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NASA NTRS1992

SAR backscatter from coniferous forest gaps

A study is in progress comparing Airborne Synthetic Aperture Radar (AIRSAR) backscatter from coniferous forest plots containing gaps to backscatter from adjacent gap-free plots. Issues discussed are how do gaps in the range of 400 to 1600 sq m (approximately 4-14 pixels at intermediate incidence angles) affect forest backscatter statistics and what incidence angles, wavelengths, and polarizations are most sensitive to forest gaps. In order to visualize the slant-range imaging of forest and gaps, a simple conceptual model is used. This strictly qualitative model has led us to hypothesize that forest radar returns at short wavelengths (eg., C-band) and large incidence angles (e.g., 50 deg) should be most affected by the presence of gaps, whereas returns at long wavelengths and small angles should be least affected. Preliminary analysis of 1989 AIRSAR data from forest near Mt. Shasta supports the hypothesis. Current forest backscatter models such as MIMICS and Santa Barbara Discontinuous Canopy Backscatter Model have in several cases correctly predicted backscatter from forest stands based on inputs of measured or estimated forest parameters. These models do not, however, predict within-stand SAR scene texture, or 'intrinsic scene variability' as Ulaby et al. has referred to it. For instance, the Santa Barbara model, which may be the most spatially coupled of the existing models, is not truly spatial. Tree locations within a simulated pixel are distributed according to a Poisson process, as they are in many natural forests, but tree size is unrelated to location, which is not the case in nature. Furthermore, since pixels of a simulated stand are generated independently in the Santa Barbara model, spatial processes larger than one pixel are not modeled. Using a different approach, Oliver modeled scene texture based on an hypothetical forest geometry. His simulated scenes do not agree well with SAR data, perhaps due to the simple geometric model used. Insofar as texture is the expression of biological forest processes, such as succession and disease, and physical ones, such as fire and wind-throw, it contains useful information about the forest, and has value in image interpretation and classification. Forest gaps are undoubtedly important contributors to scene variance. By studying the localized effects of gaps on forest backscatter, guided by our qualitative model, we hope to understand more clearly the manner in which spatial heterogeneities in forests produce variations in backscatter, which collectively give rise to scene texture.

Day, John L.↗

NASA NTRS1992

Registering and resampling images in STSDAS

Registering different images can be difficult, especially if the images to be registered are images at different wavelengths, where features in one image may look entirely different or be absent from the second image. Using two new packages soon to be added to the STSDAS package, REGISTER and RESAMPLE, this job is done automatically. The REGISTER package allows the user to determine the amount of translation, rotation, and/or magnification needed to make two images, spectra, or time series congruent. The methods implemented to compute the registration parameters use: a set of the pixel coordinates of the same features identified in two files, or the FITS coordinate transformation parameters in the headers of two data files, or a single feature identified as the peak of a cross-correlation between two vectors. The coefficients describing the registration are defined by the equations (for a two-dimensional image): x = a + bx + cy, y = d + ex + fy, where (X,Y) are the pixel coordinates of a feature in the reference image, (x,y) are the pixel coordinates of a feature in the secondary image, and the computed coefficients are a, b, c, d, e, and f. Results may be produced by linking the output of REGISTER to RESAMPLE in a command language procedure. The output from REGISTER and the input to RESAMPLE consists of a matrix of coefficients (a through f above) fully specifying the registration. The RESAMPLE package resamples simple vector or image data for a given amount of translation, rotation (images only), and magnification, or reflection of the science data. Specific options included are: image rotation about the FITS reference pixel; scale changes, i.e. magnification or demagnification (for images, independently on both axes); simple translation; reflection (for images, about one or both axes); and resampling and registration to a reference data set. Output from the RESAMPLE task is the resampled image which may then be displayed and compared with the reference image.

Williamson, R. L., II↗

NASA NTRS1992

Solar full-disk magnetic field image receiving system and observation software

The paper introduces terminal hardware system of 10 cm high resolution full-disk magnetic field telescope among solar multi-channel telescope produced by Beijing Astronomical Observatory, and its software procedure by using imaging processing as well real time data collecting. These data were processed by Sun Workstation 470/4, including doing some spectrum analysis, the system is unique in the world now. It uses a set of CCD (1320 pixels plus 1035 pixels) of high resolution image explosion, also it has a set of fast and high resolution (1024 pixel plus 1024 pixel) image processor. Moreover, we can obtain higher time and space resolution about solar full-disk magnetic field and velocity field. This will provide excellent means in observation and studies of full-disk solar large-scale magnetic field and velocity field.

