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Evaluation of the airborne visible-infrared imaging spectrometer for mapping subtle lithological variation

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), flown aboard the NASA ER-2 aircraft in 1987 and 1989, used four linear arrays and four individual spectrometers to collect data simultaneously from the 224 bands in a scanned 614 pixel-wide swath perpendicular to the aircraft direction. The research had two goals. One was to evaluate the AVIRIS data. The other was to look at the subtle lithological variation at the two test sites to develop a better understanding of the regional geology and surficial processes. The geometric characteristics of the data, adequacy of the spatial resolution, and adequacy of the spectral sampling interval are evaluated. Geologic differences at the test sites were mapped. They included lithological variation caused by primary sedimentary layering, facies variation, and weathering; and subtle mineralogical differences caused by hydrothermal alterations of igneous and sedimentary rocks. The investigation used laboratory, field, and aircraft spectral measurements; known properties of geological materials; digital image processing and spectrum processing techniques; and field geologic data to evaluate the selected characteristics of the AVIRIS data.

Kruse, Fred A.↗

Radiative transfer based retrieval of reflectance from calibrated radiance imagery measured by an imaging spectrometer for lithological mapping of the Clark Mountains, California

Spectral radiance imagery measured by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) are reduced to reflectance through compensation for atmospheric scattering, water vapor absorption, absorption of the well mixed gases, solar irradiance and the solar zenith angle. The LOWTRAN 7 (Kneizys et al., 1989) radiative transfer code form the basis for this retrieal. LOWTRAN 7 is constrained with water vapor determinations from the AVIRIS radiance data through an algorithm operating on the 940 nm atmospheric water band for every spatial element. In situ measurements of atmospheric optical depths are used to constrain the LOWTRAN 7 aerosol models. Accuracy of the retrieved reflectance spectra is evaluated with respect to surface spectra measured at the time of the overflight. The mineral bastnaesite is identified in the analysis of the retrieved reflectance imagery. These reflectance data provide a means to map the subtle mineral gradients in the PreCambrian block of the Clark Mountain range in southeastern California for geological analysis.

Green, Robert O.↗

Integration of visible-through microwave-range multispectral image data sets for geologic mapping

Multispectral remote sensing data sets collected during the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 in the southwestern U.S. were used to produce thematic image maps showing details of the surface geology. LANDSAT TM (Thematic Mapper) images were used to map the distribution of clays, carbonates, and iron oxides. AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data were used to identify and map calcite, dolomite, sericite, hematite, and geothite, including mixtures. TIMS (Thermal Infrared Multispectral Scanner) data were used to map the distribution of igneous rock phases and carbonates based on their silica contents. AIRSAR (Airborne Synthetic Aperture Radar) data were used to map surface textures related to the scale of surface roughness. The AIRSAR also allowed identification of previously unmapped fault segments and structural control of lithology and minerology. Because all of the above data sets were geographically referenced, combination of different data types and direct comparison of the results with conventional field and laboratory data sets allowed improved geologic mapping of the test site.

Kruse, Fred A.↗

Artificial intelligence for geologic mapping with imaging spectrometers

This project was a three year study at the Center for the Study of Earth from Space (CSES) within the Cooperative Institute for Research in Environmental Science (CIRES) at the University of Colorado, Boulder. The goal of this research was to develop an expert system to allow automated identification of geologic materials based on their spectral characteristics in imaging spectrometer data such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This requirement was dictated by the volume of data produced by imaging spectrometers, which prohibits manual analysis. The research described is based on the development of automated techniques for analysis of imaging spectrometer data that emulate the analytical processes used by a human observer. The research tested the feasibility of such an approach, implemented an operational system, and tested the validity of the results for selected imaging spectrometer data sets.

Kruse, F. A.↗

Cirrus cloud detection from airborne imaging spectrometer data using the 1.38 micron water vapor band

Using special images acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) at 20 km altitude, we show that wavelengths close to the center of the strong 1.38 micron water vapor band are useful for detecting thin cirrus clouds. The detection makes use of the fact that cirrus clouds are located above almost all the atmospheric water vapor. Because of the strong water vapor absorption in the lower atmosphere, AVIRIS channels near 1.38 micron receive little scattered solar radiance from the surface of low level clouds. When cirrus clouds are present, however, these channels receive large amounts of scattered solar radiance from the cirrus clouds. Our ability to determine cirrus cloud cover using space-based remote sensing will be improved if channels near the center of the 1.38 micron water vapor band are added to future satellites.

Gao, Bo-Cai↗

Terrestrial imaging spectrometry - Current status, future trends

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.

Vane, Gregg↗

The effect of spatial resolution upon cloud optical property retrievals. I - Optical thickness

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.

Feind, Rand E.↗

Comparison Of Measurments Of Atmospheric Water Vapor

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.

