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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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NASA NTRS1982

Irrigated acreage in the Bear River Basin as of the 1975 growing season

The irrigated cropland in the Bear River Basin as of the 1975 growing season was inventoried from satellite imagery. LANDSAT color infrared images (scale 1:125,000) were examined for early, mid, and late summer dates, and acreage was estimated by use of township/section overlays. The total basin acreage was estimated to be 573,435 acres, with individual state totals as follows: Idaho 234,370 acres; Utah 265,505 acres; and Wyoming 73,560 acres. As anticipated, wetland areas intermingled among cropland appears to have produced an over-estimation of irrigated acreage. According to a 2% random sample of test sites evaluated by personnel from the Soil Conservation Service such basin-wide over-estimation is 7.5%; individual counties deviate significantly from the basin-wide figure, depending on the relative amount of wetland areas intermingled with cropland.

Ridd, M. K.↗

NASA NTRS2019

How Does Water Delivery System Design Impact the Microbial Load of Salad Crops?

In a microgravity setting, such as the environment aboard the International Space Station (ISS), an ideal plant water delivery system is one that can grow edible crops with minimal resource consumption and minimal risk to crew members. There are also concerns associated with the ability to control fluid escape and biofilm formation resulting in potential dangers to systems, crops, or crewmembers. To identify an appropriate system, candidate systems were assembled and operated under simulated ISS environmental conditions (T,CO2,and RH) with red romaine lettuce (Lactuca sativa cultivar 'Outredgeous') as a model crop. Fluid reservoirs and randomly selected planting sites were sampled every seven days until maturity at which point edible plant biomass and root samples were also taken. Heterotrophic bacteria and fungi growth patterns throughout each planting cycle were determined by plate counts on appropriate agar media. The candidate systems were compared to a classic hydroponics system as a control and harvested crops were compared to controls as well as Veggie-grown and market produce. Plants harvested from candidate systems yielded lower average heterotrophic bacteria and fungi per gram of plant mass levels when compared to market and Veggie samples as well as those from the control system. Additional studies to evaluate the system sanitation regimen as well as testing additional crops should be considered to aid in the selection of an ideal system.

Curry, Aaron B.↗

NASA NTRS2020

Recommendations for Using Noise Monitors to Estimate Noise Exposure During X-59 Community Tests

A low fidelity simulation approach is used to explore how to place and use noise monitors during X-59 QueSST community tests, where people’s annoyance to the noise produced by the X-59 aircraft will be gathered. Several recommendations are provided including: 1) the desired number of sparsely spaced noise monitor sites within the survey area, 2) whether to group and average measurements across multiple noise monitors located at a site, 3) what spacing should be used if grouped noise monitors are used, 4) an approach to mitigate ambient noise contamination at the measurement sites, 5) a method to combine empirical and predicted dose estimates to provide a single dose estimate for respondents, and 6) assessing how changes in turbulence intensity and array configuration affect dose uncertainty. To make these recommendations, the error that is expected when fitting contrived, smoothly varying sonic boom “reference exposure surfaces” is studied when a spatially sparse and scattered set of samples is used as responses for the fit. The reference exposure surfaces mimic the sonic boom exposure at ground level that might be expected in the X-59 survey area in the absence of atmospheric turbulence, ambient noise, and other localized effects. The spatial extent of these surfaces varies and is representative of the different survey area sizes that might be expected during future X-59 community overflight tests. These contrived reference surfaces are sampled, and those reference samples are then perturbed to mimic atmospheric turbulence, ambient noise and other localized effects that might affect noise monitor measurements within overflown communities. Two different surface fitting methods are investigated when fitting these perturbed samples to approximate the reference surface. The first method uses interpolation between the perturbed data at the scattered sites to compute the fit. The second method fits a polynomial surface model to the perturbed data using ordinary least squares regression analysis. For both fitting methods, the root mean square fit error is computed from the pointwise difference between the fit surface and the reference surface as the count and configuration of the sites is varied while also averaging the error across many different realizations of both the smooth variation of the reference exposure surface and the random, localized perturbations at the sample sites. Different site configurations are compared using this error statistic to make the recommendations noted above. Additionally, the two fitting approaches (interpolation vs linear regression) are compared based on the fit error observed in these simulations. These analyses, comparisons, and recommendations should inform future decisions on the noise monitor placement and the methods used to analyze the noise monitor data that is collected during X-59 community overflights.

