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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Digital image data sets for remote sensing instruction

Several sets of LANDSAT image segments and a set of simple image processing programs operating in batch mode are being used to teach an introductory course in digital image analysis and classification. The image data sets contain only a small number of pixels and can be run quickly on most university computing systems. A number of image data sets derived from the raw spectral bands (smoothed data sets, band ratios and texture data sets) allows the student to examine and include these extracted variables in the classification process. Another data set consists of three registered LANDSAT image segments for three different dates so that the student may experiment with multitemporal data processing. The three LANDSAT scenes used in the class are described and the image data sets available for class exercises are listed.

Eyton, J. R.↗
NASA NTRS1985

Imaging spectrometry for earth remote sensing

Initial results of the novel remote earth sensing technique of imaging spectrometry, which is technically feasible from both spacecraft and aircraft platforms, indicate that the direct identification of surface materials on a picture-element basis is possible through proper sampling of absorption features in the reflectance spectrum. Sensors of this type are able to acquire images simultaneously in 100-200 contiguous spectral bands. Computerized data reduction and storage techniques are available for the large data sets thus generated, and novel analytic techniques are under development to maximize information content extraction.

Goetz, A. F. H.↗
NASA NTRS2000

Technical Report Series on the Boreal Ecosystem-Atmosphere Study (BOREAS) RSS-19 1994 CASI At-Sensor Radiance and Reflectance Images

The Remote Sensing Science (RSS)-19 team collected Compact Airborne Spectrographic Imager (CASI) images from the Chieftain Navaho aircraft in order to observe the seasonal change in the radiometric reflectance properties of the boreal forest landscape. CASI was deployed as a site-specific optical sensor during Boreal Ecosystem-Atmosphere Study (BOREAS) field campaigns. Image data were collected with CASI on 36 days during five field campaigns between February and September 1994, primarily at flux tower sites located at study sites near Thompson, Manitoba, and Prince Albert, Saskatchewan. A variety of CASI data collection strategies were used to meet the following scientific objectives: 1) canopy bidirectional reflectance, 2) canopy biochemistry, 3) spatial variability, and 4) estimates of up and downwelling Photosynthetically Active Radiation (PAR) and spectral albedo, as well as changes along transects across lakes and transects the Northern Study Area (NSA) and Southern Study Area (SSA). The images are stored as binary image files. A subset of the 1994 CASI acquisitions have been compressed and included on the BOREAS CD-ROM set. This subset includes three images for the NSA-OBS (Old Black Spruce) site on 06 Jun 94, 08 Aug 94, and 06 Sep 94, one image for the SSA-OBS site on 24 Jul 94; and one image for the NSA-Fen site on 08 Aug 94. The CASI imagery on the BOREAS CD-ROMs have been compressed using the Gzip program. The rest of the 1994 BOREAS CASI archive are not contained on the BOREAS CD-ROM set. Inventory listing files are supplied on the CD-ROM to inform users of the data that were collected. The RSS-19 1994 CASI images are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Miller, John↗
NASA NTRS1991

Acousto-optic tunable filter imaging spectrometers

A remote sensing multispectral imaging instrument is being developed that uses a high resolution, fast programmable acoustooptic tunable filter (AOTF) as the spectral bandpass filter. A compact and fully computer controllable AOTF-based imaging spectrometer that operates in the visible wavelength range (0.5-0.8 microns) has been built and tested with success. A second imaging spectrometer operating in the near-infrared wavelength range (1.2-2.4 microns) is also under experimental investigation. The design criteria meeting various system issues, such as imaging quality, spectral response, and field of view (FOV), are discussed. An experiment using this AOTF imaging spectrometer breadboard is described.

Chao, Tien-Hsin↗
DOE OSTI2021

Do Remote Camera Arrangements and Image Capture Settings Improve Individual Identification of Golden Eagles?

Individual identification of animals from camera traps has become an important task in wildlife research, but camera deployment methods often do not facilitate this important undertaking. Identification of individual golden eagles (Aquila chrysaetos) is possible using uniquely marked rectrices, but no studies have explored methods to maximize the rate of individual identification from camera images. Furthermore, our objectives were to assess whether different camera heights (1 m vs. 3 m), image capture settings (one image after a 1-min delay vs. burst of 5 images after a 30 sec delay), and arrangements relative to bait (dorsally vs. ventrally aimed) affected views of rectrices on golden eagles and our ability to identify individuals. We conducted our study from 15 December 2016 to 3 March 2017 on the Savannah River Site, South Carolina. First, we developed a scoring system based on views of rectrices and used a linear mixed-effects model to compare image scores among different camera arrangements and image settings. Next, after identifying individual eagles, we used generalized linear mixed-effects models to compare total individual eagle detections, total days an individual was detected, and probability of obtaining an unknown individual identification among camera arrangements and settings. Overall, we scored a total of 27,499 images, with 8,083 providing views of marked rectrices that allowed identification of 18 individual eagles. Average image scores and proportion of images suitable for individual identification were higher from elevated (3 m) camera arrangements than standard arrangements (1 m) across sites. Regardless of camera height, faster frequency of image capture provided more images that could be used to identify individuals and the most trap days per individual. Researchers and managers should consider deploying elevated cameras traps with faster frequency of image capture to improve data quality and potential for analysis of golden eagle populations and trends across the species’ range.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2013

Airborne Remote Sensing for Earth Science Applications

Topics covered include: Passive Remote Sensing Methods, Imaging Spectroscopy Approach, Remote Measurement via Spectral Fitting, Imaging Spectroscopy Mapping Wetland Dominants 2010 LA (AVIRIS), Deepwater Horizon Response I, Deepwater Horizon Response II, AVIRIS Ocean Color Studies.

