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Many algorithms for spectral analysis of imaging spectroscopy data of the Earth's surface require that the data be calibrated to surface reflectance. Calibration requires removing instrumental response, solar irradiance, atmospheric transmittance, and atmospheric scattering from the radiance detected at the sensor.
The Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) measures the total upwelling spectral radiance from 400 to 2500 nm sampled at 10 nm intervals. The instrument acquires spectral data at an altitude of 20 km above sea level, as images of 11 by up to 100 km at 17x17 meter spatial sampling. We have developed a nonlinear spectral fitting algorithm coupled with a radiative transfer code to derive the total path water vapor from the spectrum, measured for each spatial element in an AVIRIS image. The algorithm compensates for variation in the surface spectral reflectance and atmospheric aerosols. It uses water vapor absorption bands centered at 940 nm, 1040 nm, and 1380 nm. We analyze data sets with water vapor abundances ranging from 1 to 40 perceptible millimeters. In one data set, the total path water vapor varies from 7 to 21 mm over a distance of less than 10 km. We have analyzed a time series of five images acquired at 12 minute intervals; these show spatially heterogeneous changes of advocated water vapor of 25 percent over 1 hour. The algorithm determines water vapor for images with a range of ground covers, including bare rock and soil, sparse to dense vegetation, snow and ice, open water, and clouds. The precision of the water vapor determination approaches one percent. However, the precision is sensitive to the absolute abundance and the absorption strength of the atmospheric water vapor band analyzed. We have evaluated the accuracy of the algorithm by comparing several surface-based determinations of water vapor at the time of the AVIRIS data acquisition. The agreement between the AVIRIS measured water vapor and the in situ surface radiometer and surface interferometer measured water vapor is 5 to 10 percent.
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.
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
Ultraviolet-visible-infrared mapping digital array scanned interferometers for lunar compositional surveys was developed. The research has defined a no-moving-parts, low-weight and low-power, high-throughput, and electronically adaptable digital array scanned interferometer that achieves measurement objectives encompassing and improving upon all the requirements defined by the LEXSWIG for lunar mineralogical investigation. In addition, LUMIS provides a new, important, ultraviolet spectral mapping, high-spatial-resolution line scan camera, and multispectral camera capabilities. An instrument configuration optimized for spectral mapping and imaging of the lunar surface and provide spectral results in support of the instrument design are described.
Two Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral images selected from the Los Angeles area, one representing urban and the other, rural, were used to examine their spatial complexity across their entire spectrum of the remote sensing data. Using the ICAMS (Image Characterization And Modeling System) software, we computed the fractal dimension values via the isarithm and triangular prism methods for all 224 bands in the two AVIRIS scenes. The resultant fractal dimensions reflect changes in image complexity across the spectral range of the hyperspectral images. Both the isarithm and triangular prism methods detect unusually high D values on the spectral bands that fall within the atmospheric absorption and scattering zones where signature to noise ratios are low. Fractal dimensions for the urban area resulted in higher values than for the rural landscape, and the differences between the resulting D values are more distinct in the visible bands. The triangular prism method is sensitive to a few random speckles in the images, leading to a lower dimensionality. On the contrary, the isarithm method will ignore the speckles and focus on the major variation dominating the surface, thus resulting in a higher dimension. It is seen where the fractal curves plotted for the entire bandwidth range of the hyperspectral images could be used to distinguish landscape types as well as for screening noisy bands.
One of the instruments that has been developed to fly on the Space Shuttle is the Imaging Spectrometric Observatory, an array of five imaging spectrometers to cover the 300-12,000-A wavelength range. In this paper the spectrometer designed to operate in the extreme ultraviolet is described. The instrument is intended for studies of the thermosphere and magnetosphere and support of various plasma experiments to be performed from the Shuttle. The design is modular so that various components such as gratings and detectors can be changed and optimized for a range of specific studies following the first survey mission. The detector is an intensified 2-D CCD which permits simultaneous spectral and spatial imaging. The spectral multiplexing gives the spectrometer a considerable speed advantage. The instrument has a small field of view and is thus capable of obtaining much needed scale height information on the atmospheric EUV emissions. Operating from the Shuttle, global and temporal coverage will be obtained, and the EUV data will be enhanced by the simultaneously acquired UV, visible, and near-IR observations.