Xu, Yan↗

NASA NTRS1993

Measuring track densities in lunar grains by image analysis

We have developed techniques to use digitized scanning electron micrographs and computer image analysis programs to measure track densities in lunar soil grains. Tracks were formed by highly ionizing solar energetic particles and cosmic rays during near surface exposure on the Moon. The track densities are related to the exposure conditions (depth and time). Distributions of the number of grains as a function of their track densities can reveal the modality of soil maturation. We used a sample that had already been etched in 6 N NaOH at 118 C for 15 h to reveal tracks. We determined that back-scattered electron images taken at 50 percent contrast and approximately 49.8 percent brightness produced suitable high contrast images for analysis. We ascertained gray-scale thresholds of interest: 0-230 for tracks, 231 for masked regions, and 232-255 for background. We found no need to set an upper size limit for distinguishing tracks. We did use lower limits to exclude noise: 16 pixels at 15000x, 4 pixels at 10000x, 2 pixels at 6800x, and 0 pixels at 4600x. We used computer counting and measurement of area to obtain track densities. We found an excellent correlation with manual measurements for track densities below 1x10(exp 8) sq cm. For track densities between 1x10(exp 8) sq cm to 1x10(exp 9) sq cm, we found that a regression formula using the percentage area covered by tracks gave good agreement with manual measurements. Finally we used these new techniques to obtain a track density distribution that gave more detail and was more rapidly obtained than using manual techniques 15 years ago.

Blanford, George E.↗

NASA NTRS1994

Studies on image compression and image reconstruction

During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included.

Sayood, Khalid↗

NASA NTRS1994

On current compositing algorithms

Several techniques exist for compositing the multitemporal NOAA Advanced Very High Resolution Radiometer (AVHRR) data for vegetation studies. The major pixel selection criteria of these techniques rely on the characteristics of the NDVI (Normalized Difference Vegetative Index): appearance of clouds, poor atmospheric conditions, and off-nadir viewing geometries would depress the NDVI values. Consequently, selecting the pixels with the maximum value of NDVI would presumably eliminate these external perturbating effects. However, the maximum NDVI does not always correspond to these ideal conditions. In fact, the NDVI varies with these external factors in an unpredictable way. There was an indication that the maximum NDVI tended to favor the off-nadir view in the forward direction. The resultant composite product would be consequently affected. To improve the multitemporal data via compositing, therefore, both the pixel selection criteria and the classifier NDVI need to be modified or corrected for external factors. The current compositing algorithms were reviewed, and alternatives were proposed to use the combinations of the red and near infrared channels and biological characteristics of vegetation as second criteria in pixel selections. The traditional classifier NDVI was replaced with different vegetation indices. The approach was applied to an AVHRR data set over the HAPEX study site in Niger in 1992. The results showed that the approach improved the AVHRR time series quality and was promising towards the development of an efficient compositing algorithm.

Qi, J.↗

NASA NTRS1994

PRISM project optical instrument

The scientific goal of the Passively-cooled Reconnaissance of the InterStellar Medium (PRISM) project is to map the emission of molecular hydrogen at 17.035 micrometers and 28.221 micrometers. Since the atmosphere is opaque at these infrared wavelengths, an orbiting telescope is being studied. The availability of infrared focal plane arrays enables infrared imaging spectroscopy at the molecular hydrogen wavelengths. The array proposed for PRISM is 128 pixels square, with a pixel size of 75 micrometers. In order to map the sky in a period of six months, and to resolve the nearer molecular clouds, each pixel must cover 0.5 arcminutes. This sets the focal length at 51.6 cm. In order for the pixel size to be half the diameter of the central diffraction peak at 28 micrometers would require a telescope aperture of 24 cm; an aperture of 60 cm has been selected for the PRISM study for greater light gathering power.

