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At least 1,423 records · Page 79

Extraction of ozone and chlorophyll-A distribution from AVIRIS data

The potential of airborne imaging spectrometry for assessing and monitoring natural resources is studied. Therefore, an AVIRIS scene of the NASA's MacEurope 1991 campaign - acquired in Central Switzerland - is used. The test site consists of an urban area, the Lake Zug with its surrounding fields, the Rigi mountain in the center of the test site, and the Lake of Four Cantons. The region is covered by the AVIRIS flight #910705, run 6 and 7 of the NASA ER-2 aircraft resulting in an average nominal pixel size of about 18 m. Simultaneous to the ER-2 overflight spectroradiometric measurements have been taken in various locations. Preselected reference targets were measured in the field with a GER Mark V spectroradiometer, and radiance measurements were taken to the lake using a Li-Cor LI 1800UW specroradiometer below and above the water surface. A comprehensive meteorological data set was obtained by joining the POLLUMET experiment which carried out measurements to investigate the summer smog in Switzerland on the same day. The quality assessment for the actual data set can be found in detail in Meyer et al. A parametric approach calculating the location of the airplane was used to simulate the observation geometry. This parametric preprocessing procedure, which takes care of effects of flight line and attitude variations as well as the pixel-by-pixel topographic corrections is described in Meyer.

Schaepman, M.↗

Minimizing systematic errors from atmospheric multiple scattering and satellite viewing geometry in coastal zone color scanner level IIA imagery

Water-leaving radiances and phytoplankton pigment concentrations are calculated from coastal zone color scanner (CZCS) radiance measurements by removing atmospheric Rayleigh and aerosol radiances from the total radiance signal measured at the satellite. The single greatest source of error in CZCS atmospheric correction algorithms in the assumption that these Rayleigh and aerosol radiances are separable. Multiple-scattering interactions between Rayleigh and aerosol components cause systematic errors in calculated aerosol radiances, and the magnitude of these errors is dependent on aerosol type and optical depth and on satellite viewing geometry. A technique was developed which extends the results of previous radiative transfer modeling by Gordon and Castano to predict the magnitude of these systematic errors for simulated CZCS orbital passes in which the ocean is viewed through a modeled, physically realistic atmosphere. The simulated image mathematically duplicates the exact satellite, Sun, and pixel locations of an actual CZCS image. Errors in the aerosol radiance at 443 nm are calculated for a range of aerosol optical depths. When pixels in the simulated image exceed an error threshhold, the corresponding pixels in the actual CZCS image are flagged and excluded from further analysis or from use in image compositing or compilation of pigment concentration databases. Studies based on time series analyses or compositing of CZCS imagery which do not address Rayleigh-aerosol multiple scattering should be interpreted cautiously, since the fundamental assumption used in their atmospheric correction algorithm is flawed.

Martin, D. L.↗

Correlated noise in the COBE DMR sky maps

The Cosmic Background Explorer Satellite Differential Radiometer (COBE DMR) sky maps contain low-level correlated noise. We obtain estimates of the amplitude and pattern of the correlated noise from three techniques: angular averages of the covariance matrix, Monte Carlo simulations of two-point correlation functions and direct analysis of the DMR maps. The results from the three methods are mutually consistent. The noise covariance matrix of a DMR sky maps is diagonal to an accuracy of better than 1%. For a given sky pixel, the dominant noise covariance occure with the ring of pixels at an angular separation of 60 deg due to the 60 deg separation of the DMR horns. The mean covariance at 60 deg is 0.45%((sup +0.18)(sub -0.14)) of the mean variance. Additionally, the variance in a given pixel is 0.7% greater than would be expected from a single beam experiment with the same noise properties. Autocorrelation functions suffer from a approximately 1.5 sigma positive bias at 60 deg while cross-correlations have no bias. Published COBE DMR results are not significantly affected by correlated noise.

