agency, Minnesota Department of Natural Resources, the National Oceanic and Atmospheric Administration, and Ducks Unlimited. WET 2.0 incorporates Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) data. Utilizing a Random Forest classifier, WET 2.0 is capable of automatically mapping wetland extent in the entire Great Lakes Basin, achieving a mean overall accuracy of 80.12% when tested in Michigan.Findings and maps produced by WET 2.0 will enable our partners to identify areas of ecosystem degradation and wetland destruction in order to enact environmental practices and policy initiatives to maintain environmental and economic health in the area.

Water Resources↗
NASA NTRS2020

Great Lakes Water Resources II: A Google Earth Engine Tool to Automate Wetland Mapping Using Optical and Radar Satellite Sensors in the Great Lakes Basin for Wetland Management and Monitoring

The Great Lakes Basin is one of the world’s largest freshwater ecosystems. The Basin harbors over 200,000 acres of wetlands. These wetlands provide a variety of environmental, ecological, and recreational functions to over 30 million people in the region. Some of these functions include improving water quality, mitigating flood impacts, providing wildlife habitat, and housing recreational activities. However, due to anthropogenic activities, habitat conversion and degradation threaten to disrupt or destroy remaining wetland ecosystems. Maps of wetland distribution based on ground surveys are costly and labor-intensive, prohibiting timely evaluations of wetland loss and gain. The Great Lakes Water Resources II team at the NASA Jet Propulsion Laboratory developed the Wetlands Extent Tool 2.0 (WET 2.0) in Google Earth Engine to automate mapping of wetland distribution in the Great Lakes Basin. The team partnered with the US Fish and Wildlife Service (USFWS), Environmental Protection Agency (EPA), Minnesota Department of Natural Resources (MDNR), the National Oceanic and Atmospheric Administration (NOAA), and Ducks Unlimited (DU). WET 2.0 incorporates Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) satellite data. WET 2.0 is trained to classify anywhere in the Great Lakes Basin. Utilizing a Random Forest classifier, WET 2.0 is capable of automatically mapping wetland extent in the entire Great Lakes Basin, achieving a mean overall accuracy of 80.12% when tested in Michigan. Findings and maps produced in WET 2.0 will enable our partners to identify areas of ecosystem degradation and wetland destruction in order to enact environmental practices and policy initiatives to maintain environmental and economic health in the area.

Water Resources↗
NASA NTRS2009

Apollo-Era Life Rafts Save Hundreds of Sailors

The space shuttle is unique among spacecraft in that it glides back to Earth and lands like an airplane, usually touching ground near where it launched at Kennedy Space Center, but sometimes, in poor weather, gliding into the back-up landing site at Dryden Flight Research Center and then catching a ride back to the Cape on the back of a modified Boeing 747. Before NASA began flying the shuttle, though, astronauts had a longer, more involved trip back to base after a mission. Their capsule, called the command module, would plunge through the atmosphere before releasing a series of parachutes that would slow the craft enough for it to land on the water without too significant of an impact. Called a splashdown, this type of landing put the astronauts out in the ocean, where a specially designated U.S. Navy ship would then deploy a helicopter to retrieve the space travelers. Waiting for the rescue, the astronauts would release a highly visible marker dye into the water, then leave the command module and climb aboard a life raft. These early space pioneers had traveled thousands of miles and then landed safely back on Earth. The journey s end was in sight, but they had one more obstacle. The rotor downdraft from the helicopter coming to retrieve them, reaching sometimes as much as 100 knots per hour, was enough to flip a typical flat-bottomed life raft. Not willing to be thwarted after coming so far, NASA engineers began devising a solution. They knew they needed a highly stable inflatable raft capable of riding out the rough winds, and the solution was to make use of the most abundant resource available: water. Engineers at NASA s Johnson Space Center went to work designing and patenting a hydrodynamically stabilized ballast system that would prevent a life raft from tipping in choppy seas and fierce winds.

Source record↗
NASA NTRS1974

The National Aeronautics and Space Administration interdisciplinary studies in space technology at the University of Kansas

A broad range of research projects contained in a cooperative space technology program at the University of Kansas are reported as they relate to the following three areas of interdisciplinary interest: (1) remote sensing of earth resources; (2) stability and control of light and general aviation aircraft; and (3) the vibrational response characteristics of aeronautical and space vehicles. Details of specific research efforts are given under their appropriate departments, among which are aerospace engineering, chemical and petroleum engineering, environmental health, water resources, the remote sensing laboratory, and geoscience applications studies.

