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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Contamination effects from materials selected for spacecraft instruments

Measurements of the Total Mass Loss (TML) and the Collected Volatile Condensable Materials (CVCM) are used as a guide for selecting those materials being low in outgassing. A contamination modelling method utilizing the data and also the rate at which a material outgasses in a system with a known conductance has been developed and has been applied to the problem encountered with the Very High Resolution Radiometer (VHRR). Recently, the contamination model has been applied to the problem with the 5th band of the Multi-Spectral Scanner on the Landsat-C satellite. In the MSS design, the volumes involved and their respective conductance in a molecular flow field demonstrated that the water vapor adsorbed and absorbed by an epoxy paint was being pumped off and re-ad(b)sorbed, with a resultant very slow loss of water during each degassing temperature cycle of the instrument's cooler. Recommendations for designing improved coolers are presented.

Heslin, T. M.↗
NASA NTRS1980

Coordinated aircraft and ship surveys for determining impact of river inputs on great lakes waters. Remote sensing results

The remote sensing results of aircraft and ship surveys for determining the impact of river effluents on Great Lakes waters are presented. Aircraft multi-spectral scanner data were acquired throughout the spring and early summer of 1976 at five locations: the West Basin of Lake Erie, Genesee River - Lake Ontario, Menomonee River - Lake Michigan, Grand River - Lake Michigan, and Nemadji River - Lake Superior. Multispectral scanner data and ship surface sample data are correlated resulting in 40 contour plots showing large-scale distributions of parameters such as total suspended solids, turbidity, Secchi depth, nutrients, salts, and dissolved oxygen. The imagery and data analysis are used to determine the transport and dispersion of materials from the river discharges, especially during spring runoff events, and to evaluate the relative effects of river input, resuspension, and shore erosion. Twenty-five LANDSAT satellite images of the study sites are also included in the analysis. Examples of the use of remote sensing data in quantitatively estimating total particulate loading in determining water types, in assessing transport across international boundaries, and in supporting numerical current modeling are included. The importance of coordination of aircraft and ship lake surveys is discussed, including the use of telefacsimile for the transmission of imagery.

Raquet, C. A.↗
NASA NTRS1978

Multiple-frame, full resolution Landsat mosaicking to standard map projections

Landsat digital data are presently available by frames whose size and location are determined by satellite orbit. The utility of Landsat data was increased by the image processing support for JPL's planetary program which provided the basic software and procedures necessary for image mosaicking. The computer software has been extended to perform this task on Landsat Multi-spectral scanner imagery and a ten frame digital mosaic of the Southern California desert has been completed. Major processing steps include location of geographic points in the digital frame and of common geographic points in adjacent frames, conversion to a map projection, lateral 'rubber sheet' correction of the digital frames, brightness correction of adjacent frames, and mosaicking of the frames to eliminate overlap and produce a single large frame.

Zobrist, A. L.↗
NASA NTRS1979

Signature evaluation of natural targets using high spectral resolution techniques

The concept of 'spectral signature' identification has been applied to LANDSAT and other broad-band multi-spectral scanner data to classify various materials on the earth's surface. A large amount of the spectral information available is invisible, however, to the broad-band sensors. Although the natural targets of interest in remote sensing do not exhibit fine line features such as those associated with gaseous media, there is significant information to be extracted from smoothly varying spectral reflection functions of most natural targets. Subtle variations observed recently in the high resolution 'spectral signatures' of vegetation targets, in particular, promise to open new avenues of application using higher spectral and radiometric resolution techniques. This research was accomplished using a 500-band spectroradiometer system specially adapted to rapid airborne operations

Collins, W.↗
NASA NTRS1980

A review of future remote sensing satellite capabilities

Existing, planned and future NASA capabilities in the field of remote sensing satellites are reviewed in relation to the use of remote sensing techniques for the identification of irrigated lands. The status of the currently operational Landsat 2 and 3 satellites is indicated, and it is noted that Landsat D is scheduled to be in operation in two years. The orbital configuration and instrumentation of Landsat D are discussed, with particular attention given to the thematic mapper, which is expected to improve capabilities for small field identification and crop discrimination and classification. Future possibilities are then considered, including a multi-spectral resource sampler supplying high spatial and temporal resolution data possibly based on push-broom scanning, Shuttle-maintained Landsat follow-on missions, a satellite to obtain high-resolution stereoscopic data, further satellites providing all-weather radar capability and the Large Format Camera.