Lineweaver, C. H.↗

Plasma Properties and Magnetic Field Structure of the Solar Corona, Based on Coordinated Max '91 Observations from SERTS, the VLA, and Magnetographs

The plasma properties and magnetic field structure of the solar corona were determined using coordinated observations obtained with NASA/GSFC's Solar EUV Rocket Telescope and Spectrograph (SERTS), the Very Large Array (VLA), and Kitt Peak photospheric longitudinal magnetograms. A problem was identified with the SERTS calibration as determined from laboratory measurements. A revised calibration curve was derived by requiring that the numerous available measured line intensity ratios agreed with their respective theoretical values. Densities were derived from line intensity ratios, and active region densities were found to typically exceed quiet Sun densities by factors of only about 2. The active region density was found to remain constant across the SERTS slit, despite the fact that the emission line intensities vary significantly. This indicates that the product of the path length and the volume filling factor must vary significantly from the active region outskirts to the central core. Filling factors were derived and found to range from much less than one to nearly unity. Wavelength shifts were examined along the SERTS slit in the spatially resolved spectra, but no evidence was found for significant Doppler shifts in active region 7563 or in the quiet Sun. The numerical procedure developed by Monsignori-Fossi and Landini was used to derive the active region and quiet sun differential emission measure (DEM) from the spatially averaged spectra. A DEM was estimated for each spatial pixel in the two dimensional active region images by scaling the averaged active region DEM based upon corresponding pixel intensities of SERTS Mg IX, Fe XV, and Fe XVI images. These results, along with density measurements, were used in an IDL computer code which calculated the temperature dependence of the coronal magnetic field in each spatial pixel by minimizing the difference between the observed and calculated 20 and 6 cm microwave brightness temperatures.

Brosius, Jeffrey W.↗

Kriging in the Shadows: Geostatistical Interpolation for Remote Sensing

It is often useful to estimate obscured or missing remotely sensed data. Traditional interpolation methods, such as nearest-neighbor or bilinear resampling, do not take full advantage of the spatial information in the image. An alternative method, a geostatistical technique known as indicator kriging, is described and demonstrated using a Landsat Thematic Mapper image in southern Chiapas, Mexico. The image was first classified into pasture and nonpasture land cover. For each pixel that was obscured by cloud or cloud shadow, the probability that it was pasture was assigned by the algorithm. An exponential omnidirectional variogram model was used to characterize the spatial continuity of the image for use in the kriging algorithm. Assuming a cutoff probability level of 50%, the error was shown to be 17% with no obvious spatial bias but with some tendency to categorize nonpasture as pasture (overestimation). While this is a promising result, the method's practical application in other missing data problems for remotely sensed images will depend on the amount and spatial pattern of the unobscured pixels and missing pixels and the success of the spatial continuity model used.

Rossi, Richard E.↗

The Effects of Sensor Field-of-View on the Geometrical Characteristics of Sea Ice Leads and Implications for Large-Area Heat Flux Estimates

The release of heat from sea ice fractures ('leads') is an important component of the heat budget in the Arctic, but their impact on regional scale climate is difficult to assess without more information on their distribution in both space and time. Remote sensing of leads using satellite data, specifically AVHRR thermal and Landsat visible-band imagery, is examined empirically with respect to lead width, orientation, and area fraction. The geometrical aspects of the sensor are simulated so that the effect of sensor field-of-view on retrieved lead width statistics can be assessed. This is done using Landsat data and simulated lead networks degraded to AVHRR pixel sizes. The analyses illustrate how leads of sufficiently high contrast tend to 'grow' with increasing pixel size and how small or low contrast leads disappear. The relationship between lead contrast and the width/field-of-view ratio is also examined in order to determine the limits of lead detectability, and illustrates the multivalued nature of the problem of lead width retrieval. To help quantify the importance of changes in lead statistics, turbulent heat flux is calculated as a function of lead width and lead fraction. It is shown that pixel size has a substantial effect on estimates of turbulent heat transfer from leads to the atmosphere.

Key, J.↗

Satellite-Sensor Calibration Verification Using the Cloud-Shadow Method

An atmospheric-correction method which uses cloud-shaded pixels together with pixels in a neighboring region of similar optical properties is described. This cloud-shadow method uses the difference between the total radiance values observed at the sensor for these two regions, thus removing the nearly identical atmospheric radiance contributions to the two signals (e.g. path radiance and Fresnel-reflected skylight). What remains is largely due to solar photons backscattered from beneath the sea to dominate the residual signal. Normalization by the direct solar irradiance reaching the sea surface and correction for some second-order effects provides the remote-sensing reflectance of the ocean at the location of the neighbor region, providing a known 'ground target' spectrum for use in testing the calibration of the sensor. A similar approach may be useful for land targets if horizontal homogeneity of scene reflectance exists about the shadow. Monte Carlo calculations have been used to correct for adjacency effects and to estimate the differences in the skylight reaching the shadowed and neighbor pixels.