Barr, B. G.↗
NASA NTRS1975

Utilization of LANDSAT data for water quality surveys in the Choptank River

Computer processing of LANDSAT-1 multispectral digital data demonstrated the applicability of remotely sensed data to water quality survey in the Choptank River. Water classes derived by automated analysis correlate to river nuisance levels of chlorophyll a and sediment loading as defined by the Maryland Department of Water Resources and the U.S. Corps of Engineers. Results indicate that an increase in chlorophyll a concentration corresponds, relative to MSS 5, to decreases in 4 and increases in 6 relative to the trends with increasing sediment load. It appears that for the purpose of water quality analysis, under favorable atmospheric conditions, only MSS 4, 5 and 6 are necessary.

Johnson, J. M.↗
NASA NTRS2004

Education Outreach Associated with Technology Transfer in a Colonia of South Texas: Green Valley Farms Science and Space Club for Middle School Aged Children in Green Valley Farms, San Benito, Texas

Texas colonias are unincorporated subdivisions characterized by inadequate water and wastewater infrastructure, inadequate drainage and road infrastructure, substandard housing, and poverty. Since 1989 the Texas Legislature has implemented policies to halt further development of colonias and to address water and wastewater infrastructure needs in existing and new colonias along the border with Mexico. Government programs and non-government and private organization projects aim to address these infrastructure needs. Texas Tech University's Water Resources Center demonstrated the use of alternative on-site wastewater treatment in the Green Valley Farms colonia, San Benito, Texas. The work in Green Valley Farms was a component of a NASA-funded project entitled Evaluation of NASA's Advanced Life Support Integrated Water Recovery System for Non-Optimal Conditions and Terrestrial Applications. Two households within the colonia are demonstration sites for constructed wetlands. A colonia resident and activist identified educational opportunities for colonia children as a primary goal for many colonia residents. Colonia parents view education as the door to opportunity and escape from poverty for their children. The educational outreach component of the project in Green Valley Farms was a Science and Space Club for middle-school age students. Involved parents, schoolteachers, and school administrators enthusiastically supported the monthly club meetings and activities. Each month, students participated in interactive learning experiences about water use and reuse in space and on earth. Activities increased knowledge and interest in water resource issues and in science and engineering fields. The Institute for the Development and Enrichment of Advanced Learners (IDEAL) at Texas Tech University provided full scholarships for five students from Green Valley Farms to attend the Shake Hands With Your Future camp at Texas Tech University in June 2003. The educational outreach component was evaluated in February 2004 using survey instruments for students and parents, and interviews with science teachers and counselors.

Potess, Marla D.↗
NASA NTRSDate not supplied

A Lunar Water ISRU System Study for Human-Scale Propellant Production

NASA’s plans to return to the moon in the Artemis campaign include intentions for sustainable surface operations. In-Situ Resource Utilization (ISRU) is key to enabling sustainability. The use of water, which has been identified in the lunar polar regions [1-4], could be pivotal to a sustainable architecture. While water has been identified, there is limited information regarding its form and distribution. The Lunar Water ISRU Measurement Study (LWIMS) [5] outlined the current state of knowledge regarding water resources on the moon, what information is lacking, and how to approach a measurement campaign to close those knowledge gaps. However the NASA timeline necessitates that lunar surface water prospecting, or reconnaissance, efforts and ISRU system design to occur in parallel. ISRU hardware and systems development must proceed without key resource knowledge. Yet, engineering design requires come constraints and targets to work to. The goal of this study was to define a set of lunar water reference cases, based on the cur-rent lunar water information, to help focus ISRU de-sign and planning. This approach is similar to an study focused on Mars resources called Mars Water ISRU Planning (MWIP) [6].

Lunar Water↗
NASA NTRS1974

ERTS program of the US Army Corps of Engineers

The Army Corps of Engineers research and development efforts associated with the ERTS Program are confined to applications of investigation, design, construction, operation, and maintenance of water resource projects. Problems investigated covered: (1) resource inventory; (2) environmental impact; (3) pollution monitoring; (4) water circulation; (5) sediment transport; (6) data collection systems; (7) engineering; and (8) model verification. These problem areas were investigated in relation to bays, reservoirs, lakes, rivers, coasts, and regions. ERTS-1 imagery has been extremely valuable in developing techniques and is now being used in everyday applications.

