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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Speckle noise reduction of 1-look SAR imagery

Speckle noise is inherent to synthetic aperture radar (SAR) imagery. Since the degradation of the image due to this noise results in uncertainties in the interpretation of the scene and in a loss of apparent resolution, it is desirable to filter the image to reduce this noise. In this paper, an adaptive algorithm based on the calculation of the local statistics around a pixel is applied to 1-look SAR imagery. The filter adapts to the nonstationarity of the image statistics since the size of the blocks is very small compared to that of the image. The performance of the filter is measured in terms of the equivalent number of looks (ENL) of the filtered image and the resulting resolution degradation. The results are compared to those obtained from different techniques applied to similar data. The local adaptive filter (LAF) significantly increases the ENL of the final image. The associated loss of resolution is also lower than that for other commonly used speckle reduction techniques.

Nathan, Krishna S.↗
NASA NTRS1988

DMSP-SSM/1 NASA algorithm validation using primarily LANDSAT and secondarily DMSP and/or AVHRR visible and thermal infrared satellite imagery

The approach to the DMSP SSMI (Defense Meteorological Satellite Program; Special Sensor Microwave Imager) sea-ice validation effort is to demonstrate a quantitative relationship between the SSMI-derived sea ice parameters and those same parameters derived from other data sets including visible and infrared satellite imagery, aerial photographic and high-resolution microwave aircraft imagery. The question to be addressed is to what accuracy (relative to these other observations) can the following ice parameters be determined: (1) position of the ice boundary; (2) total sea ice concentration; and (3) multiyear sea ice concentration. Specific tasks include: (1) a study of the interrelationship of surface information content and sensor spatial and spectral resolution in order to establish relationships between ice surface features and the manner in which they are expressed in the satellite observations; and (2) apply these relationships to map the sea ice features which can be used to evaluate NASA's proposed SSM/1 sea ice algorithms. Other key points to be addressed include the accuracy to which these parameters can be determined in different regions (marginal ice zone such as Bering Sea, Arctic ocean, such as Beaufort Sea); the accuracy of these parameters for different seasons; the accuracy of the algorithms weather filter under different weather conditions; and the effectiveness of the 85.5 GHz channels to locate the ice edge.

Steffen, K.↗
NASA NTRS1988

A comparison of airborne GEMS/SAR with satellite-borne Seasat/SAR radar imagery - The value of archived multiple data sets

In a study concerning the value of using radar imagery from systems with diverse parameters, X-band images of the Northern Louisiana Salt dome area generated by the airborne Goodyear electronic mapping system (GEMS) are analyzed in conjunction with imagery generated by the satelliteborne Seasat/SAR. The GEMS operated with an incidence angle of 75 to 85 deg and a resolution of 12 m, whereas the Seasat/SAR operated with an incidence angle of 23 deg and a resolution of 25 m. It is found that otherwise unattainable data on land management activities, improved delineation of the drainage net, better definition of surface roughness in cleared areas, and swamp identification, became accessible when adjustments for the time lapse between the two missions were made and supporting ground data concerning the physical and vegetative characteristics of the terrain were acquired.

Hanson, Bradford C.↗
NASA NTRS1988

Spatial compression of Seasat SAR imagery

The results of a study of techniques for spatial compression of synthetic-aperture-radar (SAR) imagery are summarized. Emphasis is on image-data volume reduction for archive and online storage applications while preserving the image resolution and radiometric fidelity. A quantitative analysis of various techniques, including vector quantization (VQ) and adaptive discrete cosine transform (ADCT), is presented. Various factors such as compression ratio, algorithm complexity, and image quality are considered in determining the optimal algorithm. The compression system requirements are established for electronic access of an online archive system based on the results of a survey of the science community. The various algorithms are presented and their results evaluated considering the effects of speckle noise and the wide dynamic range inherent in SAR imagery. The conclusion is that although the ADCT produces the best signal-to-distortion-noise ratio for a given compression ratio, the two-level tree-searched VQ technique is preferred due to its simplicity of decoding and near-optimal performance.

Chang, C. Y.↗
NASA NTRS1988

Atmospheric effect removal from space imagery

A method to derive a ground reflectance scene from space imagery by removing the contribution of atmospheric radiance was developed. The method utilizes a multiple scattering radiative transfer code to model the Earth-atmosphere system and converts the output into a set of quadratic coefficients which best fit the relationships between the upwelling radiance reaching the sensor and the lower boundary conditions of the ground reflectance. Pixel by pixel correction of the atmospheric effects is done by invoking these coefficients. The algorithm was applied to a number of Thematic Mapper and CZCS data to generate interesting ground scenes and was used to simulate space imagery from ground reflectance scenes.