Reinersman, P.↗

Development and Operation of a Material Identification and Discrimination Imaging Spectroradiometer

Many imaging applications require quantitative determination of a scene's spectral radiance. This paper describes a new system capable of real-time spectroradiometric imagery. Operating at a full-spectrum update rate of 30Hz, this imager is capable of collecting a 30 point spectrum from each of three imaging heads: the first operates from 400 nm to 950 nm, with a 2% bandwidth; the second operates from 1.5 micro-m to 5.5 micro-m with a 1.5% bandwidth; the third operates from 5 micro-m to 12 micro-m, also at a 1.5% bandwidth. Standard image format is 256 x 256, with 512 x 512 possible in the VIS/NIR head. Spectra of up to 256 points are available at proportionately lower frame rates. In order to make such a tremendous amount of data more manageable, internal processing electronics perform four important operations on the spectral imagery data in real-time. First, all data in the spatial/spectral cube of data is spectro-radiometrically calibrated as it is collected. Second, to allow the imager to simulate sensors with arbitrary spectral response, any set of three spectral response functions may be loaded into the imager including delta functions to allow single wavelength viewing; the instrument then evaluates the integral of the product of the scene spectral radiances and the response function. Third, more powerful exploitation of the gathered spectral radiances can be effected by application of various spectral-matched filtering algorithms to identify pixels whose relative spectral radiance distribution matches a sought-after spectral radiance distribution, allowing materials-based identification and discrimination. Fourth, the instrument allows determination of spectral reflectance, surface temperature, and spectral emissivity, also in real-time. The spectral imaging technique used in the instrument allows tailoring of the frame rate and/or the spectral bandwidth to suit the scene radiance levels, i.e., frame rate can be reduced, or bandwidth increased to improve SNR when viewing low radiance scenes. The unique challenges of design and calibration are described. Pixel readout rates of 160 MHz, for full frame readout rates of 1000 Hz (512 x 512 image) present the first challenge; processing rates of nearly 600 million integer operations per second for sensor emulation, or over 2 billion per second for matched filtering, present the second. Spatial and spectral calibration of 66,536 pixels (262,144 for the 512 x 512 version) and up to 1,000 spectral positions mandate novel decoupling methods to keep the required calibration memory to a reasonable size. Large radiometric dynamic range also requires care to maintain precision operation with minimum memory size.

Dombrowski, Mark↗

Incorporating the APS Catalog of the POSS I and Image Archive in ADS

The primary purpose of this contract was to develop the software to both create and access an on-line database of images from digital scans of the Palomar Sky Survey. This required modifying our DBMS (called Star Base) to create an image database from the actual raw pixel data from the scans. The digitized images are processed into a set of coordinate-reference index and pixel files that are stored in run-length files, thus achieving an efficient lossless compression. For efficiency and ease of referencing, each digitized POSS I plate is then divided into 900 subplates. Our custom DBMS maps each query into the corresponding POSS plate(s) and subplate(s). All images from the appropriate subplates are retrieved from disk with byte-offsets taken from the index files. These are assembled on-the-fly into a GIF image file for browser display, and a FITS format image file for retrieval. The FITS images have a pixel size of 0.33 arcseconds. The FITS header contains astrometric and photometric information. This method keeps the disk requirements manageable while allowing for future improvements. When complete, the APS Image Database will contain over 130 Gb of data. A set of web pages query forms are available on-line, as well as an on-line tutorial and documentation. The database is distributed to the Internet by a high-speed SGI server and a high-bandwidth disk system. URL is http://aps.umn.edu/IDB/. The image database software is written in perl and C and has been compiled on SGI computers with MIX5.3. A copy of the written documentation is included and the software is on the accompanying exabyte tape.