Calabrese, M. A.↗
NASA NTRS1980

Evaluation of the effects of varying moisture contents on microwave thermal emissions from agriculture fields

Three tasks related to soil moisture sensing at microwave wavelengths were undertaken: (1) analysis of data at L, X and K sub 21 band wavelengths over bare and vegetated fields from the 1975 NASA sponsored flight experiment over Phoenix, Arizona; (2) modeling of vegetation canopy at microwave wavelengths taking into consideration both absorption and volume scattering effects; and (3) investigation of overall atmospheric effects at microwave wavelengths that can affect soil moisture retrieval. Data for both bare and vegetated fields are found to agree well with theoretical estimates. It is observed that the retrieval of surface and near surface soil moisture information is feasible through multi-spectral and multi-temporal analysis. It is also established that at long wavelengths, which are optimal for surface sensing, atmospheric effects are generally minimal. At shorter wavelengths, which are optimal for atmosheric retrieval, the background surface properties are also established.

Burke, H. H. K.↗
NASA NTRS1981

Oregon trails revisted

Oregon State University's Environmental Remote Sensing Applications Laboratory (ERSAL) has six full-time researchers with expertise in a variety of biological, Earth, atmospheric and computer sciences as well as image interpretation and statistical techniques. The primary emphasis of the ERSAL research and demonstration program is the development and application of remote sensing technology in operational resource management programs. LANDSAT multi-spectral, multi-date digital data and imagery are utilized in concert with high altitude NASA-acquired photography, low altitude ERSAL-acquired photography, and field observations and data to provide customized, inexpensive and useful final products. Synopses are given of 9 applications projects conducted in Oregon.

Lewis, A. J.↗
NASA NTRS1981

Status and outlook for NASA's Land Remote Sensing Program

Both LANDSAT 2 and LANDSAT 3 are currently in operational status following recovery from technical problems. The LANDSAT D program continues NASA's R&D with the dual objectives of assessing the capabilities of the thematic mapper sensor and evaluating the requirements for an operational land observing system. LANDSAT D' will not be launched until LANDSAT D ceases operation, to provide data continuity through 1988. Future NASA remote sensing programs will continue to emphasize research, technology development, cooperative projects with end users of data and cooperation with the National Oceanic and Atmospheric Administration (NOAA) on transition to an operational land observing system. Technology development should extend the results of research to practical applications through improved ground data processing and information extraction techniques and development of new sensors such as the solid state multi-spectral linear array.

Weinstein, R. H.↗
NASA NTRS1983

FUNSTAT and statistical image representations

General ideas of functional statistical inference analysis of one sample and two samples, univariate and bivariate are outlined. ONESAM program is applied to analyze the univariate probability distributions of multi-spectral image data.

Parzen, E.↗
NASA NTRS1982

The use of VAS satellite data in weather analysis, prediction and diagnosis

Imagery available with the Goes satellite visible-IR spin-scan radiometer (VISSR) atmospheric sounders (VAS) are examined in terms of mid- and low-tropospheric moisture sensing and mesoscale soundings. The VAS can be operated in a Dwell Sounding mode (DS) involving preprogrammed scanning of a specific area using any number of combinations of 12 channels between 4-15 microns. A second, multi-spectral imaging mode (MSI) comprises operation of two IR channels simultaneously when time constraints are in effect. Case studies are presented to demonstrate the effectiveness of VAS imagery for characterizing mesoscale moisture conditions when identifying severe storms. The moisture patterns of the upper and lower troposphere are made visible, and a 6.7 micron channel image can be overlaid on a low level moisture field to delineate fields of potential instability.