Kim, Hongsuk H.↗
NASA NTRS1988

Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery

An algorithm for automatic atmospheric correction of satellite imagery of the earth's surface is proposed which is applicable to low-resolution and high-resolution imagery of land areas. The algorithm is based on the satellite image being corrected and on the climatology of the area, and it requires that some pixels in the image correspond to dense dark vegetation as the surface cover. The algorithm is sensitive to the assumed reflectance of the dense dark vegetation, and the accuracy of the corrected surface reflectance is expected to be + or - 0.01. Using the method, aerosol optical thicknesses were derived from clear and hazy Landsat MSS images in the Washington, D.C. and Chesapeake Bay region, and the results are found to agree well with simultaneous sunphotometer ground measurements.

Kaufman, Yoram J.↗
NASA NTRS1988

Storm diagnostic/predictive images derived from a combination of lightning and satellite imagery

A technique is presented for generating trend or convective tendency images using a combination of GOES satellite imagery and cloud-to-ground lightning observations. The convective tendency images can be used for short term forecasting of storm development. A conceptual model of cloud electrical development and an example of the methodology used to generate lightning/satellite convective tendency imagery are given. Successive convective tendency images can be looped or animated to show the previous growth or decay of thunderstorms and their associated lighting activity. It is suggested that the convective tendency image may also be used to indicate potential microburst producing storms.

Goodman, Steven J.↗
NASA NTRS1988

Tropical synoptic signatures in composited 6.7 micrometer water vapor imagery

A model of the signatures of a synoptic development as seen in 6.7-micron water vapor channel imagery has been constructed from a composite of cases for a moisture burst over the eastern Pacific Ocean. The characteristics revealed in these composites are discussed and compared with the signatures of the moisture bursts as seen in satellite-derived visual and window channel IR imagery. A test of the forecast capability of the model was performed on 120 consecutive days, including 29 moisture bursts. After 2 hours of training, a meteorologist was able to forecast 19 (65 percent) of the bursts at least 24 hours in advance. In 6 cases, bursts were forecast when none occurred.

Thompson, A. H.↗
NASA NTRS1988

Meso-beta scale simulations of convective cloud systems over Florida utilizing synthetic data derived from GOES satellite imagery

An attempt is made to improve the simulation of the meso-alpha and meso-beta scales' precipitation distribution over the Florida peninsula during the warm season through improvement of the initialization of beta scale convective cloud systems, using GOES IR and visible satellite imagery. These data can be used to define the location and spatial extent of meso-beta scale cloud systems at a specified time. Attention is presently given to the results of the first phase of this study, in which only moisture information was synthesized from the satellite imagery.

Zack, John W.↗
NASA NTRS1988

Simulation and diagnosis of water vapor imagery with mesoscale model output

The present simulation of 6.7-micron channel water vapor imagery employs March 6-7, 1982 soundings from the Limited Area Mesoscale Prediction System (LAMPS) mesoscale model as inputs to a radiative transfer scheme. A comparison of model-generated and observed brightness temperatures indicates that LAMPS was able to replicate major features of the VAS imagery, including the pronounced warm, dry development streak and a cold cloud area. The model was not, however, able to resolve such finer-scaled details as the double structure of the development portion of the streak.

Muller, Bradley M.↗
NASA NTRS1989

Detecting biotic and hydrogeochemical processes in large peat basins with Landsat TM imagery

A survey was made of three large peat basins in boreal North America with Landsat TM imagery and field sampling. False-color composites composed of Bands 2, 3, and 4 are particularly effective in discriminating the major vegetation types and the important hydrogeochemical processes in these peatlands. This imagery indicates that the discharge of alkaline groundwater provides one of the most important regional and local controls on peatland development.

Glaser, Paul H.↗
NASA NTRS1989

Regional analysis of tertiary volcanic Calderas (western U.S.) using Landsat Thematic Mapper imagery

The Landsat Thematic Mapper (TM) imagery of the Basin and Range province of southern Nevada was analyzed to identify and map volcanic rock assemblages at three Tertiary calderas. It was found that the longer-wavelength visible and the NIR TM Bands 3, 5, and 7 provide more effective lithologic discrimination than the shorter-wavelength bands, due partly to deeper penetration of the longer-wavelength bands, resulting in more lithologically driven radiances. Shorter-wavelength TM Bands 1 and 2 are affected more by surficial weathering products including desert varnish which may or may not provide an indirect link to lithologic identity. Guidelines for lithologic analysis of volcanic terrains using Landsat TM imagery are outlined.

Spatz, David M.↗
NASA NTRS1990

Analysis of stratocumulus cloud fields using LANDSAT imagery: Size distributions and spatial separations

Stratocumulus cloud fields in the FIRE IFO region are analyzed using LANDSAT Thematic Mapper imagery. Structural properties such as cloud cell size distribution, cell horizontal aspect ratio, fractional coverage and fractal dimension are determined. It is found that stratocumulus cloud number densities are represented by a power law. Cell horizontal aspect ratio has a tendency to increase at large cell sizes, and cells are bi-fractal in nature. Using LANDSAT Multispectral Scanner imagery for twelve selected stratocumulus scenes acquired during previous years, similar structural characteristics are obtained. Cloud field spatial organization also is analyzed. Nearest-neighbor spacings are fit with a number of functions, with Weibull and Gamma distributions providing the best fits. Poisson tests show that the spatial separations are not random. Second order statistics are used to examine clustering.