Augmenting spectral data with spatial information for image classification has recently gained significant attention, as classification accuracy can often be improved by extracting spatial information from neighboring pixels. In this paper, we propose a new framework in which active learning (AL) and hierarchical segmentation (HSeg) are combined for spectral-spatial classification of hyperspectral images. The spatial information is extracted from a best segmentation obtained by pruning the HSeg tree using a new supervised strategy. The best segmentation is updated at each iteration of the AL process, thus taking advantage of informative labeled samples provided by the user. The proposed strategy incorporates spatial information in two ways: 1) concatenating the extracted spatial features and the original spectral features into a stacked vector and 2) extending the training set using a self-learning-based semi-supervised learning (SSL) approach. Finally, the two strategies are combined within an AL framework. The proposed framework is validated with two benchmark hyperspectral datasets. Higher classification accuracies are obtained by the proposed framework with respect to five other state-of-the-art spectral-spatial classification approaches. Moreover, the effectiveness of the proposed pruning strategy is also demonstrated relative to the approaches based on a fixed segmentation.
In August and September of 1995 the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) was deployed to Brazil as part of the NASA Smoke Cloud Aerosol and Radiation experiment in Brazil (SCAR-B). AVIRIS measures spectra from 400 to 2500 nm at 10-nm intervals. These spectra are acquired as images with dimensions of 11 by up to 800 km with 20-m spatial resolution. Spectral images measured by AVIRIS are spectrally, radiometrically, and spatially calibrated. During the SCAR-B deployment, AVIRIS measured more than 300 million spectra of regions of Brazil. A portion of these spectra were acquired over areas of actively burning fires. Actively burning fires emit radiance in the AVIRIS spectral range as a function of temperature. This emitted radiance is expressed from the 2500-nm end of the AVIRIS spectrum to shorter wavelengths as a function of intensity and modeled by the Planck function. The objective of this research and analysis was to use spectroscopic methods to determine the minimum high temperature of the most intense fires measured in the SCAR-B AVIRIS data set. Spectra measured by AVIRIS with hot sources have been previously examined for volcanic lava.
In August and September of 1995 the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) was deployed to Brazil as part of the NASA Smoke Cloud Aerosol and Radiation experiment in Brazil (SCAR-B). AVIRIS measures spectra from 400 to 2500 nm at 10-nm intervals. These spectra are acquired as images with dimensions of 11 by up to 800 km with 20-m spatial resolution. Spectral images measured by AVIRIS are spectrally, radiometrically, and spatially calibrated. During the SCAR-B deployment, AVIRIS measured more than 300 million spectra of regions of Brazil. A portion of these spectra were acquired over areas of actively burning fires. Actively burning fires emit radiance in the AVIRIS spectral range as a function of temperature. This emitted radiance is expressed from the 2500-nm end of the AVIRIS spectrum to shorter wavelengths as a function of intensity and modeled by the Planck function.. The objective of this research and analysis was to use spectroscopic methods to determine the minimum high temperature of the most intense fires measured in the SCAR-B AVIRIS data set. Spectra measured by AVIRIS with hot sources have been previously examined for volcanic lava and fires in Brazil.
The objective of this program was to map the abundances of major elements such as O, Si, S, and Fe in the supernova remnants, Tycho and Cas A. The approach was based upon using archival cosmic X-ray data from several space missions, notably, the Einstein Observatory, EXOSAT, ROSAT, BBSRT, and ASCA. Two of the missions, Einstein and ROSAT, had high resolution telescopes that provided excellent images, but no spectral information. Two missions with much poorer resolution telescopes, BBXRT and ASCA, gave good spectral information through pulse height of signals in their cooled solid state detector, but rather crude spatial information. Our goal was to extract spectral information from the combined analysis of the Einstein and ROSAT images of Cas A and Tycho and to verify or refine the spectral map by checking its agreement with the BBSRT or ASCA spectra results for larger regions. In particular, we note that the Einstein and ROSAT telescopes have different spectral responses. The Einstein bandwidth includes the 2-4 keV region which is absent from ROSAT. Hence, by forming linear combinations of the Einstein and ROSAT images, we are able to resolve the contributions of the 0.5-2 keV band from the 2-4 keV band. The former contains lines of O and Fe while the latter is dominated by Si and S. We correct for the expansion that has taken place in the remnants during the ten-year interval between the Einstein and ROSAT measurements, but we must assume that no significant spectral changes have occurred during that time. The analysis of the Tycho SNR was completed and the results have been published. A copy of the paper is included. The analysis of Cas A has proved to be more complicated. It is continuing with support from another program. Part of the problem may be due to difficulties in the aspect information which is needed to precisely register the ROSAT and Einstein images.