Bruegge, Carol J.↗

Hyperspectral modeling for extracting aerosols from aircraft/satellite data

Sensitivity studies using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) bands are currently under investigation. The objective of this research is to develop improved algorithms for the determination of aerosol type (e.g., presently described by S(sub 12). Preliminary computer calculations were made using LOWTRAN 7, which is the most advanced atmospheric code of the Air Force Geophysics Laboratory. LOWTRAN 7 permits the calculation of atmospheric transmission and absorption caused by aerosols and molecules along a non-homogeneous path for a variety of aerosol models. The calculations used the Navy Aerosol Model (NAM), which was constructed for the marine environment using a three component size distribution model. Calculations of the total transmittance (L(sub T)), the path radiance (L(sub P)), and the reflected radiance (L(sub r)) were made as a function of wavelength (lambda) from 0.4 to 2.4 microns for each of the 224 10 nm wide AVIRIS bands. These calculations were made for various types of atmospheres for the troposphere (0-2 km).

Hickman, G. Daniel↗

A linear spectral matching technique for retrieving equivalent water thickness and biochemical constituents of green vegetation

Over the last decade, technological advances in airborne imaging spectrometers, having spectral resolution comparable with laboratory spectrometers, have made it possible to estimate biochemical constituents of vegetation canopies. Wessman estimated lignin concentration from data acquired with NASA's Airborne Imaging Spectrometer (AIS) over Blackhawk Island in Wisconsin. A stepwise linear regression technique was used to determine the single spectral channel or channels in the AIS data that best correlated with measured lignin contents using chemical methods. The regression technique does not take advantage of the spectral shape of the lignin reflectance feature as a diagnostic tool nor the increased discrimination among other leaf components with overlapping spectral features. A nonlinear least squares spectral matching technique was recently reported for deriving both the equivalent water thicknesses of surface vegetation and the amounts of water vapor in the atmosphere from contiguous spectra measured with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The same technique was applied to a laboratory reflectance spectrum of fresh, green leaves. The result demonstrates that the fresh leaf spectrum in the 1.0-2.5 microns region consists of spectral components of dry leaves and the spectral component of liquid water. A linear least squares spectral matching technique for retrieving equivalent water thickness and biochemical components of green vegetation is described.

Gao, Bo-Cai↗

Tracking photosynthetic efficiency with narrow-band spectroradiometry

Narrow-waveband spectroradiometry presents the possibility of detecting subtle signals closely related to the current physiological state of vegetation. One such signal related to the epoxidation state of the xanthophyll cycle pigments, violaxanthin, antheraxanthin, and zeaxanthin is discussed. Recent advances in plant ecophysiology demonstrated a close relationship between these pigments and the regulatory state of photosystem 2 in photosynthesis. Our recent field studies of sunflower (Helianthus annuus) and oak (Quercus agrifolia) demonstrated that a 'xanthophyll signal' can be isolated from the diurnal reflectance spectra of intact canopies. Furthermore, the xanthophyll signal can be used to derive a 'physiological reflectance index' (PRI) that closely correlates with the actual photosynthetic efficiency (defined as the photosynthetic rate divided by the incident PAR) in closed canopies. If these signals were detectable in Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) images, they could lead to improved remote estimates of photosynthetic fluxes.

Gamon, John A.↗

Discrimination among semi-arid landscape endmembers using the Spectral Angle Mapper (SAM) algorithm

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired during three consecutive seasons of the year (26 Sep. 1989, 22 Mar. 1990, and 7 Aug. 1990) over an area of the High Plains east of Greeley, Colorado. This region contains extensive eolian deposits in the form of stabilized dune complexes (small scale parabolic dunes superimposed on large scale longitudinal and parabolic dunes). Due to the dunes' large scale (2-10 km) and low relief (1-5 m), the scaling relationships that contribute to the evolution of this landscape are nearly impossible to understand without the use of remote sensing. Additionally, climate models indicate that the High Plains could be one of the first areas to experience changes in climate caused by either global warming or cooling. During the past 10,000 years there were at least three periods of extensive sand activity, followed by periods of landscape stability, as shown in the stratigraphic record of this area. Therefore, if the past is an indication of the future, the monitoring of this landscape and its sensitive ecosystem is important for early detection of regional and global climate change.

Yuhas, Roberta H.↗

Imaging spectrometry of the Earth and other solar system bodies

Imaging spectrometry is a relatively new tool for remote sensing of the Earth and other bodies of the solar system. The technique dates back to the late 1970's and early 1980's. It is a natural extension of the earlier multi-spectral imagers developed for remote sensing that acquire images in a few, usually broad spectral bands. Imaging spectrometers combine aspects of classical spectrometers and imaging systems, making it possible to acquire literally hundreds of images of an object, each image in a separate, narrow spectral band. It is thus possible to perform spectroscopy on a pixel-by-pixel basis with the data acquired with an imaging spectrometer. Two imaging spectrometers have flown in space and several others are planned for future Earth and planetary missions. The French-built Phobos Infrared Spectrometer (ISM) was part of the payload of the Soviet Mars mission in 1988, and the JPL-built Near Infrared Mapping Spectrometer (NIMS) is currently en route to Jupiter aboard the Galileo spacecraft. Several airborne imaging spectrometers have been built in the past decade including the JPL-built Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) which is the only such sensor that covers the full solar reflected portion of the spectrum in narrow, contiguous spectral bands. NASA plans two imaging spectrometers for its Earth Observing System, the Moderate and the High Resolution Imaging Spectrometers (MODIS and HIRIS). A brief overview of the applications of imaging spectrometry to Earth science will be presented to illustrate the value of the tool to remote sensing and indicate the types of measurements that are required. The system design for AVIRS and a planetary imaging spectrometer will be presented to illustrate the engineering considerations and challenges that must be met in building such instruments. Several key sensor technology areas will be discussed in which miniaturization and/or enhanced performance through micromachining and nanofabrication may allow smaller, more robust, and more capable imaging spectrometers to be built in the future.