sonic boom↗

NASA NTRS1995

Bayes classification of interferometric TOPSAR data

We report the Bayes classification of terrain types at different sites using airborne interferometric synthetic aperture radar (INSAR) data. A Gaussian maximum likelihood classifier was applied on multidimensional observations derived from the SAR intensity, the terrain elevation model, and the magnitude of the interferometric correlation. Training sets for forested, urban, agricultural, or bare areas were obtained either by selecting samples with known ground truth, or by k-means clustering of random sets of samples uniformly distributed across all sites, and subsequent assignments of these clusters using ground truth. The accuracy of the classifier was used to optimize the discriminating efficiency of the set of features that was chosen. The most important features include the SAR intensity, a canopy penetration depth model, and the terrain slope. We demonstrate the classifier's performance across sites using a unique set of training classes for the four main terrain categories. The scenes examined include San Francisco (CA) (predominantly urban and water), Mount Adams (WA) (forested with clear cuts), Pasadena (CA) (urban with mountains), and Antioch Hills (CA) (water, swamps, fields). Issues related to the effects of image calibration and the robustness of the classification to calibration errors are explored. The relative performance of single polarization Interferometric data classification is contrasted against classification schemes based on polarimetric SAR data.

Michel, T. R.↗

NASA NTRS2000

Diffusing Wave Spectroscopy Used to Study Foams

The white appearance of familiar objects such as clouds, snow, milk, or foam is due to the random scattering of light by the sample. As we all know, pure water is clear and easily passes a beam of light. However, tiny water droplets, such as those in a cloud, scatter light because the air and water droplet have different indexes of refraction. When many droplets, or scattering sites, are present, the incident light is scattered in random directions and the sample takes on a milky white appearance. In a glass of milk, the scattering is due to small colloidal particles. The white appearance of shaving cream, or foam, is due to the scattering of light at the water-bubble interface. Diffusing wave spectroscopy (DWS) is a laser light-scattering technique used to noninvasively probe the particle dynamics in systems that strongly scatter light. The technique takes advantage of the diffuse nature of light, which is reflected or transmitted from samples such as foams, dense colloidal suspensions (such as paint and milk), emulsions, liquid crystals, sandpiles, and even biological tissues.

Zimmerli, Gregory A.↗

NASA NTRS2004

Constraints on the Lithological Variation near the Surface of the HED Planetoid from the Petrology of 91 & 92 Series Antarctic Achondrites

The petrography of a suite of meteorite sections: PCA91006,14; PCA91078,9; PCA91083,6; PCA91159,4; PCA91179,9; PCA91245,9; EET92003,14; EET92004,12; EET92015,4; EET92022,7; EET92026,4; and EET92027,5 is used as an initial sample of the lithological variation on the surface of the HED planetoid (presumably asteroid 4 Vesta). These samples will be combined with much larger arrays of petrographic data for the many Antarctic basaltic achondrites to provide a random sample of the surface of the body. The full variety of the lithologies existing on the parent body is only accessible when the polymict achondrites are considered. The polymict samples contain lithologies that sample multiple provenances as well as those not seen as monolithologic meteorites like eucrites and diogenites. Comparison of lithological variation within individual meteorites provides a subset of variations at the site of last impact. In aggregate, the variations within the achondrites now available may be close to a random sample of the parent body. In combination of microanalytical and imaging techniques now available permit a mass balanced assessment of the distribution and abundance of lithologies to be made. These initial results provide a description of methodology to be tested. All samples were studied and photographed on a polarizing microscope to provide location information. Major mineral phases and randomly selected points (on lines and grids) were analyzed in each thin section. In addition backscattered electron and X-ray imaging of clasts and sections provide the basis for high precision modal analyses of the abundance and distribution of both lithic and mineral clasts. These data provide objective, area based comparisons with other Antarctic samples.

