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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

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

The author has identified the following significant results. The production of ratio images from multispectral scanner data is described and several examples of ratio images from aircraft and ERTS-1 data are given for visible, reflective infrared, and thermal infrared wavelengths. The application of photogrammetric techniques to ratio images, defined for this paper as ratio scannergrammetry, is considerably aided by the lesser dependence of ratio images on atmospheric and solar illumination variations, compared with single channel scanner imagery or aerial photos. Ratio scannergrammetry is further aided by the proportionality between ratios of a target deduced from ratio images and ratios of reflectances calculated from laboratory spectra of samples from the target area. Consequently, ratios calculated from laboratory data can be used to predict which ratios are best for discriminating a given rock or mineral, to predict what other rocks or minerals will be confused with it, and finally, to place ratio scannergrammetry on an absolute basis, within an estimated standard error on the order of 5% to 10%. Examples of relative agreement between laboratory data and ratio images are given from two iron oxides, hematite and magnetite.

Vincent, R. K.↗
NASA NTRS1977

Data handling for the geometric correction of large images

Several geometric distortions are present in remotely sensed images depending on the type of sensors and the object being observed. It is often desirable to compensate for these distortions and store the images in reference to a standard coordinate system. Digital techniques for correction are versatile and introduce a minimum of radiometric errors. The main problems to be considered in this area are the determination of the corrective transformation, resampling, and the management of the large quantities of data. It is shown that, by a judicious rearrangement of the input data, considerable reductions in the required memory capacity can be achieved. The rearrangement can be accomplished in several stages. The method presented here is amenable to pipeline implementation for processing a continuous stream of images.

Ramapriyan, H. K.↗
NASA NTRS1992

Landsat-TM identification of Amblyomma variegatum (Acari: Ixodidae) habitats in Guadeloupe

The feasibility of identifying specific habitats of the African bont tick, Amblyomma variegatum, from Landsat-TM images was investigated by comparing remotely sensed images of visible farms in Grande Terre (Guadeloupe) with field observations made in the same period of time (1986-1987). The different tick habitates could be separated using principal component analysis. The analysis clustered the sites by large and small variance of band values, and by vegetation and moisture indexes. It was found that herds in heterogeneous sites with large variances had more ticks than those in homogeneous or low variance sites. Within the heterogeneous sites, those with high vegetation and moisture indexes had more ticks than those with low values.

Hugh-Jones, M.↗
NASA NTRS1997

Advanced applications: an overview

Applications of materials in white-light optical imaging, remote-sensing systems are discussed. Image formation in terms of wavefronts and the influence of materials on the quality of images is given. The rationale for why some space optics structures are large is presented.

image quality structure material↗
NASA NTRS2008

Solar Tower Experiments for Radiometric Calibration and Validation of Infrared Imaging Assets and Analysis Tools for Entry Aero-Heating Measurements

The NASA Engineering and Safety Center sponsored Hypersonic Thermodynamic Infrared Measurements assessment team has a task to perform radiometric calibration and validation of land-based and airborne infrared imaging assets and tools for remote thermographic imaging. The IR assets and tools will be used for thermographic imaging of the Space Shuttle Orbiter during entry aero-heating to provide flight boundary layer transition thermography data that could be utilized for calibration and validation of empirical and theoretical aero-heating tools. A series of tests at the Sandia National Laboratories National Solar Thermal Test Facility were designed for this task where reflected solar radiation from a field of heliostats was used to heat a 4 foot by 4 foot test panel consisting of LI 900 ceramic tiles located on top of the 200 foot tall Solar Tower. The test panel provided an Orbiter-like entry temperature for the purposes of radiometric calibration and validation. The Solar Tower provided an ideal test bed for this series of radiometric calibration and validation tests because it had the potential to rapidly heat the large test panel to spatially uniform and non-uniform elevated temperatures. Also, the unsheltered-open-air environment of the Solar Tower was conducive to obtaining unobstructed radiometric data by land-based and airborne IR imaging assets. Various thermocouples installed on the test panel and an infrared imager located in close proximity to the test panel were used to obtain surface temperature measurements for evaluation and calibration of the radiometric data from the infrared imaging assets. The overall test environment, test article, test approach, and typical test results are discussed.

Splinter, Scott C.↗
DOE OSTI2021

Open Data and Deep Semantic Segmentation for Automated Extraction of Building Footprints