AVIRIS: Airborne Imaging Spectrometer↗
NASA NTRS1984

Image variance and spatial structure in remotely sensed scenes

Digital images derived by scanning air photos and through acquiring aircraft and spcecraft scanner data were studied. Results show that spatial structure in scenes can be measured and logically related to texture and image variance. Imagery data were used of a South Dakota forest; a housing development in Canoga Park, California; an agricltural area in Mississppi, Louisiana, Kentucky, and Tennessee; the city of Washington, D.C.; and the Klamath National Forest. Local variance, measured as the average standard deviation of brightness values within a three-by-three moving window, reaches a peak at a resolution cell size about two-thirds to three-fourths the size of the objects within the scene. If objects are smaller than the resolution cell size of the image, this peak does not occur and local variance simply decreases with increasing resolution as spatial averaging occurs. Variograms can also reveal the size, shape, and density of objects in the scene.

Woodcock, C. E.↗
NASA NTRS1972

Imaging radar techniques for remote sensing applications.

The basic concepts of fine-resolution, imaging radar systems are reviewed. Both side-looking and hologram (downward-looking) radars are described and compared. Several examples of microwave imagery obtained with these two types of systems are shown.

Zelenka, J. S.↗
NASA NTRS1989

Passive millimeter-wave imaging - A tool for remote sensing

This paper describes a program of airborne radiometric imaging at 90 GHz and 140 GHz. Using high sensitivity (below 1 K) and high angular resolution (0.5-1.0 degree), high quality images have been made. The following measurements are discussed: cloud and fog penetration at 90 GHz, discrimination between agricultural and urban areas, discrimination between different vegetation types, detection of vehicles on roads, detection and classification of airports and airplanes, ship detection and quantitative oil spill sensing. The application of information enhancement techniques with automatic and real time application aspects is also described, and results of applied techniques for contrast and contour enhancement are shown.

Suess, Helmut↗
NASA NTRS2021

Compact Thermal Imager (CTI) for Atmospheric Remote Sensing

The demonstration of a newly developed compact thermal imager (CTI) on the International Space Station (ISS) has provided not only a technology advancement but a rich high-resolution dataset on global clouds, atmospheric and land emissions. This study showed that the free-running CTI instrument could be calibrated to produce scientifically useful radiance imagery of the atmosphere, clouds, and surfaces with a vertical resolution of ~460 m at limb and a horizontal resolution of ~80 m at nadir. The new detector demonstrated an excellent sensitivity to detect the weak limb radiance perturbations modulated by small-scale atmospheric gravity waves. The CTI’s high-resolution imaging was used to infer vertical cloud temperature profiles from a side-viewing geometry. For nadir imaging, the combined high-resolution and high-sensitivity capabilities allowed the CTI to better separate cloud and surface emissions, including those in the planetary boundary layer (PBL) that had small contrast against the background surface. Finally, based on the ISS’s orbit, the stable detector performance and robust calibration algorithm produced valuable diurnal observations of cloud and surface emissions with respect to solar local time during May–October 2019, when the CTI had nearly continuous operation.

thermal imager↗
NASA NTRS1985

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Guseman, L. F., Jr.↗
DOE OSTI2022

Introduction to Special Section: Machine Learning for Image-based Geologic Interpretation

Image-based geological interpretation has been a labor-intensive and time-consuming process because it requires well-trained geoscientists to identify geological structures, features, and textures from various types of images. These images include scanning electron microscopic images, optical microscopic images, optical photos, resistivity images, seismic volumes, remote-sensing images, etc. With fast-evolving machine learning (ML) technology and computing power in recent decades, computers can achieve nearhuman-level to super-human-level performance with scalable high efficiency in the computer vision field. These technological revolutions facilitated image-based geological interpretation in petroleum exploration and production. For example, a fault picking method applied to 3-D seismic volume data using deep learning can achieve superior performance in comparison to conventional auto-picking methods. In addition, under the new normal of low oil prices, the petroleum industry seeks cost-effective strategies such as automating traditionally labor-intensive processes. Nevertheless, the potential of applying ML to geological image interpretation is still facing a few key challenges including data scarcity, data distribution, poor data and/or label quality, data leakage, learning algorithms, model architecture, training methodologies, testing and evaluation metrics, hyper-parameters optimization, model drift, production deployment, and the like.