Welch, R. M.↗
NASA NTRS1991

Fusion of monocular cues to detect man-made structures in aerial imagery

The extraction of buildings from aerial imagery is a complex problem for automated computer vision. It requires locating regions in a scene that possess properties distinguishing them as man-made objects as opposed to naturally occurring terrain features. It is reasonable to assume that no single detection method can correctly delineate or verify buildings in every scene. A cooperative-methods paradigm is useful in approaching the building extraction problem. Using this paradigm, each extraction technique provides information which can be added or assimilated into an overall interpretation of the scene. Thus, the main objective is to explore the development of computer vision system that integrates the results of various scene analysis techniques into an accurate and robust interpretation of the underlying three dimensional scene. The problem of building hypothesis fusion in aerial imagery is discussed. Building extraction techniques are briefly surveyed, including four building extraction, verification, and clustering systems. A method for fusing the symbolic data generated by these systems is described, and applied to monocular image and stereo image data sets. Evaluation methods for the fusion results are described, and the fusion results are analyzed using these methods.

Shufelt, Jefferey↗
NASA NTRS1990

Radiative transfer based retrieval of reflectance from calibrated radiance imagery measured by an imaging spectrometer for lithological mapping of the Clark Mountains, California

Spectral radiance imagery measured by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) are reduced to reflectance through compensation for atmospheric scattering, water vapor absorption, absorption of the well mixed gases, solar irradiance and the solar zenith angle. The LOWTRAN 7 (Kneizys et al., 1989) radiative transfer code form the basis for this retrieal. LOWTRAN 7 is constrained with water vapor determinations from the AVIRIS radiance data through an algorithm operating on the 940 nm atmospheric water band for every spatial element. In situ measurements of atmospheric optical depths are used to constrain the LOWTRAN 7 aerosol models. Accuracy of the retrieved reflectance spectra is evaluated with respect to surface spectra measured at the time of the overflight. The mineral bastnaesite is identified in the analysis of the retrieved reflectance imagery. These reflectance data provide a means to map the subtle mineral gradients in the PreCambrian block of the Clark Mountain range in southeastern California for geological analysis.

Green, Robert O.↗
NASA NTRS1991

Investigation of soil influences in AVHRR red and near-infrared vegetation index imagery

The effects of soil optical properties on vegetation index imagery are analyzed with ground-based spectral measurements and both simulated and actual AVHRR data from the NOAA satellites. Soil effects on vegetation indices were divided into primary variations associated with the brightness of bare soils, secondary variations attributed to 'color' differences among bare soils, and soil-vegetation spectral mixing. Primary variations were attributed to shifts in the soil line owing to atmosphere or soil composition. Secondary soil variance was responsible for the Saharan desert 'artefact' areas of increased vegetation index response in AVHRR imagery.

Huete, A. R.↗
NASA NTRS1991

Assimilation of global cloud imagery from multiple satellites

Synoptic images of the global cloud field are created from measurements of IR radiation taken aboard four geostationary and two polar-orbiting platforms simultaneously observing the earth's cloud field. A series of spatial and temporal interpolations, together with data reliability criteria, are used to map synoptic measurements from the geostationary satellites and asynoptic measurements from the polar-orbiting satellites. The synoptic global cloud imagery (GCI) that results has a horizontal resolution of 0.7 deg in longitude by 0.35 deg in latitude and a temporal resolution of 3 h, providing an unprecedented view of the global cloud pattern. Each composite image represents a nearly instantaneous snapshot of the entire earth's cloud field. Collectively, the composite imagery resolve, on a global basis, most of the variability inherent to organized convection, including several harmonics of the diurnal cycle. Because of its homogeneous properties, the GCI lends itself easily to a variety of space-time analyses useful for studying global cloud behavior.

Tanaka, Ken↗
NASA NTRS1991

Automated cloud screening of AVHRR imagery using split-and-merge clustering

Previous methods to segment clouds from ocean in AVHRR imagery have shown varying degrees of success, with nighttime approaches being the most limited. An improved method of automatic image segmentation, the principal component transformation split-and-merge clustering (PCTSMC) algorithm, is presented and applied to cloud screening of both nighttime and daytime AVHRR data. The method combines spectral differencing, the principal component transformation, and split-and-merge clustering to sample objectively the natural classes in the data. This segmentation method is then augmented by supervised classification techniques to screen clouds from the imagery. Comparisons with other nighttime methods demonstrate its improved capability in this application. The sensitivity of the method to clustering parameters is presented; the results show that the method is insensitive to the split-and-merge thresholds.

Gallaudet, Timothy C.↗