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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Improvement of water resources management through the use of satellites flood plain delineation

The delineation of flood-prone areas is an important activity in several parts of the world. Conventional methods map the topography surrounding the river via ground surveys and supplementary aerophotography. The conventional method costs approximately $2,000 per river-kilometer, is laborious and time-consuming. ERTS information can supplement this method by two complementary techniques: (1) the dynamic method images the floods as they occur, exploiting the fact that visible evidence of inundation remains for a substantial period after the high waters have receded; (2) the static method utilizes the fact that several flood plains have been found recognizable on ERTS imagery from distinctive, permanent indicators left by previous floods. For areas whose full development is still in the future, the dynamic method allows the gradual buildup with time of a flood plain map, by simply correlating existing ERTS imagery. The static method allows in several areas, a first-cut indication, of proneness to floods.

Castruccio, P. A.↗
NASA NTRS1982

Delineation of cold-prone areas using nighttime SMS/GOES thermal data Effects of soils and water

Infrared digital data from geostationary satellites were used to demonstrate the usefulness of remotely sensed surface temperature data to delineate microscale and mesoscale climates. Nocturnal winter data (December-February) from 1976-77 to 1978-79 over Florida revealed noticeable contrasts in surface temperature patterns. Colder areas were associated with low soil moisture content in the upper layers of excessively drained and well drained sandy soils, whereas warmer areas were associated with bodies of water, wetlands, or poorly drained soils. An unexpected surface temperature pattern for one night where the north-central Florida climatic zone was colder than the north Florida climatic zone was found to be caused by differences in antecedent frontal rainfall. Differences in surface radiant energy fluxes over these two areas at 0200 EST 20 December 1977, based on average satellite-sensed surface temperatures, were compared with differences in soil heat fluxes that were computed from 1.5 m climatological temperatures and soil thermal properties by use of a simplified surface energy balance equation.

Chen, E.↗
NASA NTRS1983

The utilization of Nimbus-7 SMMR measurements to delineate rainfall over land

Approaches for developing an improved passive microwave technique to delineate rain from wet land surfaces are considered, and an investigation is conducted with the objective to study the application of these ideas with empirical data. The investigation includes a statistical analysis of Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) 37.0, 18.0, and 10.7 GHz data. The possibility was assessed to make use of the 18.0 and 10.7 GHz channels in order to reduce the ambiguities found in the 37.0 GHz radiometer data for differentiating rainfall areas from wet land surfaces. It was found, however, that none of the SMMR channels could differentiate rain from wet or dry land when surface temperatures were less than 15 C. It appears that an improved rainfall-over-land detection technique could be developed by two different methods, utilizing both satellite infrared and multifrequency dual polarized passive microwave data.

Rodgers, E.↗
NASA NTRS1984

Delineation of major geologic structures in Turkey using SIR-B data

Shuttle Imaging Radar-B (SIR-B) images of well mapped segments of major faults, such as the North Anatolian Fault (NAF) and East Anatolian Fault (EAF) will be studied to identify the prominent signatures that characterize the fault zones for those specific regions. The information will be used to delineate the unmapped fault zones in areas with similar geological and geomorphological properties. The data obtained from SIR-B images will be compared and correlated with the LANDSAT thematic mapper and seismicity alignments based on well constrained earthquake epicenters.

Toksoz, M. N.↗
NASA NTRS1983

Correlation of infrared reflectance ratios at 2.3 microns/1.6 micron and 1.1 micron/1.6 micron with delta O-18 values delineating fossil hydrothermal systems in the Idaho batholith

Reflectance ratios from laboratory spectra and airborne multispectral images are found to be strongly correlated with delta O-18 values of granite rocks in the Idaho batholith. The correlation is largely a result of interactions between hot water and rock, which lowered the delta O-18 values of the rocks and produced secondary hydrous material. Maps of the ratio of reflectivities at 2.3 and 1.6 microns should delineate fossil hydrothermal systems and provide estimates of alteration intensity. However, hydrous minerals produced during deuteric alteration or weathering cannot be unambiguously distinguished in remotely sensed images from the products of propylitic alteration without the use of narrow-band scanners. The reflectivity at 1.6 micron is strongly correlated with rock density and may be useful in distinguishing rock types in granitic terranes.