Taylor, Charles R.↗

NASA NTRS1995

Validating spatial structure in canopy water content using geostatistics

Heterogeneity in ecological phenomena are scale dependent and affect the hierarchical structure of image data. AVIRIS pixels average reflectance produced by complex absorption and scattering interactions between biogeochemical composition, canopy architecture, view and illumination angles, species distributions, and plant cover as well as other factors. These scales affect validation of pixel reflectance, typically performed by relating pixel spectra to ground measurements acquired at scales of 1m(exp 2) or less (e.g., field spectra, foilage and soil samples, etc.). As image analysis becomes more sophisticated, such as those for detection of canopy chemistry, better validation becomes a critical problem. This paper presents a methodology for bridging between point measurements and pixels using geostatistics. Geostatistics have been extensively used in geological or hydrogeolocial studies but have received little application in ecological studies. The key criteria for kriging estimation is that the phenomena varies in space and that an underlying controlling process produces spatial correlation between the measured data points. Ecological variation meets this requirement because communities vary along environmental gradients like soil moisture, nutrient availability, or topography.

Sanderson, E. W.↗

NASA NTRS1995

A spatially adaptive spectral re-ordering technique for lossless coding of hyper-spectral images

In this paper, we propose a new approach, applicable to lossless compression of hyper-spectral images, that alleviates some limitations of linear prediction as applied to this problem. According to this approach, an adaptive re-ordering of the spectral components of each pixel is performed prior to prediction and encoding. This re-ordering adaptively exploits, on a pixel-by pixel basis, the presence of inter-band correlations for prediction. Furthermore, the proposed approach takes advantage of spatial correlations, and does not introduce any coding overhead to transmit the order of the spectral bands. This is accomplished by using the assumption that two spatially adjacent pixels are expected to have similar spectral relationships. We thus have a simple technique to exploit spectral and spatial correlations in hyper-spectral data sets, leading to compression performance improvements as compared to our previously reported techniques for lossless compression. We also look at some simple error modeling techniques for further exploiting any structure that remains in the prediction residuals prior to entropy coding.

Memon, Nasir D.↗

NASA NTRS1995

Unmixing AVHRR Imagery to Assess Clearcuts and Forest Regrowth in Oregon

Advanced Very High Resolution Radiometer imagery provides frequent and low-cost coverage of the earth, but its coarse spatial resolution (approx. 1.1 km by 1.1 km) does not lend itself to standard techniques of automated categorization of land cover classes because the pixels are generally mixed; that is, the extent of the pixel includes several land use/cover classes. Unmixing procedures were developed to extract land use/cover class signatures from mixed pixels, using Landsat Thematic Mapper data as a source for the training set, and to estimate fractions of class coverage within pixels. Application of these unmixing procedures to mapping forest clearcuts and regrowth in Oregon indicated that unmixing is a promising approach for mapping major trends in land cover with AVHRR bands 1 and 2. Including thermal bands by unmixing AVHRR bands 1-4 did not lead to significant improvements in accuracy, but experiments with unmixing these four bands did indicate that use of weighted least squares techniques might lead to improvements in other applications of unmixing.

Hlavka, Christine A.↗

NASA NTRS1994

The Area Coverage of Geophysical Fields as a Function of Sensor Field-of View

In many remote sensing studies of geophysical fields such as clouds, land cover, or sea ice characteristics, the fractional area coverage of the field in an image is estimated as the proportion of pixels that have the characteristic of interest (i.e., are part of the field) as determined by some thresholding operation. The effect of sensor field-of-view on this estimate is examined by modeling the unknown distribution of subpixel area fraction with the beta distribution, whose two parameters depend upon the true fractional area coverage, the pixel size, and the spatial structure of the geophysical field. Since it is often not possible to relate digital number, reflectance, or temperature to subpixel area fraction, the statistical models described are used to determine the effect of pixel size and thresholding operations on the estimate of area fraction for hypothetical geophysical fields. Examples are given for simulated cumuliform clouds and linear openings in sea ice, whose spatial structures are described by an exponential autocovariance function. It is shown that the rate and direction of change in total area fraction with changing pixel size depends on the true area fraction, the spatial structure, and the thresholding operation used.

