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At least 163 records · Page 9

Derivation of scaled surface reflectances from AVIRIS data

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.

Gao, Bo-Cai↗

Software for the derivation of scaled surface reflectances from AVIRIS data

An operational software program is now available for deriving 'scaled surface reflectances' from spectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The program simulates both the atmospheric scattering and absorption effects. Brief descriptions of the algorithm, inputs, outputs, the limitations of the software, and procedures for obtaining the software are given.

Gao, Bo-Cai↗

Estimation of Biomass Fire Temperature and Areal Extent from Calibrated AVIRIS Spectra

This paper describes an approach to derive a range of biomass fire parameters from spectra measured by NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS measures images of the upwelling spectral radiance from 400 to 2500 nm at 10nm intervals. Images are measured of 11 by up to 100 km with 20 by 20 m spatial resolution.

Biomass AVRIS biomass fire smoke cloud aerosol and↗

Lossless compression of AVIRIS data: Comparison of methods and instrument constraints

A family of lossless compression methods, allowing exact image reconstruction, are evaluated for compressing Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) image data. The methods are used on Differential Pulse Code Modulation (DPCM). The compressed data have an entropy of order 6 bits/pixel. A theoretical model indicates that significantly better lossless compression is unlikely to be achieved because of limits caused by the noise in the AVIRIS channels. AVIRIS data differ from data produced by other visible/near-infrared sensors, such as LANDSAT-TM or SPOT, in several ways. Firstly, the data are recorded at a greater resolution (12 bits, though packed into 16-bit words). Secondly, the spectral channels are relatively narrow and provide continuous coverage of the spectrum so that the data in adjacent channels are generally highly correlated. Thirdly, the noise characteristics of the AVIRIS are defined by the channels' Noise Equivalent Radiances (NER's), and these NER's show that, at some wavelengths, the least significant 5 or 6 bits of data are essentially noise.

Roger, R. E.↗

AVIRIS ground data processing system

During the last year and a half, Feb. 1991 to Jun. 1992, a major upgrade of the Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) ground data processing system took place. Both the hardware and software components were changed significantly to improve the processing capacity and performance and to structure a data facility capable of handling the projected work load into the near future. A summary report of these changes and some projections for the future are provided. The objectives of the AVIRIS data facility are to decommutate and archive AVIRIS data and to provide raw or radiometrically calibrated data products to the science investigator. These primary objectives have not changed from the initial concepts. The upgrade effort has greatly improved the processing system. These objectives can now be accomplished in a more timely fashion at a reasonable cost and there is sufficient capacity to manage the current processing load and provide for future growth. The method of implementation added the flexibility to provide better service to the investigator and allow for future changes.

Hansen, Earl G.↗

Estimating The SNR Of AVIRIS Data

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.

Curran, Paul J.↗

In-flight calibration of the spectral and radiometric characteristics of AVIRIS in 1991

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.

Green, Robert O.↗

Proceedings of the Tenth JPL Airborne Earth Science Workshop

This publication contains the proceedings of the AVIRIS Earth Science and Applications Workshop - a forum held to report science research and applications results with spectral images measured by the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). These papers were presented at the Jet Propulsion Laboratory on February 27 and 28 and March 1 and 2, 2001.

Green, Robert O.↗

Mineral Mapping Using AVIRIS Data at Ray Mine, AZ

Imaging Spectroscopy enables the identification and mapping of surface mineralogy over large areas. This study focused on assessing the utility of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data for environmental impact analysis over the Environmental Protection Agency's (EPA) high priority Superfund site Ray Mine, AZ. Using the Spectral Angle Mapper (SAM) algorithm to analyze AVIRIS data makes it possible to map surface materials that are indicative of acid generating minerals. The improved performance of the AVIRIS sensor since 1996 provides data with sufficient signal to noise ratio to characterize up to 8 image endmembers. Specifically we employed SAM to map minerals associated with mine generated acid waste, namely jarositc, goethite, and hematite, in the presence of a complex mineralogical background.

McCubbin, Ian↗

The Hyperspectral Imager Aboard the SSTI's Lewis Spacecraft: A Comparison with AVIRIS

This paper compares the performance and operational parameters of the Hyperspectral Imager (HSI), scheduled for launch aboard the Lewis spacecraft in July 1996, with those of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The HSI is a pushbroom, imaging spectrometer with 30 meter spatial resolution, generating 384 spectral channels over the range 400 to 2500 nm at 5.0 to 6.4 nm resolution for each of its 256 crosstrack pixels.