Gillespie, A. R.↗
NASA NTRS1984

Delineating mid- and low-level water vapor patterns in pre-convective environments using VAS moisture channels

Infrared and visible imagery from VAS are used to delineate mid- and lower-tropospheric moisture fields for a variety of severe storm cases in the southern and central United States. The ability of sequences of images to isolate areas of large negative vertical moisture gradients and apparent convective instability prior to the onset of convective storms is assessed. A variety of image combination procedures are used to deduce the stability fields which are then compared with the available radiosonde data. The results for several severe storm cases indicate that VAS can detect mid- and low-level mesoscale water vapor fields as distinct radiometric signals. The VAS imagery shows a strong tendency for thunderstorms to develop along the edges of bands of midlevel dryness as they overtake either preexisting or developing low-level moisture maxima. Image sequences depict the speed with which deep moist and dry layers can develop and move.

Petersen, R. A.↗
NASA NTRS1987

The delineation and interpretation of the Earth's gravity field

The geoid and topographic fields of the central Pacific were delineated and shown to correlate closely at intermediate wavelengths (500 to 2500 km). The associated admittance shows that anomalies having wavelengths less than about 1000 km are probably supported by the elastic strength of the lithosphere. Larger wavelength anomalies are due to dynamic effects in the sublithosphere. Direct modeling of small scale convection in the asthenosphere shows that the amplitudes of observed geoid and topographic anomalies can be independently matched, but that the observed admittance cannot. Only by imposing an initial regional variation in the thermal regime is it possible to match the admittance. It is proposed that this variation may be due to differences in the onset time of convection beneath the lithosphere of different ages. That is, convection beneath thickening lithosphere is strongly dependent on the rate of thickening (V) relative to the rise time for convection. The critical Rayleigh number contains the length scale K/V, where K is thermal diffusivity. Young, fast growing lithosphere stabilizes the underlying asthenosphere unless it has an unusually low viscosity. Lithosphere of different age, separated by fracture zones, will go unstable at different times, producing regional horizontal temperature gradient that may strongly influence convection. Laboratory and numerical experiments are proposed to study this form of convection and its influence on the geoid.

Marsh, Bruce D.↗
NASA NTRS1989

Computer-aided boundary delineation of agricultural lands

The National Agricultural Statistics Service of the United States Department of Agriculture (USDA) presently uses labor-intensive aerial photographic interpretation techniques to divide large geographical areas into manageable-sized units for estimating domestic crop and livestock production. Prototype software, the computer-aided stratification (CAS) system, was developed to automate the procedure, and currently runs on a Sun-based image processing system. With a background display of LANDSAT Thematic Mapper and United States Geological Survey Digital Line Graph data, the operator uses a cursor to delineate agricultural areas, called sampling units, which are assigned to strata of land-use and land-cover types. The resultant stratified sampling units are used as input into subsequent USDA sampling procedures. As a test, three counties in Missouri were chosen for application of the CAS procedures. Subsequent analysis indicates that CAS was five times faster in creating sampling units than the manual techniques were.

Cheng, Thomas D.↗
NASA NTRS1992

Computer Aids Delineation Of Boundaries In Farmlands

Computer-aided stratification (CAS) procedure developmental procedure of image-processing computer equipment and programs partly automating delineation of boundaries between areas. These areas, "primary sampling units", are images of primarily agricultural lands composed by melding digital Landsat Thematic Mapper data and Digital Line Graph data from United States Geological Survey. CAS output data used as inputs for subsequent sampling procedures from which statistics on uses of agricultural lands developed.

Slyle, R.↗
NASA NTRS1992

Interactive boundary delineation of agricultural lands using graphics workstations

A review is presented of the computer-assisted stratification and sampling (CASS) system developed to delineate the boundaries of sample units for survey procedures. CASS stratifies the sampling units by land-cover and land-use type, employing image-processing software and hardware. This procedure generates coverage areas and the boundaries of stratified sampling units that are utilized for subsequent sampling procedures from which agricultural statistics are developed.

Cheng, Thomas D.↗
NASA NTRS2010

Combining Modis and Quikscat Data to Delineate Surface and Near-Surface Melt on the Greenland Ice Sheet

Over the last two decades, increasing melt has been measured on the Greenland Ice Sheet, along with mass loss as determined from satellite data, Monitoring the state of the Greenland Ice Sheet becomes critical especially because it is actively losing mass, and the ice sheet has a sea-level rise potential of 7 in. However measurement of the extent of surface melt varies depending on the sensor used, whether it is passive or active microwave or visible or thermal infrared. We have used remote-sensing data products to study surface and near-surface melt characteristics of the Greenland Ice Sheet. We present a blended MODIS-QS melt daily product for 2007 [1]. The products, including Moderate Resolution Imaging Spectroradiometer (MODIS) daily land-surface temperature (LST) and a special daily melt product derived from the QuikSCAT (QS) scatterometer [2,3] show consistency in delineating the melt boundaries on a daily basis in the 2007 melt season [I], though some differences are identified. An assessment of maximum melt area for the 2007 melt shows that the QSCAT product detects a greater amount of melt (862,769 square kilometers) than is detected by the MODIS LST product (766,184 square kilometers). The discrepancy is largely because the QS product can detect both surface and near-surface melt and the QS product captures melt if it occurred anytime during the day while the MODIS product is obtained from a point in time on a given day. However on a daily bases, other factors influence the measurement of melt extent. In this work we employ the digital-elevation model of Bamber et al. [4] along with the National Centers for Environmental Prediction (NCEP) data to study some areas and time periods in detail during the 2007 melt season. We focus on times in which the QS and MODIS LST products do not agree exactly. We use NCEP and elevation data to analyze the atmospheric factors forcing the melt process, to gain an improved understanding of the conditions that lead to melt and melt persistence, and our ability to capture surface melt accurately using MODIS and QS data.