Bjonnes, Emily E.↗

NASA NTRS2019

The Terrestrial Organism and Biogeochemistry Spatial Sampling Design for the National Ecological Observatory Network

The National Ecological Observatory Network (NEON) seeks to facilitate ecological prediction at a continental scale by measuring processes that drive change and responses at sites across the United States for thirty years. The spatial distribution of observations of terrestrial organisms and soil within NEON sites is determined according to a “design‐based” sample design that relies on the randomization of sampling locations. Development of the sample design was guided by high‐level NEON objectives and the multitude of data products that will be subjected to numerous analytical approaches to address the causes and consequences of ecological change. A requirement framework permeates the NEON design, ensuring traceability from each facet of the design to the high‐level requirements that make the NEON mission statement actionable. Requirements were developed for the terrestrial sample design to guide the key components of the design: Randomizing the sample locations ensures the unbiased collection of data, is appropriate for organisms and soil, and provides data suitable for a variety of analyses. Stratification increases efficiency and allows sampling to focus on those parts of the landscape measured by other NEON observation platforms. Attention to the sample size and spatial plot allocation ensures that data products will be sufficient to inform questions asked of the data and the NEON objectives. Establishing a framework with the capacity for re‐evaluate and design iteration allows for adaption to unexpected challenges and optimization of the sample design based on early data returns. The utility of the NEON sampling design is highlighted by its application across terrestrial systems. The data generated from this unique design will be used to quantify patterns in: the abundance and diversity of small mammals, breeding birds, insects, and soil microbes; vegetation structure, biomass, productivity, and diversity; and soil biogeochemistry.

National Ecological Observatory Network↗

NASA NTRS1975

Lunar glass compositions - Apollo 16 core sections 60002 and 60004

Approximately 500 glasses between 1 mm and 125 microns in size have been analyzed from fourteen samples from the Apollo 16 core sections 60002 and 60004. The majority of glasses have compositions comparable to those found in previous studies of lunar surface soils; however, two new and distinct glass compositions that are probably derived in part from mare material occur in the core samples. The major glass composition in all samples is that of Highland Basalt glass, but it also appears that high-K Fra Mauro Basalt (KREEP) glass is more common at the Apollo 16 site than was previously thought. The relative abundance of glasses within the core samples is random in distribution: each sample is characterized by a particular assemblage and distribution of the constituent glass compositions.

Meyer, H. O. A.↗

NASA NTRS1987

The correspondence of surface climate parameters with satellite and terrain data

One of the goals of the research was to develop a ground sampling stragegy for calibrating remotely sensed measurements of surface climate parameters. The initial sampling strategy involved the stratification of the terrain based on important ancillary surface variables such as slope, exposure, insolation, geology, drainage, fire history, etc. For a spatially heterogeneous population, sampling error is reduced and efficiency increased by stratification of the landscape into more homogeneous sub-areas and by employing periodic random spacing of samples. These concepts were applied in the initial stratification of the study site for the purpose of locating and allocating instrumentation.

Dozier, Jeff↗

NASA NTRSDate not supplied

Mapping Post-fire Conifer Regeneration using Snow-on Imagery

The 2000 Jasper Fire in the Black Hills of South Dakota was the largest wildfire to date in the region, burning over 83,000 acres of ponderosa pine forest. In collaboration with partners from the United States Forest Service (USFS) Black Hills Experimental Forest, USFS Rocky Mountain Research Station, and United States Geological Survey Geosciences and Environmental Change Science Center, we characterized post-fire forest regeneration within high severity burn patches. We accomplished this by implementing novel conifer detection techniques using a snow index mask to create a winter, snow-on image composite from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data. We utilized 2015 USFS stem maps of field-observed regeneration plots and ocularly sampled reforestation sites planted from 2001–2013. The field data and imagery were used to train a Random Forest (RF) model in Google Earth Engine. The RF model classified conifer regeneration density as low, medium, or high across the high-severity burn area with an overall accuracy of 81.3% for 2021. Approximately 45.9% of the high-severity burn area had low or no regeneration (0-40 trees per acre) 20 years post-fire. Given our partners' desire to find easily accessible low conifer regeneration zones, we identified 4,079 acres of priority planting sites that were within 1,500 feet of roads, had not been planted previously, and were larger than 50 acres. This method supports the use of snow-on imagery as a successful technique to identify conifer regeneration in a post-wildfire landscape.

Yeshey Seldon↗

NASA NTRS1978

Nationwide forestry applications program: Procedure 1 applicability to rangeland classification

The author has identified the following significant results. An assumption that short prairie grass and salt grass could be differentiated on aircraft photographs was inaccurate for the Weld County site. However, rangeland could be differentiated using procedure 1 from LACIE. Estimates derived from either random or systematic sampling were satisfactory. Level 1 features were separated and mapped, and proportions were estimated with accompanying confidence statements.