Jarman, J. W.↗
NASA NTRS2020

Exploring Spatiotemporal Relations Between Soil Moisture, Precipitation, and Streamflow for a Large Set of Watersheds Using Google Earth Engine

An understanding of streamflow variability and its response to changes in climate conditions is essential for water resource planning and management practices that will help to mitigate the impacts of extreme events such as floods and droughts on agriculture and other human activities. This study investigated the relationship between precipitation, soil moisture, and streamflow over a wide range of watersheds across the United States using Google Earth Engine (GEE). The correlation analyses disclosed a strong association between precipitation, soil moisture, and streamflow, however, soil moisture was found to have a higher correlation with the streamflow relative to precipitation. Results indicated different strength of the association depends on the watershed classes and lag times assessments. The perennial watersheds showed higher coherence compared to intermittent watersheds. Previous month precipitation and soil moisture have a stronger influence on the current month streamflow, particularly in the snow-dominated watersheds. Monthly streamflow forecasting models were developed using an autoregressive integrated moving average (ARIMA) and support vector machine (SVM). The results showed that the SVM model generally performed better than the ARIMA model. Overall streamflow forecasting model performance varied considerably among watershed classes, and perennial watersheds tend to exhibit better predictably compared to intermittent watersheds due to lower streamflow variability. The SVM models with precipitation and streamflow inputs performed better than those with streamflow input only. Results indicated that the inclusion of antecedent root-zone soil moisture improved the streamflow forecasting in most of the watersheds, and the largest improvements occurred in the intermittent watersheds. In conclusion, this work demonstrated that knowing the relationship between precipitation, soil moisture, and streamflow in different watershed classes will enhance the understanding of the hydrologic process and can be effectively utilized in improving streamflow forecasting for better satellite-based water resource management strategies.

Nazmus Sazib↗
NASA NTRS2017

Mars Atmospheric Conversion to Methane and Water: An Engineering Model of the Sabatier Reactor with Characterization of Ru/Al2O3 for Long Duration Use on Mars

The Atmospheric Processing Module (APM) is a Mars In-Situ Resource Utilization (ISRU) technology designed to demonstrate conversion of the Martian atmosphere into methane and water. The Martian atmosphere consists of approximately 95 carbon dioxide (CO2) and residual argon and nitrogen. APM utilizes cryocoolers for CO2 acquisition from a simulated Martian atmosphere and pressure. The captured CO2 is sublimated and pressurized as a feedstock into the Sabatier reactor, which converts CO2 and hydrogen to methane and water. The Sabatier reaction occurs over a packed bed reactor filled with Ru/Al2O3 pellets. The long duration use of the APM system and catalyst was investigated for future scaling and failure limits. Failure of the catalyst was detected by gas chromatography and temperature sensors on the system. Following this, characterization and experimentation with the catalyst was carried out with analysis including x-ray photoelectron spectroscopy and scanning electron microscopy with elemental dispersive spectroscopy. This paper will discuss results of the catalyst performance, the overall APM Sabatier approach, as well as intrinsic catalyst considerations of the Sabatier reactor performance incorporated into a chemical model.

Ru/Al2O3 Catlayst↗
NASA NTRS2017

Mars Atmospheric Conversion to Methane and Water: An Engineering Model of the Sabatier Reactor with Characterization of Ru/Al2O3 for Long Duration Use on Mars

The Atmospheric Processing Module (APM) is a Mars In-Situ Resource Utilization (ISRU) technology designed to demonstrate conversion of the Martian atmosphere into methane and water. The Martian atmosphere consists of approximately 95 carbon dioxide (CO2) and residual argon and nitrogen. APM utilizes cryocoolers for CO2 acquisition from a simulated Martian atmosphere and pressure. The captured CO2 is sublimated and pressurized as a feedstock into the Sabatier reactor, which converts CO2 and hydrogen to methane and water. The Sabatier reaction occurs over a packed bed reactor filled with Ru/Al2O3 pellets. The long duration use of the APM system and catalyst was investigated for future scaling and failure limits. Failure of the catalyst was detected by gas chromatography and temperature sensors on the system. Following this, characterization and experimentation with the catalyst was carried out with analysis including x-ray photoelectron spectroscopy and scanning electron microscopy with elemental dispersive spectroscopy. This paper will discuss results of the catalyst performance, the overall APM Sabatier approach, as well as intrinsic catalyst considerations of the Sabatier reactor performance incorporated into a chemical model.

Catlayst↗