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NASA NTRS1993

Intercomparison of MAS, AVIRIS, and HIS data from FIRE cirrus 2

The NASA ER-2 flight on 5 Dec. 1991 is unique among the FIRE Cirrus 2 missions in that data were acquired simultaneously by the MODIS Airborne Simulator (MAS), the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and the High Resolution Interferometer Sounder (HIS). These data represent a unique source of information about the spatial and spectral properties of cirrus clouds. The MAS is a new instrument which will aid in defining algorithms and building an understanding of the ability of the Moderate Resolution Imaging Spectroradiometer (MODIS) to remotely sense atmospheric conditions for assessing global change. In order to establish confidence in the absolute calibration accuracy of the MAS radiances, an inter-comparison of MAS radiances with AVIRIS and HIS has been undertaken.

Gumley, Liam E.↗
NASA NTRS1993

Spectral decomposition of AVIRIS data

A set of techniques is presented that uses only information contained within a raw Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) scene to estimate and to remove additive components such as multiple scattering and instrument dark current. Multiplicative components (instrument gain, topographic modulation of brightness, atmospheric transmission) can then be normalized, permitting enhancement, extraction, and identification of relative reflectance information related to surface composition and mineralogy. The technique for derivation of additive-component spectra from a raw AVIRIS scene is an adaption of the 'regression intersection method' of Crippen. This method uses two surface units that are spatially extensive, and located in rugged terrain. For a given wavelength pair, subtraction of the derived additive component from individual band values will remove topography in both regions in a band/band ratio image. Normalization of all spectra in the scene to the average scene spectrum then results in cancellation of multiplicative components and production of a relative-reflectance scene. The resulting AVIRIS product contains relative-reflectance features due to mineral absorption that depart from the average spectrum. These features commonly are extremely weak and difficult to recognize, but they can be enhanced by using two simple 3-D image-processing tools. The validity of these techniques will be demonstrated by comparisons between relative-reflectance AVIRIS spectra and those derived by using JPL standard calibrations. The AVIRIS data used in this analysis were acquired over the Kelso Dunes area (34 deg 55' N, 115 deg 43' W) of the eastern Mojave Desert, CA (in 1987) and the Upheaval Dome area (38 deg 27' N, 109 deg 55' W) of the Canyonlands National Park, UT (in 1991).

Gaddis, Lisa↗
NASA NTRS1993

Remote sensing of smoke, clouds, and fire using AVIRIS data

Clouds remain the greatest element of uncertainty in predicting global climate change. During deforestation and biomass burning processes, a variety of atmospheric gases, including CO2 and SO2, and smoke particles are released into the atmosphere. The smoke particles can have important effects on the formation of clouds because of the increased concentration of cloud condensation nuclei. They can also affect cloud albedo through changes in cloud microphysical properties. Recently, great interest has arisen in understanding the interaction between smoke particles and clouds. We describe our studies of smoke, clouds, and fire using the high spatial and spectral resolution data acquired with the NASA/JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).

Gao, Bo-Cai↗
NASA NTRS1993

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.↗
NASA NTRS1993

The effects of AVIRIS atmospheric calibration methodology on identification and quantitative mapping of surface mineralogy, Drum Mountains, Utah

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures reflected light in 224 contiguous spectra bands in the 0.4 to 2.45 micron region of the electromagnetic spectrum. Numerous studies have used these data for mineralogic identification and mapping based on the presence of diagnostic spectral features. Quantitative mapping requires conversion of the AVIRIS data to physical units (usually reflectance) so that analysis results can be compared and validated with field and laboratory measurements. This study evaluated two different AVIRIS calibration techniques to ground reflectance: an empirically-based method and an atmospheric model based method to determine their effects on quantitative scientific analyses. Expert system analysis and linear spectral unmixing were applied to both calibrated data sets to determine the effect of the calibration on the mineral identification and quantitative mapping results. Comparison of the image-map results and image reflectance spectra indicate that the model-based calibrated data can be used with automated mapping techniques to produce accurate maps showing the spatial distribution and abundance of surface mineralogy. This has positive implications for future operational mapping using AVIRIS or similar imaging spectrometer data sets without requiring a priori knowledge.