Reeves, C. A.↗

NASA NTRS1995

Global stratigraphy of Venus: Analysis of a random sample of thirty-six test areas

Basilevsky, Alexander T.↗

NASA NTRSDate not supplied

Black Hills Wildfires: Mapping Post-fire Conifer Regeneration using Snow-on Imagery

The 2000 Jasper Fire in the Black Hills of South Dakota was the largest wildfire to date in the region, burning over 83,000 acres of ponderosa pine forest. In collaboration with partners from the United States Forest Service (USFS) Black Hills Experimental Forest, USFS Rocky Mountain Research Station, and United States Geological Survey Geosciences and Environmental Change Science Center, we characterized post-fire forest regeneration within high-severity burn patches. We accomplished this by implementing novel conifer detection techniques using a snow index mask to create a winter, snow-on image composite from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data. We utilized 2015 USFS stem maps of field-observed regeneration plots and ocularly sampled additional reforestation sites planted in 2001–2013. In Google Earth Engine (GEE), the field data and imagery were used to train a Random Forest (RF) model. The RF model classified 2021 conifer regeneration density as low, medium, or high across the high-severity burn area with an overall accuracy of 81.3%. Approximately 45.9% of the high-severity burn had low or no regeneration (0-40 trees per acre) 20 years post-fire. Given our partners' desire to find easily accessible low conifer regeneration zones, we identified 4,079 acres of priority planting sites that were within 1,500 feet of roads, had not been planted previously, and were larger than 50 acres. This method supports the use of snow-on imagery as a successful technique to identify conifer regeneration.

Casey Menick↗

NASA NTRS2022

Black Hills Wildfires: Mapping Post-Fire Conifer Regeneration using Snow-On Imagery

The 2000 Jasper Fire in the Black Hills of South Dakota was the largest wildfire to date in the region, burning over 83,000 acres of ponderosa pine forest. In collaboration with partners from the United States Forest Service (USFS) Black Hills Experimental Forest, USFS Rocky Mountain Research Station, and United States Geological Survey Geosciences and Environmental Change Science Center, we characterized post-fire forest regeneration within high-severity burn patches. We accomplished this by implementing novel conifer detection techniques using a snow index mask to create a winter, snow-on image composite from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data. We utilized 2015 USFS stem maps of field-observed regeneration plots and ocularly sampled additional reforestation sites planted in 2001–2013. In Google Earth Engine (GEE), the field data and imagery were used to train a Random Forest (RF) model. The RF model classified 2021 conifer regeneration density as low, medium, or high across the high-severity burn area with an overall accuracy of 81.3%. Approximately 45.9% of the high-severity burn had low or no regeneration (0-40 trees per acre) 20 years post-fire. Given our partners' desire to find easily accessible low conifer regeneration zones, we identified 4,079 acres of priority planting sites that were within 1,500 feet of roads, had not been planted previously, and were larger than 50 acres. This method supports the use of snow-on imagery as a successful technique to identify conifer regeneration.

Casey Menick↗

NASA NTRS2003

Estimating Uncertainty in GPCP and TRMM Multi-Satellite Precipitation Estimates

One of the high-priority problems in satellite precipitation estimation is developing algorithms for estimating the errors in precipitation retrievals by individual sensors and subsequent multi-satellite combinations. Classically, we distinguish between "random" and "bias" errors, which do and do not, respectively average to zero over a "big enough" time/space sample. The current operational GPCP and TRMM multi-satellite algorithms are nearly unique in estimating random error for the monthly precipitation estimates from individual sensor systems (including gauge), following Huffman, and then making multi-sensor combinations. No routinely operational global precipitation produces estimates of bias error. Subsequently, a similar scheme has been followed to provide random error estimates for the Multi-satellite Precipitation Analysis (MPA) being computed in real time and after real time for TRMM. The Huffman algorithm for random error is briefly reviewed, including a discussion of the limitations imposed on the algorithm by standard monthly precipitation data sets. Starting from a very simple theoretical treatment of the histogram of precipitation samples in a month, an equation is developed that depends on the estimated average precipitation rate for the month, the number of samples in the month, and two constants. The constants are set separately for each source of precipitation estimate (such as "raingauge") by calibration at selected ground sites. We discuss recent work validating the random error estimates to highlight the successes and limitations of this first-generation approach. We then consider what information is needed from the individual sensor algorithms to facilitate additional accuracy in the estimation of random errors across the time/space span of climate regimes which a global estimation system must handle. In addition, the thorny issue of estimating bias is raised. Finally, the role of error estimates (and the qualitative errors!) in creating combinations of precipitation estimates from different individual sensors is discussed. This issue is particularly important when fine scales in space and time are being considered, say the 0.25 x 0.25-deg 3-hourly estimates in the MPA.