Humphreys, Roberta M.↗

RADARSAT Underflights: Comparison of C-band VV and HH Backscatter-Wind Retrieval

The primary objective of this grant was to validate the modified CMOD4 wind speed algorithm used to invert RADARSAT data. We proposed to do the following: TASK 1: Participate in at least two underflights of RADARSAT (collecting backscatter measurements with the UMASS C-band and Ku-band scatterometers, CSCAT and KUSCAT. TASK 2: Process data gathered with CSCAT and KUSCAT into one kilometer along-track pixels with each pixel consisting of seventy-two five degree azimuth bins - each bin containing normalized radar cross section (NRCS) values for that particular azimuth angle and for each of the four incidence angles viewed by CSCAT and KUSCAT. Derive wind speed and direction estimates from each NRCS along-track pixel using CMOD4 and NSCAT models. TASK 3: Compare collocated CSCAT vertically polarized (VV) and RADARSAT horizontally polarized (HH) NRCS data and wind estimates, and based on the comparison, evaluate the performance of the modified CMOD4 wind speed algorithm to invert RADARSAT NRCS measurements. The first two tasks were completed. The third task is still on-going since the RADARSAT data for the underflights has not been released to the University of Massachusetts. We expect that the RADARSAT data will become available in the next few months, and we will complete the third task in a promptly manner once the data has been received. Below the missions flown and the data collected are summarized. Two missions, based out of the NASA Wallops Flight Facility, were flown. The first flight was on 21 September 1997 and the second on 24 September 1997. The time for each mission was approximately 2 hours. Figure 1 plots the flight tracks and marks the location of the NOAA buoys that were in the vicinity.

Source record↗

High Resolution Airborne Digital Imagery for Precision Agriculture

The Environmental Research Aircraft and Sensor Technology (ERAST) program is a NASA initiative that seeks to demonstrate the application of cost-effective aircraft and sensor technology to private commercial ventures. In 1997-98, a series of flight-demonstrations and image acquisition efforts were conducted over the Hawaiian Islands using a remotely-piloted solar- powered platform (Pathfinder) and a fixed-wing piloted aircraft (Navajo) equipped with a Kodak DCS450 CIR (color infrared) digital camera. As an ERAST Science Team Member, I defined a set of flight lines over the largest coffee plantation in Hawaii: the Kauai Coffee Company's 4,000 acre Koloa Estate. Past studies have demonstrated the applications of airborne digital imaging to agricultural management. Few studies have examined the usefulness of high resolution airborne multispectral imagery with 10 cm pixel sizes. The Kodak digital camera integrated with ERAST's Airborne Real Time Imaging System (ARTIS) which generated multiband CCD images consisting of 6 x 106 pixel elements. At the designated flight altitude of 1,000 feet over the coffee plantation, pixel size was 10 cm. The study involved the analysis of imagery acquired on 5 March 1998 for the detection of anomalous reflectance values and for the definition of spectral signatures as indicators of tree vigor and treatment effectiveness (e.g., drip irrigation; fertilizer application).

Herwitz, Stanley R.↗

Textural-Contextual Labeling and Metadata Generation for Remote Sensing Applications

Despite the extensive research and the advent of several new information technologies in the last three decades, machine labeling of ground categories using remotely sensed data has not become a routine process. Considerable amount of human intervention is needed to achieve a level of acceptable labeling accuracy. A number of fundamental reasons may explain why machine labeling has not become automatic. In addition, there may be shortcomings in the methodology for labeling ground categories. The spatial information of a pixel, whether textural or contextual, relates a pixel to its surroundings. This information should be utilized to improve the performance of machine labeling of ground categories. Landsat-4 Thematic Mapper (TM) data taken in July 1982 over an area in the vicinity of Washington, D.C. are used in this study. On-line texture extraction by neural networks may not be the most efficient way to incorporate textural information into the labeling process. Texture features are pre-computed from cooccurrence matrices and then combined with a pixel's spectral and contextual information as the input to a neural network. The improvement in labeling accuracy with spatial information included is significant. The prospect of automatic generation of metadata consisting of ground categories, textural and contextual information is discussed.