Advances in machine learning and computer vision, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics, cost-effectively, and at scale. These characteristics are relevant to a variety of urban and energy applications, yet are time consuming and costly to acquire with today’s manual methods. Several recent research studies have shown that in comparison to more traditional methods that are based on features engineering approach, an end-to-end learning approach based on deep learning algorithms significantly improved the accuracy of automatic building footprint extraction from remote sensing images. However, these studies used limited benchmark datasets that have been carefully curated and labeled. How the accuracy of these deep learning-based approach holds when using less curated training data has not received enough attention. The aim of this work is to leverage the openly available data to automatically generate a larger training dataset with more variability in term of regions and type of cities, which can be used to build more accurate deep learning models. In contrast to most benchmark datasets, the gathered data have not been manually curated. Thus, the training dataset is not perfectly clean in terms of remote sensing images exactly matching the ground truth building’s foot-print. A workflow that includes data pre-processing, deep learning semantic segmentation modeling, and results post-processing is introduced and applied to a dataset that include remote sensing images from 15 cities and five counties from various region of the USA, which include 8,607,677 buildings. The accuracy of the proposed approach was measured on an out of sample testing dataset corresponding to 364,000 buildings from three USA cities. The results favorably compared to those obtained from Microsoft’s recently released US building footprint dataset.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1997

Cluster Method Analysis of K. S. C. Image

Information obtained from satellite-based systems has moved to the forefront as a method in the identification of many land cover types. Identification of different land features through remote sensing is an effective tool for regional and global assessment of geometric characteristics. Classification data acquired from remote sensing images have a wide variety of applications. In particular, analysis of remote sensing images have special applications in the classification of various types of vegetation. Results obtained from classification studies of a particular area or region serve towards a greater understanding of what parameters (ecological, temporal, etc.) affect the region being analyzed. In this paper, we make a distinction between both types of classification approaches although, focus is given to the unsupervised classification method using 1987 Thematic Mapped (TM) images of Kennedy Space Center.

Rodriguez, Joe, Jr.↗
NASA NTRS1982

Imaging spectrometer technologies for advanced Earth remote sensing

A major requirement of multispectral imaging systems for advanced Earth remote sensing is the provision for greater spectral resolution and more versatile spectral band selection. The imaging spectrometer instrument concept provides this versatility by the combination of pushbroom imaging and spectrally dispersing optics using area array detectors in the focal plane. The shuttle imaging spectrometer concept achieves 10- and 20-meter ground instantaneous fields of view with 20-nanometer spectral resolution from Earth Orbit. Onboard processing allows the selection of spectral bands during flight; this, in turn, permits the sensor parameters to be tailored to the experiment objectives. Advances in optical design, infrared detector arrays, and focal plane cooling indicate the feasibility of the instrument concept and support the practicability of a validation flight experiment for the shuttle in the late 1980s.

Wellman, J. B.↗
NASA NTRS1982

Imaging spectrometer technologies for advanced earth remote sensing

A major requirement of multispectral imaging systems for advanced earth remote sensing is the provision for greater spectral resolution and more versatile spectral band selection. The imaging spectrometer instrument concept provides this versatility by the combination of pushbroom imaging and spectrally dispersing optics using area array detectors in the focal plane. The shuttle imaging spectrometer concept achieves 10- and 20-meter ground instantaneous fields of view with 20-nanometer spectral resolution from earth orbit. Onboard processing allows the selection of spectral bands during flight; this, in turn, permits the sensor parameters to be tailored to the experiment objectives. Advances in optical design, infrared detector arrays, and focal plane cooling indicate the feasibility of the instrument concept and support the practicability of a validation flight experiment for the shuttle in the late 1980s. Previously announced in STAR as N83-28542

Wellman, J. B.↗
NASA NTRS2004

An Integrated Multiangle, Multispectral, and Polarimetric Imaging Concept for Aerosol Remote Sensing from Space

Techniques for passive remote sensing of aerosol optical and microphysical properties from space include visible, near and shortwave-infrared imaging (e.g., from MODIS), multiangle intensity imaging (e.g., ATSR-2, AATSR, MISR), near-ultraviolet mapping (e.g., TOMSIOMI), and polarimetry (e.g., POLDER, APS). Each of these methods has unique strengths. In this paper, we present a concept for integrating these approaches into a unified sensor. Design goals include spectral coverage from the near-UV to the shortwave infrared; intensity and polarimetric imaging simultaneously at multiple view angles; global coverage within a few days; kilometer to sub-kilometer spatial resolution; and measurement of the degree of linear polarization (DOLP) for a subset of the spectral complement with an uncertainty of 0.5% or less.

polarimetric↗
NASA NTRS1988

Autocorrelation and regularization in digital images. I - Basic theory

Spatial structure occurs in remotely sensed images when the imaged scenes contain discrete objects that are identifiable in that their spectral properties are more homogeneous within than between them and other scene elements. The spatial structure introduced is manifest in statistical measures such as the autocovariance function and variogram associated with the scene, and it is possible to formulate these measures explicitly for scenes composed of simple objects of regular shapes. Digital images result from sensing scenes by an instrument with an associated point spread function (PSF). Since there is averaging over the PSF, the effect, termed regularization, induced in the image data by the instrument will influence the observable autocovariance and variogram functions of the image data. It is shown how the autocovariance or variogram of an image is a composition of the underlying scene covariance convolved with an overlap function, which is itself a convolution of the PSF. The functional form of this relationship provides an analytic basis for scene inference and eventual inversion of scene model parameters from image data.

