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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Utilizing Earth Observations to Understand Landscape Patterns and Assist in Wildlife Management in Iona National Park, Angola

Following the end of the Angolan Civil War (1975-2002), human habitation in Iona National Park has grown exponentially, as has the livestock population. An ongoing drought beginning in 2017 has brought people, livestock, and wildlife into increasing competition for resources within the park. This study used Earth observation data, primarily Landsat and Sentinel imagery, to examine landscape trends to improve wildlife preservation approaches in Iona National Park, Angola. In collaboration with the NGO African Parks, we developed a robust land use and land cover (LULC) classification model using remote sensing data to augment sparse ground-based data in this arid land region. We used Google Earth Engine and a random forest classifier to map vegetation types, water bodies, and potential wildlife habitats. This analysis resulted in a high spatial resolution LULC time-series between 1984-2023, highlighting critical periods of socioecological change over the past 40 years. These results increased the partner’s ability to make scientifically grounded decisions about resource allocation and conservation priorities. This analysis supports the feasibility of applying remote sensing techniques coupled with machine learning models in dry regions, where standard survey methods are frequently limited by accessibility and resource availability. However, we identified limitations in ground-truth data and the difficulty of recognizing certain vegetation types in arid areas. Despite these limitations, the study demonstrated Earth observations' ability to transform wildlife management techniques in distant and data-scarce locations, providing a reproducible foundation for similar ecosystems around the world.

Emmanuel Aklie↗
NASA NTRS1999

Mapping Vegetation Structure in Kakadu National Park: An AIRSAR and GIS Application in Conservation

Airborne Synthetic Aperture Radar (AIRSAR) data were used to map vegetation structure in Kakadu National Park Australia as part of the PACRIM project. SAR data were co-registered with Landsat TM, aerial photos, and map data in a geographic information system for a small test area consisting of mangrove, floodplain grasslands, lowland tropical evergreen forest and upland mixed deciduous and evergreen tropical forest near the South Alligator River. Landsat (Thematic Mapper) TM very clearly showed the floristic composition and burn scars from the previous years fires and the AIRSAR data provided a profile of vegetation structure. Extensive field data on vegetation species composition and structure were collected across a series of transects in cooperation with a survey of avifauna in an effort to link the habitat edge structure with bird species responses. A test site was found that contained two types of habitat edges: 1) A structure specific edge - characterized by the appearance of a very strong structural change in the forest canopy occurring in the absence of a substantial turnover in floristics. 2) Floristic edge - a sharp transition in vegetation genetic composition with a mixed set of structural changes. Specific polarization combinations were selected that were highly correlated to a set of desired structural parameters found in the field data. Classification routines were employed to group radar pixels into 3 structural classes based on: the Surface Area to Volume ratio (SA/V) of the stems, the SA/V of the branches, and the leaf area index of the canopy. Separate canopy structure maps were then entered into the GIS and bird responses were observed relative to the classes and their boundaries. Follow-on work will consist of extending this approach to neighboring areas, generating structure maps, predicting bird responses across the edges, and make accuracy assessments.

Imhoff, Marc L.↗
DOE OSTI2026

CROCUS Tipping Bucket Rain Gauge Data from Argonne Deployable Mast Deployed at NEIU Carruthers Center for Inner City Studies (CCICS)

The Tipping Bucket Rain Gauge (TBRG) dataset contains data from a non-heated Met One 12-inch tipping bucket rain gauge that was mounted on the Argonne Deployable Mast (ADM). The ADM is a rapid deployable meteorological trailer that can be outfitted with instrumentation to measure urban heat island effects, urban flooding or urban flux measurements. During the urban flooding field campaign, the ADM was outfitted with multiple precipitation measurement systems, including the TBRG. This dataset contains one minute measurements for precipitation accumulation during the ADM's deployment at the Northeastern Illinois University (NEIU) Carruthers Center for Inner City Studies (CCICS) campus. These data are helpful for identifying periods of precipitation, leading to potential flooding. TBRGs can be used to validate optical rain gauge data and disdrometer data collected during the CROCUS urban flooding campaign. Data were collected at the CCICS building parking lot, located in the south side of Chicago, IL. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (ADM-ccics), instrument name (tbrg), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or act-doe.

1-minute Precipitation Accumulation↗
NASA NTRS1993

Linear mixing model applied to AVHRR LAC data

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55 - 3.93 microns channel was extracted and used with the two reflective channels 0.58 - 0.68 microns and 0.725 - 1.1 microns to run a Constraine Least Squares model to generate vegetation, soil, and shade fraction images for an area in the Western region of Brazil. The Landsat Thematic Mapper data covering the Emas National park region was used for estimating the spectral response of the mixture components and for evaluating the mixing model results. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse resolution data for global studies.

