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Report presents preliminary analysis of performance of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), a scanning instrument producing images at wavelengths from 400 to 2,450 nm. Includes four spectrometers connected by optical fibers to common set of foreoptics. Focuses upon calibration of instrument and determination of reflectance of surface of Earth from its measurements.
To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors.
Combination of established statistical and filtering techniques yields improved estimates of signal-to-noise ratio (SNR) of multispectral imagery produced by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Method yields more accurate estimate of random variability in AVIRIS imagery. Combination of techniques called "geostatistical" method. In first step of method, periodic noise removed by notch filtering in frequency domain. In subsequent steps, sensor noise and variability within picture elements isolated by use of semi-variance of picture elements.
Topics presented include the evolution of the Airborne Visible/Infrared Imaging Spectrometer flight and ground data processing system, direct mineral identification with Geoscan Mk II Advanced Multispectral Scanner, a new approach to imaging spectroscopy, and a linear-wedge spectrometer. Also presented are the effects of moisture content and chemical composition on the near-infrared spectra of forest foliage, change detection in vegetation using 1989 AVIRIS data, and the inversion of high-spectral-resolution data.
Airborne Visible/Infrared Imaging Spectrometer data covering the wavelength range between 2000 and 2400 nm are examined for their ability to display the diagnostic mineral absorption features of certain alteration minerals, employing various data processing techniques. The techniques may be separated into two broad categories: scene based techniques that use parameters derived from the data themselves, and correction techniques utilizing external information such as solar/atmospheric models. Results indicate that the data corrected utilizing the LOWTRAN 7 atmospheric transfer code constrained with local weather station data are the most effective at showing the diagnostic absorption features of the regions of known mineralogy and introduce the least number of artifacts into the data.
A method for retrieving surface reflectances from spectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is being developed. In this method, the integrated water vapor amount on a pixel by pixel basis is derived from the 0.94- and 1.14-micron water vapor features. The water vapor, carbon dioxide (CO2), oxygen (O2) and methane (CH4) transmission spectrum in the 0.4-2.5 micron region is calculated. The derived water vapor value and the solar and observational geometry are used in the calculation. The AVIRIS spectrum is ratioed against the transmission spectrum to obtain the surface reflectance spectrum. Major mineral absorption features near 2.2 microns in retrieved reflectance spectra can be identified. Different vegetation absorption characteristics are observed. At present, the method is most useful for deriving surface reflectances from AVIRIS data measured on clear days with high visibilities.
A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.
A review of recent progress in the field of imaging spectrometry is presented based on the 14 articles comprising the special issue of this journal. The results presented were achieved through research done with data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), the first imaging spectrometer to cover the full solar reflected portion of the spectrum. The majority of the early work in imaging spectrometry prior to AVIRIS focused largely on geological applications and specifically surface mineral identification. In the past 5 years, the range of applications has expanded into the scientific disciplines of ecology, hydrology, oceanography, and atmospheric science. Significant progress has also been made in sensor design and calibration, and information extraction. NASA plans to place high spectral resolution sensors in earth orbit within the next few years; two have been flown already on recent planetary missions and have proven to be of great value to the study of planetary surfaces and atmospheres. The work presented in this issue will lead directly to more effective utilization of imaging spectrometry in the study of the earth. We present a discussion of future trends in imaging spectrometry at the conclusion of this article.
A method for retrieving 'scaled surface reflectances' assuming horizontal surfaces having Lambertian reflectances from spectral data collected by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is presented here. In this method, the integrated water vapor amount on a pixel by pixel basis is derived from the 0.94 micron and 1.14 micron water vapor absorption features. The transmission spectra of H2O, CO2, O3, N2O, CO, CH4, and O2 in the 0.4-2.5 micron region are simulated. The scattering effect due to atmospheric molecules and aerosols is modeled with the 5S computer code. The AVIRIS radiances are divided by solar irradiances above the atmosphere to obtain the apparent reflectances. The scaled surface reflectances are derived from the apparent reflectances using the simulated atmospheric gaseous transmittances and the simulated molecular and aerosol scattering data. The scaled surface reflectances differ from the real surface reflectances by a multiplicative factor. In order to convert the scaled surface reflectances into real surface reflectances, the slopes and aspects of the surfaces must be known.
Data on chlorophyll content and bathymetry of Lake Tahoe obtained on August 9, 1990 by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) are compared to concurrent in situ surface and in-water measurements. Measured parameters included profiles of percent transmission of monochromatic light, stimulated chlorophyll fluorescence, photosynthetically available radiation, spectral upwelling and downwelling irradiance, and upwelling radiance. Several analyses were performed illustrating the utility of the AVIRIS over a dark water scene. Image-derived chlorophyll concentration compared extremely well with that measured with bottle samples. A bathymetry map of the shallow parts of the lake was constructed which compares favorably with published lake soundings.