Vane, Gregg↗

Radiative transfer code based estimation of atmospheric parameters for inversion of imaging spectrometer measured radiance to apparent surface reflectance

Surface reflectance is required to quantitatively investigate molecular absorption and particle scattering properties of materials on the Earth's surface. Atmospheric aerosol optical depth, surface pressure and water vapor are required to constrain a radiative transfer code for the inversion of measured spectral radiance to apparent surface reflectance. A suite of algorithms using nonlinear least squares fitting techniques are described that directly estimate these atmospheric parameters from spectral radiance measured by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The derived atmospheric parameters are used to constrain a radiative transfer code for the inversion of the imaging spectrometer radiance to apparent reflectance. The derived apparent reflectance is validated with respect to in situ measurement on the same target.

Green, Robert O.↗

Estimation of aerosol optical depth and additional atmospheric parameters for the calculation of apparent reflectance from radiance measured by the Airborne Visible/Infrared Imaging Spectrometer

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures spatial images of the total upwelling spectral radiance from 400 to 2500 nm through 10 nm spectral channels. Quantitative research and application objectives for surface investigations require inversion of the measured radiance of surface reflectance or surface leaving radiance. To calculate apparent surface reflectance, estimates of atmospheric water vapor abundance, cirrus cloud effects, surface pressure elevation, and aerosol optical depth are required. Algorithms for the estimation of these atmospheric parameters from the AVIRIS data themselves are described. From these atmospheric parameters we show an example of the calculation of apparent surface reflectance from the AVIRIS-measured radiance using a radiative transfer code.

Green, Robert O.↗

Use of the Airborne Visible/Infrared Imaging Spectrometer to calibrate the optical sensor on board the Japanese Earth Resources Satellite-1

We describe an experiment to calibrate the optical sensor (OPS) on board the Japanese Earth Resources Satellite-1 with data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). On 27 Aug. 1992 both the OPS and AVIRIS acquired data concurrently over a calibration target on the surface of Rogers Dry Lake, California. The high spectral resolution measurements of AVIRIS have been convolved to the spectral response curves of the OPS. These data in conjunction with the corresponding OPS digitized numbers have been used to generate the radiometric calibration coefficients for the eight OPS bands. This experiment establishes the suitability of AVIRIS for the calibration of spaceborne sensors in the 400 to 2500 nm spectral region.

Green, Robert O.↗

Classification of high dimensional multispectral image data

A method for classifying high dimensional remote sensing data is described. The technique uses a radiometric adjustment to allow a human operator to identify and label training pixels by visually comparing the remotely sensed spectra to laboratory reflectance spectra. Training pixels for material without obvious spectral features are identified by traditional means. Features which are effective for discriminating between the classes are then derived from the original radiance data and used to classify the scene. This technique is applied to Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data taken over Cuprite, Nevada in 1992, and the results are compared to an existing geologic map. This technique performed well even with noisy data and the fact that some of the materials in the scene lack absorption features. No adjustment for the atmosphere or other scene variables was made to the data classified. While the experimental results compare favorably with an existing geologic map, the primary purpose of this research was to demonstrate the classification method, as compared to the geology of the Cuprite scene.

Hoffbeck, Joseph P.↗

The effect of signal noise on the remote sensing of Foliar biochemical concentration

Spectral measurements made using an imaging spectrometer contain systematic and random noise, while the former can be corrected the latter remains a source of error in the remotely sensed signal. A number of investigators have tried to determine the signal-to-noise-ratio (SNR) of the instrument, or the resultant imagery. However, the level of noise at which spectra are too noisy to be useful is not usually determined. The first attempt was by Goetz and Calvin, who suggested that the depth of the absorption feature should be at least an order of magnitude greater than the noise and more recently Dekker suggested a SNR of around 600:1 was required in visible/near infrared wavelengths to measure a 1/gl change in chlorophyll a concentration water. The wide range of applications of imaging spectroscopy make it difficult to set SNR specifications as they are dependent on a number of factors, one of the most important being reflectance of a particular target. For example, the SNR of imagery for vegetated targets is relatively low simply because vegetation has a relatively low level of reflectance. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is being used to estimate the concentration of biochemicals within vegetation canopies. This paper reports a study undertaken to identify first, wavebands that were highly correlated with foliar biochemical concentration and second, to determine how sensitive these correlations were to sensor noise.

Smith, Geoffrey M.↗