Holben, Brent N.↗
DOE OSTI2024

AmeriFlux US-EA4 EAA Field Research Park Woodland

This is the AmeriFlux version of the carbon flux data for the site US-EA4 EAA Field Research Park Woodland. Site Description - This tower is located at the Edwards Aquifer Authority (EAA) Field Research Park (FRP) just northeast of San Anotnio. It is located at the top of a hill in a small clearing amongst oak-juniper woodlands

McKinney, Tyson↗
NASA NTRS1991

Radar measurements of the orbital debris environment

The collection and preliminary processing of the first significant accumulation of orbital debris data collected by the Haystack radar is described. The data are collected in the 'beam park' mode of operation in which the radar stares in a fixed direction and debris randomly passes through the field of view. Haystack's processing system performed automatic real-time processing and threshold detection, and saved only data associated with a possible detection. Approximately 123 hours of data were collected with the radar beam parked at an elevation angle of 10 deg and an azimuth of 180 deg; 3.8 hours were collected at an elevation angle of 30 deg and an azimuth of 180 deg; and 33.9 hours were collected at an elevation angle of 90 deg. A computer model of the response of the Haystack radar while in beam park operation is described. The model calculates the probability of detection and collection area for all sizes and orbital inclinations of debris visible to the radar. At this time, the approximate sizes of the detected objects have not been determined. However, the observed detection rates and cumulative signal to noise ratio distributions agree well with the results of the radar response model using NASA's current orbital debris environment.

Stansbery, Eugene G.↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-EA4 EAA Field Research Park Woodland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-EA4 EAA Field Research Park Woodland. This is the FLUXNET version of the carbon flux data for the site US-EA4 EAA Field Research Park Woodland produced by applying the standard ONEFlux (1F) software. Site Description - This tower is located at the Edwards Aquifer Authority (EAA) Field Research Park (FRP) just northeast of San Anotnio. It is located at the top of a hill in a small clearing amongst oak-juniper woodlands

McKinney, Tyson [The University of Texas at Austin↗
NASA NTRS2012

Generating Ground Reference Data for a Global Impervious Surface Survey

We are engaged in a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. The GLS data from Landsat provide an unprecedented opportunity to map global urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such as buildings, roads and parking lots. Finally, with GLS data available for the 1975, 1990, 2000, and 2005 time periods, and soon for the 2010 period, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. Our approach works across spatial scales using very high spatial resolution commercial satellite data to both produce and evaluate continental scale products at the 30m spatial resolution of Landsat data. We are developing continental scale training data at 1m or so resolution and aggregating these to 30m for training a regression tree algorithm. Because the quality of the input training data are critical, we have developed an interactive software tool, called HSegLearn, to facilitate the photo-interpretation of high resolution imagery data, such as Quickbird or Ikonos data, into an impervious versus non-impervious map. Previous work has shown that photo-interpretation of high resolution data at 1 meter resolution will generate an accurate 30m resolution ground reference when coarsened to that resolution. Since this process can be very time consuming when using standard clustering classification algorithms, we are looking at image segmentation as a potential avenue to not only improve the training process but also provide a semi-automated approach for generating the ground reference data. HSegLearn takes as its input a hierarchical set of image segmentations produced by the HSeg image segmentation program [1, 2]. HSegLearn lets an analyst specify pixel locations as being either positive or negative examples, and displays a classification of the study area based on these examples. For our study, the positive examples are examples of impervious surfaces and negative examples are examples of non-impervious surfaces. HSegLearn searches the hierarchical segmentation from HSeg for the coarsest level of segmentation at which selected positive example locations do not conflict with negative example locations and labels the image accordingly. The negative example regions are always defined at the finest level of segmentation detail. The resulting classification map can be then further edited at a region object level using the previously developed HSegViewer tool [3]. After providing an overview of the HSeg image segmentation program, we provide a detailed description of the HSegLearn software tool. We then give examples of using HSegLearn to generate ground reference data and conclude with comments on the effectiveness of the HSegLearn tool.