Sokolowski, James K.↗

AVIRIS Measurements of Spectral Reflectance Characteristics of Whitecaps

The spectral reflectance of oceanic whitecaps in the visible and near infrared was investigated using high-altitude, 20 m resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measurements off the Southern California coast. The whitecap effect on surface reflectance was expressed as a function of the difference between the reflectance of pixels contaminated by whitecaps and of adjacent pixels free of whitecaps. Whitecap reflectance was found to decrease substantially in the near infrared, by about 40% at 850 nm and 80% at 1,600 nm, in agreement with previous measurements in the coastal zone and the open ocean. The spectral dependence of whitecap reflectance appears to be fairly independent of environmental conditions, making it easy to take into account the resulting and significant effects in ocean color and aerosol remote sensing algorithms.

Frouin, Robert↗

Estimating snow grain size using AVIRIS data

Estimates of snow grain size for the near-surface snow layer were calculated for the Tioga Pass region and Mammoth Mountain in the Sierra Nevada, California, using an inversion technique and data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The Tioga Pass and Mammoth Mountain single-band AVIRIS radiance images were atmospherically corrected to obtain surface reflectance. A discrete-ordinate model was used to calculate directional reflectance as a function of snowpack grain size for a wide range of snow grain radii. The resulting radius vs. reflectance curves were each fit using a nonlinear least squares technique which provided a means of transforming surface reflectance in each AVIRIS image to optically equivalent grain size on a per-pixel basis. The model results and grain size estimates derived from the AVIRIS data show that, for solar incidence angles between 0 and 30, the technique provides good estimates of grain size. This work provides the first quantitative estimates for grain size using data acquired from an airborne remote sensing instrument and is an important step in improving our ability to retrieve snow physical properties independent of field measurements.

Nolin, Anne W.↗

Mapping the spectral variability in photosynthetic and non-photosynthetic vegetation, soils, and shade using AVIRIS

The primary objective of this research was to map as many spectrally distinct types of green vegetation (GV), non-photosynthetic vegetation (NPV), shade, and soil (endmembers) in an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) scene as is warranted by the spectral variability of the data. Once determined, a secondary objective was to interpret these endmembers and their abundances spatially and spectrally in an ecological context.

Roberts, Dar A.↗

Removing Atmospheric Effects From AVIRIS Data for Surface Reflectance Retrievals

Analysis of high resolution imaging spectrometer data requires a thorough compensation for atmospheric absorption and scattering. 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-micrometer water vapor features. The water vapor, carbon dioxide (CO2), oxygen (O2) and methane (CH4) transmission spectrum in the 0.4-2.5 micrometer region is calculated. The derived water vapor value and the solar and observational geometry are used in the spectral calculation. The AVIRIS spectrum is ratioed against the transmission spectrum to obtain the surface reflectance spectrum. Major mineral absorption features near 2.2 micrometer 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. Atmospheric scattering effects will be included in our spectral calculations in the near future.

Gao, Bo-Cai↗

Mapping playa evaporite minerals with AVIRIS data - A first report from Death Valley, California

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.

Crowley, James K.↗

Determination of in-flight AVIRIS spectral, radiometric, spatial and signal-to-noise characteristics using atmospheric and surface measurements from the vicinity of the rare-earth-bearing carbonatite at Mountain Pass, California

An assessment of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) performance was made for a flight over Mountain Pass, California, July 30, 1987. The flight data were reduced to reflectance using an empirical algorithm which compensates for solar, atmospheric and instrument factors. AVIRIS data in conjunction with surface and atmospheric measurements acquired concurrently were used to develop an improved spectral calibration. An accurate in-flight radiometric calibration was also performed using the LOWTRAN 7 radiative transfer code together with measured surface reflectance and atmospheric optical depths. A direct comparison with coincident Thematic Mapper imagery of Mountain Pass was used to demonstrate the high spatial resolution and good geometric performance of AVIRIS. The in-flight instrument noise was independently determined with two methods which showed good agreement. A signal-to-noise ratio was calculated using data from a uniform playa. This ratio was scaled to the AVIRIS reference radiance model, which provided a basis for comparison with laboratory and other in-flight signal-to-noise determinations.

Green, Robert O.↗