Huffman, G. J.↗

NASA NTRS1995

Global Stratigraphy of Venus: Analysis of a Random Sample of Thirty-Six Test Areas

The age relations between 36 impact craters with dark paraboloids and other geologic units and structures at these localities have been studied through photogeologic analysis of Magellan SAR images of the surface of Venus. Geologic settings in all 36 sites, about 1000 x 1000 km each, could be characterized using only 10 different terrain units and six types of structures. These units and structures form a major stratigraphic and geologic sequence (from oldest to youngest): (1) tessera terrain; (2) densely fractured terrains associated with coronae and in the form of remnants among plains; (3) fractured and ridged plains and ridge belts; (4) plains with wrinkle ridges; (5) ridges associated with coronae annulae and ridges of arachnoid annulae which are contemporary with wrinkle ridges of the ridged plains; (6) smooth and lobate plains; (7) fractures of coronae annulae, and fractures not related to coronae annulae, which disrupt ridged and smooth plains; (8) rift-associated fractures; and (9) craters with associated dark paraboloids, which represent the youngest 1O% of the Venus impact crater population (Campbell et al.), and are on top of all volcanic and tectonic units except the youngest episodes of rift-associated fracturing and volcanism; surficial streaks and patches are approximately contemporary with dark-paraboloid craters. Mapping of such units and structures in 36 randomly distributed large regions (each approximately 10(exp 6) sq km) shows evidence for a distinctive regional and global stratigraphic and geologic sequence. On the basis of this sequence we have developed a model that illustrates several major themes in the history of Venus. Most of the history of Venus (that of its first 80% or so) is not preserved in the surface geomorphological record. The major deformation associated with tessera formation in the period sometime between 0.5-1.0 b.y. ago (Ivanov and Basilevsky) is the earliest event detected. In the terminal stages of tessera fon-nation, extensive parallel linear graben swarms representing a change in the style of deformation from shortening to extension were formed on the tessera and on some volcanic plains that were emplaced just after, and perhaps also during the latter stages of the major compressional phase of tessera emplacement. Our stratigraphic analyses suggest that following tessera formation, extensive volcanic flooding resurfaced at least 85% of the planet in the form of the presently-ridged and fractured plains. Several lines of evidence favor a high flux in the post-tessera period but we have no independent evidence for the absolute duration of ridged plains emplacement. During this time, the net state of stress in the lithosphere apparently changed from extensional to compressional, first in the form of extensive ridge belt development, followed by the formation of extensive wrinkle ridges on the flow units. Subsequently, there occurred local emplacement of smooth and lobate plains units which are presently essentially undefortned. The major events in the latest 10% of the presently preserved history of Venus (less than 50 m.y. ago) are continued rifting and some associated volcanism, and the redistribution of eolian material largely derived from impact crater deposits.

Basilevsky, Alexander T.↗

NASA NTRS1986

Mapping permafrost in the boreal forest with Thematic Mapper satellite data

A geographic data base incorporating Landsat TM data was used to develop and evaluate logistic discriminant functions for predicting the distribution of permafrost in a boreal forest watershed. The data base included both satellite-derived information and ancillary map data. Five permafrost classifications were developed from a stratified random sample of the data base and evaluated by comparison with a photo-interpreted permafrost map using contingency table analysis and soil temperatures recorded at sites within the watershed. A classification using a TM thermal band and a TM-derived vegetation map as independent variables yielded the highest mapping accuracy for all permafrost categories.

Morrissey, L. A.↗

NASA NTRS1980

Evaluation of Bayesian Sequential Proportion Estimation Using Analyst Labels

The author has identified the following significant results. A total of ten Large Area Crop Inventory Experiment Phase 3 blind sites and analyst-interpreter labels were used in a study to compare proportional estimates obtained by the Bayes sequential procedure with estimates obtained from simple random sampling and from Procedure 1. The analyst error rate using the Bayes technique was shown to be no greater than that for the simple random sampling. Also, the segment proportion estimates produced using this technique had smaller bias and mean squared errors than the estimates produced using either simple random sampling or Procedure 1.

Lennington, R. K.↗