Tilton, James C.↗
DOE OSTI2021

AmeriFlux FLUXNET-1F US-ORv Olentangy River Wetland Research Park

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-ORv Olentangy River Wetland Research Park. This is the FLUXNET version of the carbon flux data for the site US-ORv Olentangy River Wetland Research Park produced by applying the standard ONEFlux (1F) software. Site Description - The ORWRP site is a 21-ha large-scale, long-term wetland campus facility that is owned by Ohio State University. It is designed to provide teaching, research, and service related to wetland and river science and ecological engineering. The site has been developed in several phases: Phase 1 (1992 - 1994) - Construction of two 2.5-acre deepwater marshes and a river water delivery system began, with pumps installed on the floodplain to bring water from the Olentangy River. In May 1994, one wetland was planted with marsh vegetation, while the other remained as an unplanted control; Phase 2 (1994 - 1999) - Development of a research and teaching infrastructure took place with the construction of boardwalks, a pavilion, and a compound. The creation of the 7-acre naturally flooded oxbow was also included; Phase 3 (2000 - 2003) - As a research building was created, three additional wetlands were created in the vicinity of the building, including a stormwater wetland that receives runoff from the roof of the building; Phase 4 - The current phase involves research access to the Olentangy River.

Bohrer, Gil↗
DOE OSTI2024

Simulator Data Analysis to Inform Digitalized Environment Impacts on Human Reliability

The U.S. Nuclear Regulatory Commission (NRC) has developed a human reliability analysis (HRA) method, termed the Integrated Human Event Analysis System for Event and Condition Assessment (IDHEAS-ECA), in order to estimate human error probabilities (HEPs) in risk-informed regulatory applications. To update the quantification part of IDHEAS-ECA, the NRC required human performance and error data from fully digitalized main control rooms (MCRs); therefore, it requested that Idaho National Laboratory (INL) revisit previous data collection studies and investigate how the following three factors impact human reliability: self-checking, peer-checking, and automation. The HRA data collection studies revisited were the Human Reliability Data Extraction (HuREX) project, developed by the Korea Atomic Energy Research Institute (KAERI), and the Simplified Human Error Experimental Program (SHEEP), developed by INL. HuREX is a representative HRA data collection study that collects human reliability data from full-scope simulators staffed by licensed operators. SHEEP, on the other hand, has been proposed to complement such full-scope studies by collecting data via simplified simulators staffed by non-licensed student operators. In the HuREX study, KAERI collected HRA data from fully digitalized MCRs for the Advanced Power Reactor (APR)–1400. The SHEEP data were obtained from simplified simulators that partially mimicked the features of digitalized MCRs. The present report mainly discusses how the impacts of the aforementioned three factors on human errors were derived from these two data collection studies.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1981

Non-E x B ordered ion beams upstream of the earth's bow shock

The unexpected appearance of spin modulations in the fixed voltage electrostatic analyzer detectors on ISEE 1 and 2 has made it possible to study the plasma properties of the upstream ions in high time resolution. Using an isotropic flowing Maxwellian distribution to model the count rate modulations, estimates have been obtained of the local plasma temperature and three-dimensional flow velocity of the observed upstream ion population. It is found that in almost all of the observations of upstream particles there exist beam-like ions with temperatures in the range 5-80 eV. Their flow velocities cannot be ordered by E x B. This last point separates these observations from the previously reported reflected and diffuse populations of upstream ions. Mechanisms that can gyrophase bunch the ions reflected at the bow shock are discussed as a method of explaining the data.

Gurgiolo, C.↗
NASA NTRS1989

Nonequilibrium hypersonic aerothermodynamics

Nonequilibrium phenomena in hypersonic flows are examined on the basis of theoretical models and selected experimental data, in an introduction intended for second-year graduate students of aerospace engineering. Chapters are devoted to the physical nature of gas atoms and molecules, transitions of internal states, the formulation of the master equation of aerothermodynamics, the conservation equations, chemical reactions in CFD, the behavior of air flows in nonequilibrium, experimental aspects of nonequilibrium flow, a review of experimental results, and gas-solid interaction. Diagrams, graphs, and tables of numerical data are provided.

Park, Chul↗
NASA NTRS1993

Results of multiband (L, S, Ku band) propagation measurements and model for high elevation angle land mobile satellite channel