Key, Jeffrey R.↗

NASA NTRS1997

Laboratory test data on the stability of the STIS MAMAs

STIS has two MAMA detectors systems with distinctly different tube configurations. The first (designated BAND 1) has an opaque CsI photocathode deposited on the microchannel plate (MCP) providing wavelength coverage from 1150A to 1700A. The other MAMA (designated BAND 2) has a semitransparent CS2Te photocathode deposited on the faceplate in close proximity to the input of the MCP. It covers the 1650A to 3100A bandpass and serves as a backup for the short wavelength detector. Laboratory test data indicate that both of these detectors have good sensitivity, have good uniformity and provide stable response, making each capable of collecting data with a signal-to-noise ratio in excess of 100 per Space Telescope Imaging Spectrograph (STIS) optical resolution element. Over a multiyear development effort, a substantial body of laboratory test data (more than 6 GBytes spanning more than 6 years of collection) has accumulated on more than a dozen fabricated tubes. These tests even included a few destructive evaluations to examine the limitations and operating life. In addition, analyses where conducted regarding impact caused by the specified electronic tolerances and expected changes in the Hubble Space Telescope (HST) thermal environment. Perhaps the simplest test of stability is to collect a sequence of images, each with a uniform illumination, and use these individual "flat fields" to remove the pixel-to-pixel sensitivity in the other flat fields. These sequences typically spanned 3-5 weeks of time. The detectors are very stable, allowing the pixel-to-pixel sensitivity to be removed with good precision. The STIS specification for stability is 1% (sufficient for data with a S/N = 100) over a 1 week period and 2% over 30 days. All Engineering Model Units as well as Flight Detectors tested exceeded this specification.

Joseph, Charles L.↗

NASA NTRS1998

Horizontal Radiative Fluxes in Clouds at Absorbing Wavelengths

We discuss the effect of horizontal fluxes on the accuracy of a conventional plane-parallel radiative transfer calculation for a single pixel, known as the Independent Pixel Approximation (IPA) at absorbing wavelengths. Vertically integrated horizontal fluxes can be represented as a sum of three components; each component is the IPA accuracy on a pixel-by-pixel basis for reflectance, transmittance and absorptance, respectively. We show that IPA accuracy for reflectance always improves with more absorption, while the IPA accuracy for transmittance is less sensitive to the changes in absorption: with respect to the non-absorbing case, it may first deteriorate for weak absorption and then improve again for strongly absorbing wavelengths. EPA accuracy for absorptance always deteriorates with more absorption. As a result, vertically integrated horizontal fluxes, as a sum of IPA accuracies for reflectance, transmittance and absorptance, increase with more absorption. Finally, the question of correlations between horizontal fluxes, IPA uncertainties and radiative smoothing is addressed using wavenumber spectra of radiation fields reflected from or transmitted through fractal clouds.

Marshak, A.↗

NASA NTRS1999

Multi-Scale Fractal Analysis of Image Texture and Pattern

Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images of the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimensional-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

Emerson, Charles W.↗

NASA NTRS1995

A Compact Polarization Imager

A new type of image detector has been designed to analyze the polarization of light simultaneously at all picture elements (pixels) in a scene. The Integrated Dual Imaging Detector (IDID) consists of a polarizing beamsplitter bonded to a custom-designed charge-coupled device with signal-analysis circuitry, all integrated on a silicon chip. The IDID should simplify the design and operation of imaging polarimeters and spectroscopic imagers used, for example, in atmospheric and solar research. Other applications include environmental monitoring and robot vision. Innovations in the IDID include two interleaved 512 x 1024 pixel imaging arrays (one for each polarization plane), large dynamic range (well depth of 10(exp 6) electrons per pixel), simultaneous readout and display of both images at 10(exp 6) pixels per second, and on-chip analog signal processing to produce polarization maps in real time. When used with a lithium niobate Fabry-Perot etalon or other color filter that can encode spectral information as polarization, the IDID can reveal tiny differences between simultaneous images at two wavelengths.