Kiang, Richard K.↗

An Integrated Imaging Detector of Polarization and Spectral Content

A new type of image detector has been designed to simultaneously analyze the polarization of light at all picture elements in a scene. The Integrated Dual Imaging Detector (IDID) consists of a polarizing beamsplitter bonded to a charge-coupled device (CCD), with signal-analysis circuitry and analog-to-digital converters, all integrated on a silicon chip. It should be capable of 1:10(exp 4) polarization discrimination. The IDID should simplify the design and operation of imaging polarimeters and spectroscopic imagers used, for example, in atmospheric and solar research. Innovations in the IDID include (1) two interleaved 512 x 1024-pixel imaging arrays (one for each polarization plane); (2) large dynamic range (well depth of 10(exp 6) electrons per pixel); (3) simultaneous readout of both images at 10 million pixels per second each; (4) on-chip analog signal processing to produce polarization maps in real time; (5) on-chip 10-bit A/D conversion. When used with a lithium-niobate Fabry-Perot etalon or other color filter that can encode spectral information as polarization, the IDID can collect and analyze simultaneous images at two wavelengths. Precise photometric analysis of molecular or atomic concentrations in the atmosphere is one suggested application. When used in a solar telescope, the IDID will charge the polarization, which can then be converted to maps of the vector magnetic fields on the solar surface.

Rust, D. M.↗

GOME wavelength calibration using solar and atmospheric spectra

Spectral information in the global ozone monitoring experiment (GOME) solar irradiance spectra and GOME earth radiance spectra are used in conjunction with the GOME solar reference spectrum to provide absolute vacuum internal wavelength calibration for GOME. Two methods for wavelength calibration of GOME data are investigated. The first employs chi-square minimization of a merit function involving wavelength and the GOME slit function. It is quite robust and requires little GOME data in the processing (calibration window regions from 15 to 40 pixels). The second employs cross correlation of GOME data and the solar reference spectrum in the Fourier transform domain, using a procedure in the image reduction and analysis facility (IRAF) software system developed for the determination of galaxy redshifts. It also requires small amounts of GOME data (calibration window regions with from 10 to 15 pixels). Both methods provide absolute wavelength calibration accurate to a small fraction of a GOME pixel across the entire GOME spectrum, and to 0.001 nm over much of the range.

Caspar, C.↗

Cloud Filtering Using a Bi-Spectral Spatial Coherence Approach

The research in this paper focuses on describing a technique developed for cloud filtering using a bi-spectral approach on GOES-8/9 Imager data. The application was developed for use with infrared retrievals of geophysical parameters in mind, where cloud cover contaminates the derived product. However, numerous potential applications of the technique exist. The technique will be described and a preliminary validation of the algorithm will be presented. Although initially based on the spatial coherence approach from Coakley and Brethereton (1982), it has evolved to utilize a difference image of the I I and 3.9 micrometer channels on the GOES-8/9 Imager. This image is very similar to that produced by Nelson and Ellrod (1996). During the daytime the technique makes use of the varying solar reflectance in the 3.9 micrometer channel by clouds and land to identify cloudy pixels. While at night, the technique makes use of the varying emissivity of the clouds in the scene to discriminate between clear and cloudy pixels. The technique applies three basic threshold tests to produce the final cloud filtered image: 1) a standard deviation threshold to detect the spatial variance in the scene, 2) a difference threshold between adjacent pixels, and 3) a simple infrared temperature threshold. The first test is applied to the entire image at once, then in a second pass the next two tests are applied. The final infrared temperature threshold is only meant to identify the coldest clouds that might pass the previous tests. The technique performs well during the daytime, while nighttime performance is degraded but is promising. The technique has proven to be robust and shows great promise of meeting its original goal of cloud filtering for use in an infrared retrieval algorithm for use in climate studies.