58 GEOSCIENCES↗
NASA NTRS1986

Image processing methods in two and three dimensions used to animate remotely sensed data

Image processing methods and software used to animate nonimaging remotely sensed data on cloud cover are described. Three FORTRAN programs were written in the VICAR2/TAE image processing domain to perform 3D perspective rendering, to interactively select parameters controlling the projection, and to interpolate parameter sets for animation images between key frames. Operation of the 3D programs and transferring the images to film is automated using executive control language and custom hardware to link the computer and camera.

Hussey, K. J.↗
NASA NTRS1995

Aerolian erosion, transport, and deposition of volcaniclastic sands among the shifting sand dunes, Christmas Lake Valley, Oregon: TIMS image analysis

Remote sensing is a tool that, in the context of aeolian studies, offers a synoptic view of a dune field, sand sea, or entire desert region. Blount et al. (1990) presented one of the first studies demonstrating the power of multispectral images for interpreting the dynamic history of an aeolian sand sea. Blount's work on the Gran Desierto of Mexico used a Landsat TM scene and a linear spectral mixing model to show where different sand populations occur and along what paths these sands may have traveled before becoming incorporated into dunes. Interpretation of sand transport paths and sources in the Gran Desierto led to an improved understanding of the origin and Holocene history of the dunes. With the anticipated advent of the EOS-A platform and ASTER thermal infrared capability in 1998, it will become possible to look at continental sand seas and map sand transport paths using 8-12 mu m bands that are well-suited to tracking silicate sediments. A logical extension of Blount's work is to attempt a similar study using thermal infrared images. One such study has already begun by looking at feldspar, quartz, magnetite, and clay distributions in the Kelso Dunes of southern California. This paper describes the geology and application of TIMS image analysis of a less-well known Holocene dune field in south central Oregon using TIMS data obtained in 1991.

Edgett, Kenneth S.↗
NASA NTRS2009

Lossless Compression of Classification-Map Data

A lossless image-data-compression algorithm intended specifically for application to classification-map data is based on prediction, context modeling, and entropy coding. The algorithm was formulated, in consideration of the differences between classification maps and ordinary images of natural scenes, so as to be capable of compressing classification- map data more effectively than do general-purpose image-data-compression algorithms. Classification maps are typically generated from remote-sensing images acquired by instruments aboard aircraft (see figure) and spacecraft. A classification map is a synthetic image that summarizes information derived from one or more original remote-sensing image(s) of a scene. The value assigned to each pixel in such a map is the index of a class that represents some type of content deduced from the original image data for example, a type of vegetation, a mineral, or a body of water at the corresponding location in the scene. When classification maps are generated onboard the aircraft or spacecraft, it is desirable to compress the classification-map data in order to reduce the volume of data that must be transmitted to a ground station.

Hua, Xie↗
NASA NTRS1996

In-Flight Calibration and Validation of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

Calibrated spectra acquired remotely as images allow determination of surface and atmospheric properties based on absorption and scattering expressed in the spectra. AVIRIS measures spectra as images in the solar reflected portion of the electromagnetic spectrum. To use these spectra for scientific research and applications, the calibration of the spectra must be known at the time of measurement in flight. To validate the calibration of AVIRIS in flight, an in-flight calibration experiment was performed for an over-flight on May 9, 1995 at Ivanpah Playa, California. In-situ measurements of the atmosphere and surface at a calibration target were measured. These measurements were used to constrain a radiative transfer code and predict the total upwelling spectral radiance incident at AVIRIS. This prediction was compared to the radiance measured by AVIRIS for the calibration target. An agreement of 96.5% was determined. The in-flight signal-to-noise was determined and shown to have more than doubled over the previous year.

Green Robert O.↗
NASA NTRS1971

Pollution detection by digital correlation of multispectral, stero-image pairs.

Remote detection of air pollution circulation patterns is proposed to eventually predict the accumulation of hazardous surface concentrations in time for preventive emission control operations. Earth observations from space platforms will contain information on the height, mean velocity and lateral mixing scales of inversion layers and pollution plumes. Although this information is often not visible on photographs, it could conceivably be retrieved through a digital cross-correlation of multispectral stereo image pairs. Laboratory and field test results are used to illustrate the detection of non-visual inversion layers, the reduction of dominant signal interference, and the spectroscopic identification of combustion products.

Krause, F. R.↗
NASA NTRS1973

Spectral ratio imaging methods for geological remote sensing from aircraft and satellites

An improved photogrammetric technique (scannergrammetry) for the production of ratio images from multispectral scanner data is described. The multispectral technique is less affected by variations in atmospheric and solar illumination levels than single-channel scanner imagery of aerial photographs. Another advantage of the multispectral technique is the proportionality between ratios of a target deduced from ratio images, on the one hand, and ratios of reflectances calculated from laboratory spectra of samples from the target area, on the other hand. Several representative ratio images from aircraft and satellite data in the visible, reflective IR, and thermal IR regions are included. The geological applications suggested for ratio scannergrammetry include exploration of construction materials, soils, stratigraphy, volcanic ash flows, beaches, and sand dunes.

Vincent, R. K.↗