Thompson, Karl E.↗

NASA NTRS1999

Multi-Scale Fractal Analysis of Image Texture and Pattern

Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images is the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimension-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

Emerson, Charles W.↗

NASA NTRS1999

Swift: A Widefield Imaging Fabry Perot for Sofia

Contract was to pursue feasibility studies of the SOFIA Widefield Imaging Fabry-Perot (SWIFT). SWIFT was proposed as a two color 18 to 40 microns imaging Fabry-Perot that utilized two Rockwell/Boeing 256 x 256 pixel Si:Sb BIBs as detective devices. The colors were to be split between 26 and 30 microns using a MgO dichroic. The resolution achieving devices were to be a pair of cryogenic fully tunable scanning Fabry-Perot interferometers (FPIs), two in each band. For high resolving powers, a third, fixed FPI is inserted into the beam. The FPI mirrors were to be made of free standing metal mesh. We also proposed to look into a long wavelength (40 to 210 microns) band during the feasibility study period. We produced a proposal to USRA, submitted in July 1997 that substantially refined our ideas. We decided the long wavelength science was compelling, so the baseline wavelength coverage for SWIFT was widened to 17 to 205 microns. Under typical operations, we proposed to simultaneously image in two bands: 22 to 38 microns, and 50 to 205 microns. The bands were to be split by a cold CaF2 dichroic. The short wavelength (SW) band was to employ a 256 x 256 pixel Boeing/Rockwell Si:Sb BIB array, and the long wavelength (LW) band was to employ a Goddard 6 x 32 (upgradable to 32 x 32) element array of monolithic silicon "pop-up" bolometers as detective devices. The two color capability doubled the data taking efficiency, and ensured "perfect" registration between the images obtained in each band. For the SW band, the beam was to be fully sampled (0.7" pixels, 1.4 in. beam) at 17 microns, and over sampled at longer wavelengths. Even so, SWIFT has a very large (3 ft x 3 ft) field of view. To match the SW and LW fields of view (initially in one dimension only, but in 2-dimensions with 32 x 32 upgrade), SWIFT was to under sample at 63 microns (5.6 in pixels, 5.2 in beam) resulting in a 0.56 x 3 in (upgrade to 3 in x 3 in) field of view. Each band has both Lo-Res (R triple bond lambda/Delta(lambda) approx. 30 to 200) and Hi-Res (R approx. 1000 up to 10(exp 5)) modes, that can be changed in less than a minute. Spectral resolution is obtained with four identical cryogenic, fully tunable, scanning FPIS, two in each band, plus a set of fixed order FPI that can be rotated into the beam for good spectral purity at the highest resolving powers. SWIFT was proposed to explore three primary topics of scientific interest: 1. Protostars, Young Stellar Objects, and Protoplanetary Disks. 2. The Galactic Center. 3. External Galaxies.

Stacey, Gordon J.↗

NASA NTRS2001

Airborne Hyperspectral Imagery for the Detection of Agricultural Crop Stress

Multispectral digital imagery from aircraft or satellite is presently being used to derive basic assessments of crop health for growers and others involved in the agricultural industry. Research indicates that narrow band stress indices derived from hyperspectral imagery should have improved sensitivity to provide more specific information on the type and cause of crop stress, Under funding from the NASA Earth Observation Commercial Applications Program (EOCAP) we are identifying and evaluating scientific and commercial applications of hyperspectral imagery for the remote characterization of agricultural crop stress. During the summer of 1999 a field experiment was conducted with varying nitrogen treatments on a production corn-field in eastern Nebraska. The AVIRIS (Airborne Visible-Infrared Imaging Spectrometer) hyperspectral imager was flown at two critical dates during crop development, at two different altitudes, providing images with approximately 18m pixels and 3m pixels. Simultaneous supporting soil and crop characterization included spectral reflectance measurements above the canopy, biomass characterization, soil sampling, and aerial photography. In this paper we describe the experiment and results, and examine the following three issues relative to the utility of hyperspectral imagery for scientific study and commercial crop stress products: (1) Accuracy of reflectance derived stress indices relative to conventional measures of stress. We compare reflectance-derived indices (both field radiometer and AVIRIS) with applied nitrogen and with leaf level measurement of nitrogen availability and chlorophyll concentrations over the experimental plots (4 replications of 5 different nitrogen levels); (2) Ability of the hyperspectral sensors to detect sub-pixel areas under crop stress. We applied the stress indices to both the 3m and 18m AVIRIS imagery for the entire production corn field using several sub-pixel areas within the field to compare the relative sensitivity of each stress index; and (3) Comparative sensitivity of stress indices to realistic measurement uncertainties. We compare the stress indices calculated with several levels of spectral uncertainty (by shifting the wavelengths) and reflectance uncertainty (by systematically varying the reflectance retrieval code initialization).

Cassady, Philip E.↗