This study relates Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery to ground measurements of vegetation distribution, physiology, and productivity at Stanford University's Jasper Ridge Biological Preserve. Primary efforts focused on a 9-ha region of annual grassland where we completed a detailed ground-based study in conjunction with a 15 May 1991 AVIRIS overflight. Spectral mixture analysis and the normalized difference vegetation index (NDVI) calculated from AVIRIS data were used to evaluate spatial patterns of vegetation type, productivity, and potential physiological activity. Concurrent ground sampling revealed a high degree of correlation between NDVI and estimates of canopy chemistry, structure, productivity, and CO2 flux, supporting the use of imaging spectrometry to estimate spatial and temporal trends in vegetation physiology and productivity in this relatively simple grassland ecosystem. Geostatistical analyses of both ground and AVIRIS data supported the conclusion that the AVIRIS pixel size was suitable for describing the influence of major landscape features in this grassland and that spatial detail would be lost at slightly larger pixel sizes typical of other imaging spectrometers.
The feasibility of using imaging spectrometry in studies of playa evaporites is demonstrated by mapping efflorescent salt crusts in Death Valley (California), using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data and a recently developed least-squares spectral band-fitting algorithm. It is shown that it was possible to remotely identify eight different saline minerals, including three borates that have not been previously reported for the Death Valley efflorescent crusts: hydroboracite, pinnoite, and rivadavite. The three borates are locally important phases in the crusts; at least one of them, rivadavite, appears to be forming directly from brine.
High spectral and spatial resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery is used to study the effects of spatial resolution upon fair weather cumulus cloud optical thickness retrievals. As a preprocessing step, a variation of the Gao and Goetz three-band ratio technique is used to discriminate clouds from the background. The combination of the elimination of cloud shadow pixels and using the first derivative of the histogram allows for accurate cloud edge discrimination. The data are progressively degraded from 20 m to 960 m spatial resolution. The results show that retrieved cloud area increases with decreasing spatial resolution. The results also show that there is a monotonic decrease in retrieved cloud optical thickness with decreasing spatial resolution. It is also demonstrated that the use of a single, monospectral reflectance threshold is inadequate for identifying cloud pixels in fair weather cumulus scenes and presumably in any inhomogeneous cloud field. Cloud edges have a distribution of reflectance thresholds. The incorrect identification of cloud edges significantly impacts the accurate retrieval of cloud optical thickness values.
An evaluation was performed on SWIR (2000-2400 nm) data from two airborne remote sensing systems for discriminating and identifying alteration minerals at Cuprite, Nevada. The data were acquired by the NASA Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) and the GEOSCAN Mk II multispectral scanner. The evaluation involved comparison of processed imagery and image-derived spectra with existing alteration maps and laboratory spectra of rock samples from Cuprite. Results indicate that both the AVIRIS and GEOSCAN data permit the discrimination of areas of alunite, buddingtonite, kaolinite, and silicification using color composite images formed from three SWIR bands processed with either the decorrelation stretch or a log residual algorithm. The laboratory spectral features alunite, kaolinite and buddingtonite could be seen clearly only in the log residual processed AVIRIS data. However, this does not preclude their identification with the GEOSCAN data.
Report presents experimental intercomparison among measurements by four spectrometric instruments for determining concentration of atmospheric water vapor. Three instruments ground-based and needed to provide independent data to calibrate and validate measurements taken by fourth instrument, which is airborne visible/infrared imaging spectrometer (AVIRIS). Remote down-looking instruments like AVIRIS increases accuracy and coverage of water-vapor measurements.
On 7 Mar. 1991, an in-flight calibration experiment was held at the Ivanpah Playa in southeastern California for the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer. Five AVIRIS overflights were acquired of a calibration target designated on the Ivanpah Playa surface. At the time of the overflights, the reflectance of the calibration target was measured with a field spectrometer. In addition, the atmospheric optical depths and water vapor abundance were measured from a radiometer station adjacent to the calibration target. These in-situ measurements were used to constrain the MODTRAN radiative transfer code to model the upwelling spectral radiance incident to the sensor aperture during the overflights. Analyses of this modeled radiance in conjunction with the laboratory-calibrated radiance were used to determine the spectral and radiometric calibration of AVIRIS while in flight.
Five flight lines of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired over the Dolly Varden Mountains in northeastern Nevada on 2 June 1989. Signal-to-noise ratio values are given. The empirical line method was used to convert AVIRIS radiance values to reflectance. This method involves calculating gain and offset values for each band. These values are based upon a comparison of the imaging spectrometer data and field reflectance measurements, both taken over the same ground targets. The targets used were a dark andesite flow and a bright playa.
In May 1991, coincident with an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) overflight, a ground-based study covering 9 hectares of an annual grassland was completed. There were two goals of this ground study: (1) obtain ecologically and physiologically meaningful data for relating AVIRIS images to canopy structure, biochemistry, and physiology; and (2) evaluate the suitability of the 20-m AVIRIS pixel size for depicting detailed spatial patterns of productivity.