The quality of the quantitative spectral data collected by an imaging spectrometer instrument is critically dependent upon the accuracy of the spectral and radiometric calibration of the system. In order for the collected spectra to be scientifically useful, the calibration of the instrument must be precisely known not only prior to but during data collection. Thus, in addition to a rigorous in-lab calibration procedure, the airborne instruments designed and built by the NASA/JPL Imaging Spectroscopy Group incorporate an on board calibrator (OBC) system with the instrument to provide auxiliary in-use system calibration data. The output of the OBC source illuminates a target panel on the backside of the foreoptics shutter both before and after data collection. The OBC and in-lab calibration data sets are then used to validate and post-process the collected spectral image data. The resulting accuracy of the spectrometer output data is therefore integrally dependent upon the stability of the OBC source. In this paper we describe the design and application of the latest iteration of this novel device developed at NASA/JPL which integrates a halogen-cycle source with a precisely designed fiber coupling system and a fiber-based intensity monitoring feedback loop. The OBC source in this Airborne Testbed Spectrometer was run over a period of 15 hours while both the radiometric and spectral stabilities of the output were measured and demonstrated stability to within 1% of nominal.
We describe the tools and the underlying methods and principles for generating the spectral response functions for the four imaging instruments that were flown on the Hitomi x-ray astronomy satellite [Soft X-ray Spectrometer, or SXS; Soft X-ray Imager, or SXI, and two Hard X-ray Imagers, or HXI]. In essence, the spectral response function is a temporally and spatially averaged effective area and line-spread-function. For model-fittingx-ray spectra from an instrument, the spectral response function encapsulates the end-to-end physics of the entire system from telescope to detector, and also includes satellite attitude drift, exposure corrections, and in the case of the HXIs, drift in the telescope/detector alignment system. Accuracy in the construction of the spectral response functions is, therefore, critical to maximize the science return from the data.
Laboratory experiments designed to uncover mechanistic information about the spectral and spatial characteristics of shuttle glow were conducted. The luminescence was created when a pulse of O atoms traveling at orbital velocities was directed toward NO molecules previously adsorbed to aluminum, nickel, and Z306 Chemglaz (a common baffle black) coated surfaces held at various temperatures. Spectral and spatial measurements were made using a CCD imaging spectrometer. Corroborative spectral information was recorded in separate measurements using a scanning monochromator and gated photomultiplier arrangement. The e-folding distance at several temperatures was calculated from images of the surface glow using the photometrics image processing capability of the imaging spectrometer. The e-folding distance was not altered as a function of incoming O beam velocity. The results are presented and the observations provide direct evidence that the visible shuttle glow results from recombination of oxygen atoms and surface bound NO.
Image contrast enhancing by matching spectral reflectance or emittance characteristics
An electro-optical (E-O) imaging Fourier-transform spectrometer (IFTS), now under development, is a prototype of improved imaging spectrometers to be used for hyperspectral imaging, especially in the infrared spectral region. Unlike both imaging and non-imaging traditional Fourier-transform spectrometers, the E-O IFTS does not contain any moving parts. Elimination of the moving parts and the associated actuator mechanisms and supporting structures would increase reliability while enabling reductions in size and mass, relative to traditional Fourier-transform spectrometers that offer equivalent capabilities. Elimination of moving parts would also eliminate the vibrations caused by the motions of those parts. Figure 1 schematically depicts a traditional Fourier-transform spectrometer, wherein a critical time delay is varied by translating one the mirrors of a Michelson interferometer. The time-dependent optical output is a periodic representation of the input spectrum. Data characterizing the input spectrum are generated through fast-Fourier-transform (FFT) post-processing of the output in conjunction with the varying time delay.
The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases with time and also is a function of position on the detector. To complicate matters further, the satellite is 'wobbled', possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT High Resolution Imager (HRI) from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC (an x ray spectral fitting package) response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how, the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.
A program was designed toward the demonstration of the feasibility of using two dimensional recursive digital filters for subjective image processing applications that require rapid turn around. The concept of the use of a dedicated minicomputer for the processor for this application was demonstrated. The minicomputer used was the HP1000 series E with a RTE 2 disc operating system and 32K words of memory. A Grinnel 256 x 512 x 8 bit display system was used to display the images. Sample images were provided by NASA Goddard on a 800 BPI, 9 track tape. Four 512 x 512 images representing 4 spectral regions of the same scene were provided. These images were filtered with enhancement filters developed during this effort.