Petersen, R. A.↗
NASA NTRS1983

Sensor data for forest policy information

NASA-Ames Research Center has investigated the role and performance capabilities of the Landsat Multi-Spectral Scanner (MSS) for forest policy analysis for the past four years in cooperation with the California Department of Forestry. A thorough series of studies, from a statewide land cover map to smaller, highly detailed studies including collateral data, have been conducted with a view to comprehensive forest policy needs. The strengths and limitations of MSS data have been evaluated. Some observations about the information needed from new satellite sensors such as the Thematic Mapper are discussed against this background.

Peterson, D. L.↗
NASA NTRS1983

Use of VAS multispectral data for sea surface temperature determination

The Visible Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) is a radiometer possessing eight visible channel detectors and six thermal detectors that sense infrared radiation in 12 spectral bands. Housed in the GOES satellite, VAS spins in a west to east direction at 100 rpm and achieves spatial coverage at resolutions of 1 km in the visible and 7 or 14 km in the infrared by stepping a scan mirror in a north to south direction. Designed for multipurpose applications, the VAS can be operated in two different modes: (1) a multi-spectral imaging (MSI) mode, and (2) a dwell sounding (DS) mode. The MSI mode of operation is used for sea surface temperature (SST) determination. Currently, a full-disk MSI image for SST determination is received every hour, 18 hours a day during weekdays. This MSI mode of operation for SST consists of data obtained from wavelengths centered at 3.9 microns (channel 12), 11.6 microns (channel 8), and 12.6 microns (channel 7) as well as visible data.

Bates, J.↗
NASA NTRS1984

Objective assessment of Advanced Very High Resolution Radiometer data for land cover mapping

The validity of using data from the Advanced Very High Resolution Radiometer (AVHRR) of the satellites NOAA-6 and NOAA-7 for land cover mapping is assessed by making comparisons with much higher resolution LANDSAT multi-spectral scanner (MSS) data. Near synchronous data for both systems are analysed for test sites in the Imperial Valley, California, the Nile Delta, and southern Italy. The results strongly indicate that despite the very coarse resolution of the AVHRR data compared with conventional MSS data they are sufficiently strongly correlated to suggest that the former have significant potential for land cover mapping, especially at small scales and for large areas. Hence the outstanding benefits of AVHRR data, namely their high temporal frequency, relative cheapness and low data volumes for image processing, may readily be taken advantage of for such tasks.

Townshend, J. R. G.↗
NASA NTRS1984

Remote sensing of weather and climate parameters from HIRS2/MSU on Tiros-N

At the Goddard Laboratory for Atmospheric Sciences (GLAS) a physically based satellite temperature sounding retrieval system, involving the simultaneous analysis of HIRS2 and MSU sounding data, has been developed for determining atmospheric and surface conditions which are consistent with the observed radiances. In addition to determining accurate atmospheric temperature profiles even in the presence of cloud contamination, the system provides global estimates of day and night sea or land surface temperatures, snow and ice cover, and parameters related to cloud cover. The inverse radiative transfer equation approach to the multi-spectral analysis of the data, and details of its implementation, are described. Ice, snow, and cloud fields derived for January 1979 are consistent with other measures of similar parameters obtained from AVHRR and SMMR. Monthly mean sea-surface temperature fields agree with those derived from ship and buoy measurements to 0.5 C.

Susskind, J.↗
NASA NTRS1984

Investigation of SIR-B images for lithologic mapping

It is immediately apparent from the examination of almost any synthetic aperture radar (SAR) data that the radar return is primarily a function of the topographic relief. Yet radar reflectance is dependent on both surface roughness and the dielectric constant of the surface material. These two parameters can in many cases be related to lithologic units. Thus, if the first-order terrain effects due to topographic relief could (in essence) be removed from the radar image, the SAR data might well be used for lithologic discrimination. Such an approach is evaluated. Landsat Thematic Mapper data along with ground truth are used to define training cells that characterize the various lithologic units in the area. By aggregating the radar data for these cells, curves of radar reflectance versus local incidence are estimated. The curves are then used to classify the test area. The results are compared with lithologic classification based upon multi-spectral (visible and infrared) data.