Jupp, David L. B.↗
NASA NTRS2016

Electric Potential and Electric Field Imaging with Applications

The technology and techniques for remote quantitative imaging of electrostatic potentials and electrostatic fields in and around objects and in free space is presented. Electric field imaging (EFI) technology may be applied to characterize intrinsic or existing electric potentials and electric fields, or an externally generated electrostatic field may be used for (illuminating) volumes to be inspected with EFI. The baseline sensor technology, electric field sensor (e-sensor), and its construction, optional electric field generation (quasistatic generator), and current e-sensor enhancements (ephemeral e-sensor) are discussed. Demonstrations for structural, electronic, human, and memory applications are shown. This new EFI capability is demonstrated to reveal characterization of electric charge distribution, creating a new field of study that embraces areas of interest including electrostatic discharge mitigation, crime scene forensics, design and materials selection for advanced sensors, dielectric morphology of structures, inspection of containers, inspection for hidden objects, tether integrity, organic molecular memory, and medical diagnostic and treatment efficacy applications such as cardiac polarization wave propagation and electromyography imaging.

Generazio, Ed↗
DOE OSTI2021

Multi-frame moving object detection system

A plurality of remote sensing images of a scene are received. A potential target object can be identified in one of the images, wherein the target object has a low signal-to-noise ratio (SNR). A candidate motion path of the target object can be generated based upon the images. A predicted position of the target object along the candidate motion path is determined for each of the remote sensing images. An image chip is extracted from each of the images, where each image chip is centered about the predicted position of the target object in its corresponding image. A sum image chip is generated based upon the image chips. An indication that the potential target object is an actual object in the images is output based upon a value of a center pixel of the sum image chip.

Ma, Tian J.↗
NASA NTRS1981

Texture transforms of remote sensing data

Tone and texture are fundamental interrelated visual concepts. The concepts are used for the digital analysis of remotely sensed image data. The reported investigation had the objective to develop software for the quantification of image texture and to apply the texture information to both image enhancement and thematic classification of remotely sensed data. The quantitative texture information was applied to the analysis of Landsat-2 Multispectral Scanner Subsystem (MSS) data. Attention is given to the characterization of image texture, textured transformations, the subtext program, and a description of methods and results. It is pointed out that the inability to use the texture transforms of the Landsat MSS data for the thematic mapping of the study area's land cover contrasts sharply with the reported results of the textural analysis of digitized aerial photography by Hsu (1978).

Irons, J. R.↗
NASA NTRS2005

Custom Sky-Image Mosaics from NASA's Information Power Grid

yourSkyG is the second generation of the software described in yourSky: Custom Sky-Image Mosaics via the Internet (NPO-30556), NASA Tech Briefs, Vol. 27, No. 6 (June 2003), page 45. Like its predecessor, yourSkyG supplies custom astronomical image mosaics of sky regions specified by requesters using client computers connected to the Internet. Whereas yourSky constructs mosaics on a local multiprocessor system, yourSkyG performs the computations on NASA s Information Power Grid (IPG), which is capable of performing much larger mosaicking tasks. (The IPG is high-performance computation and data grid that integrates geographically distributed 18 NASA Tech Briefs, September 2005 computers, databases, and instruments.) A user of yourSkyG can specify parameters describing a mosaic to be constructed. yourSkyG then constructs the mosaic on the IPG and makes it available for downloading by the user. The complexities of determining which input images are required to construct a mosaic, retrieving the required input images from remote sky-survey archives, uploading the images to the computers on the IPG, performing the computations remotely on the Grid, and downloading the resulting mosaic from the Grid are all transparent to the user

Jacob, Joseph↗
NASA NTRS2016

High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

0↗
NASA NTRS2016

The Characterization of a DIRSIG Simulation Environment to Support the Inter-Calibration of Spaceborne Sensors

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed..

Ambeau, Brittany L.↗
NASA NTRS2016

Precision Instrument Targeting via Image Registration for the Mars 2020 Rover

A key component of Mars exploration is the operation of robotic instruments on the surface, such as those on board the Mars Exploration Rovers, the Mars Science Laboratory (MSL), and the planned Mars 2020 Rover. As the instruments carried by these rovers have become more advanced, the area targeted by some instruments becomes smaller, revealing more fine-grained details about the geology and chemistry of rocks on the surface. However, thermal fluctuations, rover settling or slipping, and inherent inaccuracies in pointing mechanisms all lead to pointing error that is on the order of the target size (several millimeters) or larger. We show that given a target located on a previously acquired image, the rover can align this with a new image to visually locate the target and refine the current pointing. Due to round-trip communication constraints, this visual targeting must be done efficiently on board the rover using relatively limited computing hardware. We employ existing ORB features for landmark-based image registration, describe and theoretically justify a novel approach to filtering false landmark matches, and employ a random forest classifier to automatically reject failed alignments. We demonstrate the efficacy of our approach using over 3,800 images acquired by Remote Micro-Imager on board the “Curiosity” rover.

Doran, Gary↗