Hall, Dorothy K.↗
NASA NTRS2015

Delineating the Impact of Weightlessness on Human Physiology Using Computational Models

Microgravity environment has profound effects on several important human physiological systems. The impact of weightlessness is usually indirect as mediated by changes in the biological fluid flow and transport and alterations in the deformation and stress fields of the compliant tissues. In this context, Fluid-Structural and Fluid-Solid Interaction models provide a valuable tool in delineating the physical origins of the physiological changes so that systematic countermeasures can be devised to reduce their adverse effects. In this presentation, impact of gravity on three human physiological systems will be considered. The first case involves prediction of cardiac shape change and altered stress distributions in weightlessness. The second, presents a fluid-structural-interaction (FSI) analysis and assessment of the vestibular system and explores the reasons behind the unexpected microgravity caloric stimulation test results performed aboard the Skylab. The last case investigates renal stone development in microgravity and the possible impact of re-entry into partial gravity on the development and transport of nucleating, growing, and agglomerating renal calculi in the nephron. Finally, the need for model validation and verification and application of the FSI models to assess the effects of Artificial Gravity (AG) are also briefly discussed.

Computational Models↗
NASA NTRS2016

DeepSAT: A Deep Learning Approach to Tree-Cover Delineation in 1-m NAIP Imagery for the Continental United States

High resolution tree cover classification maps are needed to increase the accuracy of current land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) tree cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agriculture Imagery Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~65 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. Using the NASA Earth Exchange (NEX) initiative, we have developed an end-to-end architecture by integrating a segmentation module based on Statistical Region Merging, a classification algorithm using Deep Belief Network and a structured prediction algorithm using Conditional Random Fields to integrate the results from the segmentation and classification modules to create per-pixel class labels. The training process is scaled up using the power of GPUs and the prediction is scaled to quarter million NAIP tiles spanning the whole of Continental United States using the NEX HPC supercomputing cluster. An initial pilot over the state of California spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles has produced true positive rates of around 88 percent for fragmented forests and 74 percent for urban tree cover areas, with false positive rates lower than 2 percent for both landscapes.

Imagery↗
NASA NTRS2024

Cape Hatteras Ecological Conservation: Delineating Shoreline and Mapping Change Along the Cape Hatteras National Seashore for Coastline Management and Transportation Corridor Adaptation Strategies

The National Park Service at Cape Hatteras National Seashore works to protect North Carolina’s Outer Banks where frequent storms bring heavy winds and flooding, leading to overwash events on the main highway, North Carolina Highway 12. Shorelines are susceptible to erosion directly affecting transportation and housing infrastructures. Storm events can disrupt transportation on NC-12 and ferry service from Ocracoke Island to Hatteras Island, leaving inhabitants stranded on Ocracoke Island for indefinite amounts of time. The National Park Service’s current decision-making practices involve mitigating infrastructure damage by enlisting the help of North Carolina’s Department of Transportation and finding ways to relocate this infrastructure, as well as dredging and sediment placement that support beach nourishment efforts. Our NASA DEVELOP team partnered with the National Park Service to explore the use of optical data to delineate shoreline and map coastline change from 2014 to 2024. We used Earth observations collected by Landsat 8 Operational Land Imager, Landsat 9 Operational Land Imager-2, and Sentinel-2 MultiSpectral instrument to support decision-making related to prioritizing strategic planning for transportation corridor adaptations including potential relocation of infrastructure, and beach nourishment efforts. We derived coastline maps by consolidating images from each year to create composite images for winter and summer coastline seasonal oscillation patterns. The results highlight shoreline loss over the ~10-year study period, and the difference in shoreline inundation in the winter and summer seasons. These observations create a better understanding of successful mitigation efforts and allow the National Park Service to continue to focus on plans for infrastructure updates.

Ella Haugen↗