Guillory, Anthony R.↗

Cloud Filtering Using a Bi-Spectral Spatial Coherence Approach

The research in this paper focuses on describing a technique developed for cloud filtering using a bi-spectral approach on GOES-8/9 Imager data. The application was developed for use with infrared retrievals of geophysical parameters in mind, where cloud cover contaminates the derived product. However, numerous potential applications of the technique exist. The technique will be described and a preliminary validation of the algorithm will be presented. Although initially based on the spatial coherence approach from Coakley and Brethereton (1982), it has evolved to utilize a difference image of the 11 and 3.9 micrometer channels on the GOES-8/9 Imager. This image is very similar to that produced by Nelson and Ellrod (1996). During the daytime the technique makes use of the varying solar reflectance in the 3.9 micrometer channel by clouds and land to identify cloudy pixels. While at night, the technique makes use of the varying emissivity of the clouds in the scene to discriminate between clear and cloudy pixels. The technique applies three basic threshold tests to produce the final cloud filtered image: 1) a standard deviation threshold to detect the spatial variance in the scene, 2) a difference threshold between adjacent pixels, and 3) a simple infrared temperature threshold. The first test is applied to the entire image at once, then in a second pass the next two tests are applied. The final infrared temperature threshold is only meant to identify the coldest clouds that might pass the previous tests. The technique performs well during the daytime, while nighttime performance is degraded but is promising. The technique has proven to be robust and shows great promise of meeting its original goal of cloud filtering for use in an infrared retrieval algorithm for use in climate studies.

Guillory, Anthony R.↗

An Acoustic Charge Transport Imager for High Definition Television

This project, over its term, included funding to a variety of companies and organizations. In addition to Georgia Tech these included Florida Atlantic University with Dr. William E. Glenn as the P.I., Kodak with Mr. Mike Richardson as the P.I. and M.I.T./Polaroid with Dr. Richard Solomon as the P.I. The focus of the work conducted by these organizations was the development of camera hardware for High Definition Television (HDTV). The focus of the research at Georgia Tech was the development of new semiconductor technology to achieve a next generation solid state imager chip that would operate at a high frame rate (I 70 frames per second), operate at low light levels (via the use of avalanche photodiodes as the detector element) and contain 2 million pixels. The actual cost required to create this new semiconductor technology was probably at least 5 or 6 times the investment made under this program and hence we fell short of achieving this rather grand goal. We did, however, produce a number of spin-off technologies as a result of our efforts. These include, among others, improved avalanche photodiode structures, significant advancement of the state of understanding of ZnO/GaAs structures and significant contributions to the analysis of general GaAs semiconductor devices and the design of Surface Acoustic Wave resonator filters for wireless communication. More of these will be described in the report. The work conducted at the partner sites resulted in the development of 4 prototype HDTV cameras. The HDTV camera developed by Kodak uses the Kodak KAI-2091M high- definition monochrome image sensor. This progressively-scanned charge-coupled device (CCD) can operate at video frame rates and has 9 gm square pixels. The photosensitive area has a 16:9 aspect ratio and is consistent with the "Common Image Format" (CIF). It features an active image area of 1928 horizontal by 1084 vertical pixels and has a 55% fill factor. The camera is designed to operate in continuous mode with an output data rate of 5MHz, which gives a maximum frame rate of 4 frames per second. The MIT/Polaroid group developed two cameras under this program. The cameras have effectively four times the current video spatial resolution and at 60 frames per second are double the normal video frame rate.

Hunt, William D.↗

Current Status of Aerosol Retrievals from TOMS

Properties of atmospheric aerosols over all land and water surfaces are retrieved from TOMS measurements of backscattered radiances. The TOMS technique, uses observations at two wavelengths. In the near ultraviolet (330-380 nm) range, where the effects of gaseous absorption are negligible. The retrieved properties are optical depth and a measure of aerosol absorptivity, generally expressed as single scattering albedo. The main sources of error of the TOMS aerosol products are sub-pixel cloud contamination and uncertainty on the height above the surface of UV-absorbing aerosol layers. The first error source is related to the large footprint (50 x 50 km at nadir) of the sensor, and the lack of detection capability of sub-pixel size clouds. The uncertainty associated with the height of the absorbing aerosol layers, on the other hand, is related to the pressure dependence of the molecular scattering process, which is the basis of the near-UV method of absorbing aerosol detection. The detection of non-absorbing aerosols is not sensitive to aerosol layer height. We will report on the ongoing work to overcome both of these difficulties. Coincident measurements of high spatial resolution thermal infrared radiances are used to address the cloud contamination issue. Mostly clear scenes for aerosol retrieval are selected by examining the spatial homogeneity of the IR radiance measurements within a TOMS pixel. The approach to reduce the uncertainty associated with the height of the aerosol layer by making use of a chemical transport model will also be discussed.

Torres, O.↗