Signal propagation in the land mobile satellite (LMS) service is an important consideration due to its critical impact on the overall economic and commercial viability of the system. At frequencies allocated for LMS systems, shadowing of the line-of-sight (LOS) signal as well as multipath propagation phenomena can severely impair the link availability. In particular, as most of the studies have shown, the shadowing of LOS signal causes long and deep fades in a variety of mobile environments due to the inherent nature of the channel between the satellite and a mobile. Roadside obstacles, such as buildings, trees, utility poles etc., in the immediate vicinity of a mobile and the surrounding terrain are major sources of signal shadowing in LMS links. Therefore, a proper knowledge of link degradation is essential for cost-effective planning of a satellite based mobile communication system. The results of a propagation campaign undertaken to characterize the fading nature of LMS channel at high elevation angles is presented. It was envisaged that one of the most important physical variables contributing to the amount of LOS signal shadowing is the elevation angle of the satellite. At higher elevation angles to the satellite, less obstructions in the direct satellite-to-mobile path would therefore amount to statistically better link availability. Narrowband channel measurements were carried out at three RF frequencies corresponding to L (1.3 GHz), S (2.32/2.45 GHz), and Ku (10.4 GHz) bands. The campaign itself was divided into two phases to observe the effects of seasonal variation of foliage on the roadside trees. Phase measurements were carried out in September 1991 and in April 1992. Some important aspects from the statistical analysis of the propagation data are presented.

Parks, M. A. N.↗
NASA NTRS1979

Experimental Studies of Radiative Base Heating of a Jovian Entry Model

To verify the validity of the theoretical predictions of Park on radiative base heating rates, two types of models are tested in the absence of ablation in shock tube flows which simulate the Jovian entry environments. The radiative fluxes are measured by pyroelectric radiometers imbedded in the models in a stream consisting of 10% hydrogen in a bath of either neon or argon. In addition, time-resolved photographs are taken to obtain information on the structure of base flows needed in Park's theory. The experimental data show that the radiative base heat fluxes are significant fractions of the radiative fluxes at the front stagnation point, the ratio being dependent upon Mach number and the configuration of the models. When the effects of the model geometry and Mach number are accounted for, the present experimental results agree with the theoretical predictions of Park.

Shirai, Hiroyuki↗
NASA NTRS2021

Comprehensive Comparison of Airborne and Spaceborne SAR and LiDAR Estimates of Forest Structure in the Tallest Mangrove Forest on Earth

A recent suite of new global-scale satellite sensors and regional-scale airborne campaigns are providing a wealth of remote sensing data capable of dramatically advancing our current understanding of the spatial distribution of forest structure and carbon stocks. However, a baseline for forest stature and biomass estimates has yet to be established for the wide array of available remote sensing products. At present, it remains unclear how the estimates from these sensors compare to one another in terrestrial forests, with a clear dearth of studies in high carbon density mangrove ecosystems. In the tallest mangrove forest on Earth (Pongara National Park, Gabon), we leverage the data collected during the AfriSAR campaign to evaluate 17 state-of-the-art sensor data products across the full range of height and biomass known to exist globally in mangrove forest ecosystems, providing a much-needed baseline for sensor performance. Our major findings are: (Houghton, Hall, Goetz) height estimates are not consistent across products, with opposing trends in relative and absolute errors, highlighting the need for an adaptive approach to constraining height estimates (Panet al., 2011); radar height estimates had the lowest calibration error and bias, with further improvements using LiDAR fusion (Bonan, 2008); biomass variability and uncertainty strongly depends on forest stature, with variation across products increasing with canopy height, while relative biomass variation was highest in low-stature stands (Le Quéréet al., 2017); a remote sensing product's sensitivity to variations in canopy structure is more important than the absolute accuracy of height estimates (Mitchardet al., 2014); locally-calibrated area-wide totals are more representative than generalized global biomass models for high-precision biomass estimates. The findings presented here provide critical baseline expectations for height and biomass predictions across the full range of mangrove forest stature, which can be directly applied to current (TanDEM-X, GEDI, ICESat-2) and future (NISAR, BIOMASS) global-scale forest monitoring missions.

Atticus E.L. Stovall↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-xRM NEON Rocky Mountain National Park, CASTNET (RMNP)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xRM NEON Rocky Mountain National Park, CASTNET (RMNP). This is the FLUXNET version of the carbon flux data for the site US-xRM NEON Rocky Mountain National Park, CASTNET (RMNP) produced by applying the standard ONEFlux (1F) software. Site Description - NEON's Rocky Mountain National Park (RMNP) tower stands 12 km south of Estes Park, Colorado, representing a growing mosaic of urban and exurban areas. While the property is owned by RMNP, it is not contiguous with the core park boundaries. As a mid-elevation site (2,750 m) on the east side of the Continental Divide, the site is aptly situated to investigate the chemical climate (i.e., pollution) generated along the Front Range as well as dust deposition produced and transported from the Great Basin to higher elevations. This is a particularly salient issue given recent estimates which project that an additional two million residents will inhabit the Front Range in twenty years.

Network), NEON (National Ecological Observatory↗