Parr, J. T.↗
NASA NTRS1984

Comparison of existing digital image analysis systems for the analysis of Thematic Mapper data

Most existing image analysis systems were designed with the Landsat Multi-Spectral Scanner in mind, leaving open the question of whether or not these systems could adequately process Thematic Mapper data. In this report, both hardware and software systems have been evaluated for compatibility with TM data. Lack of spectral analysis capability was not found to be a problem, though techniques for spatial filtering and texture varied. Computer processing speed and data storage of currently existing mini-computer based systems may be less than adequate. Upgrading to more powerful hardware may be required for many TM applications.

Likens, W. C.↗
NASA NTRS2026

Satellite Optical Remote Sensing of Clouds and Aerosols: From Particle Single-Scattering and Gaseous Absorption Through Radiative Transfer to Retrieval Products

Clouds and aerosols are fundamental regulators of Earth’s radiation budget and climate system, influencing both solar and terrestrial radiation through scattering, absorption, and emission processes. Accurate characterization of their physical and radiative properties from space requires a rigorous understanding of particle single-scattering, gaseous absorption, and radiative transfer in the atmosphere, as well as reliable inversion methods. This review synthesizes the physical foundations and algorithmic implementations of satellite-based passive optical remote sensing of clouds and aerosols, spanning the ultraviolet to thermal infrared spectral range. Beginning with electromagnetic scattering theory and state-of-the-art methods for computing single-scattering by nonspherical particles and computationally efficient methods for accounting for atmospheric absorption, we discuss the radiative transfer framework underpinning cloud and aerosol retrievals. The connection between single-scattering and multiple-scattering is rigorously formulated. We then summarize operational and research-grade retrieval techniques, including cloud masking and thermodynamic phase determination, CO₂ slicing for cloud-top pressure, the Nakajima-King shortwave bi-spectral, and infrared split-window approaches for cloud optical thickness and effective particle size, inversion algorithms for determining aerosol properties from multi-spectral and/or multi-angle radiometric and polarimetric measurements, and active-passive sensing synergy. Examples of the global cloud and aerosol climatologies are illustrated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR). Furthermore, the unique strengths of active remote sensing techniques based on spaceborne lidar observations are briefly elaborated in the context of studying ice clouds composed of randomly and horizontally oriented ice crystals, which is a significant challenge for conventional passive remote sensing techniques. By connecting physical theory to practical retrievals, this review highlights both the maturity of current methodologies and the remaining challenges in reducing uncertainties in particle morphology, vertical structure, absorption, and aerosol-cloud interactions. Furthermore, the impact of artificial intelligence (AI) on atmospheric remote sensing is briefly addressed.

Aerosols↗
DOE OSTI2025

Hyper Spectral Anomaly Detection

Anomaly detection is a common machine learning (ML) task with growing importance in the fields of imaging, quality assurance, and multiple security related disciplines. Anomaly detection is more difficult than traditional machine learning methods due to the inherent unlabeled nature of the datasets. Existing anomaly detection architectures commonly face challenges with explainability, retaining information related to the relational structure of the data, and false positive rates. Hyperspectral Imaging Anomaly Detection (HSI) is a statistical model that employs vertex and edge weighted graphs to preserve the data’s relationships on different topographical scales. The model is able to generalize from anomaly detection in 2D images to novel datasets related to cyber-security. Furthermore, the use of multi-spectral and other filtering methods results in fewer false positives and increases the explainability of model predictions. When applying HSI to cyber-security datasets, we are able to successfully detect malicious activity with a relatively high degree of accuracy.

97 - MATHEMATICS AND COMPUTING↗