Kruse, Fred A.↗
NASA NTRS1993

Determination of semi-arid landscape endmembers and seasonal trends using convex geometry spectral unmixing techniques

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired during three consecutive growing seasons (26 September 1989, 22 March 1990, and 7 August 1990) over an area of the High Plains east of Greeley, Colorado (40 deg 20 min N and 104 deg 16 min W). A repeat visit to assess vegetation at its peak growth was flown on 6 June 1993. 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 and morphological relationships that contribute to the evolution of this landscape are nearly impossible to understand without the use of remote sensing. Additionally, this area and regions similarly situated could be the first to experience the effects caused by global climate change. During the past 10,000 years there were at least four periods of extensive sand activity due to climate change, followed by periods of landscape stability, as shown in the stratigraphic record of this area.

Yuhas, Roberta H.↗
NASA NTRS1993

Geologic mapping using integrated AIRSAR, AVIRIS, and TIMS data

The multi-sensor aircraft campaign called the 'Geologic Remote Sensing Field Experiment' (GRSFE), conducted during 1989 in the southwestern United States, collected multiple airborne remote sensing data sets and associated field and laboratory measurements. The GRSFE airborne data sets used in this study include the airborne Synthetic Aperture Radar (AIRSAR), the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and the Thermal Infrared Multispectral Scanner (TIMS). Each sensor's unique characteristics were used for this study in a combined analysis scheme for geologic mapping. AIRSAR was used to map structures and landforms, AVIRIS was used to map mineralogy, and TIMS was used to map lithology. Visual data integration using IHS transforms and combined numerical analysis using derived geophysical and geologic parameters with 'multispectral' techniques resulted in improved geologic mapping over that possible using each data set individually.

Kruse, Fred A.↗
NASA NTRS1993

MAC Europe 1991 campaign: AIRSAR/AVIRIS data integration for agricultural test site classification

During summer 1991, multi-sensor data were acquired over the Italian test site 'Otrepo Pavese', an agricultural flat area in Northern Italy. This area has been the Telespazio pilot test site for experimental activities related to agriculture applications. The aim of the investigation described in the following paper is to assess the amount of information contained in the AIRSAR (Airborne Synthetic Aperture Radar) and AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data, and to evaluate classification results obtained from each sensor data separately and from the combined dataset. All classifications are examined by means of the resulting confusion matrices and Khat coefficients. Improvements of the classification results obtained by using the integrated dataset are finally evaluated.

Sangiovanni, S.↗
NASA NTRS1995

High spectral resolution remote sensing of canopy chemistry

Near infrared laboratory spectra have been used for many years to determine nitrogen and lignin concentrations in plant materials. In recent years, similar high spectral resolution visible and infrared data have been available via airborne remote sensing instruments. Using data from NASA's Airborne visible/Infrared Imaging Spectrometer (AVIRIS) we attempt to identify spectral regions correlated with foliar chemistry at the canopy level in temperate forests.

Aber, John D.↗
NASA NTRS1995

Mineralogic variations in fluvial sediments contaminated by mine tailings as determined from AVIRIS data, Coeur D'Alene River Valley, Idaho

The success of imaging spectrometry in mineralogic mapping of natural terrains indicates that the technology can also be used to assess the environmental impact of human activities in certain instances. Specifically, this paper describes an investigation into the use of data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) for mapping the spread of, and assessing changes in, the mineralogic character of tailings from a major silver and base metal mining district. The area under investigation is the Coeur d'Alene River Valley in northern Idaho. Mining has been going on in and around the towns of Kellogg and Wallace, Idaho since the 1880's. In the Kellogg-Smelterville Flats area, west of Kellogg, mine tailings were piled alongside the South Fork of the Coeur d'Alene River. Until the construction of tailings ponds in 1968 much of these waste materials were washed directly into the South Fork. The Kellogg-Smelterville area was declared an Environmental Protection Agency (EPA) Superfund site in 1983 and remediation efforts are currently underway. Recent studies have demonstrated that sediments in the Coeur d'Alene River and in the northern part of Lake Coeur d'Alene, into which the river flows, are highly enriched in Ag, Cu, Pb, Zn, Cd, Hg, As, and Sb. These trace metals have become aggregated in iron oxide and oxyhydroxide minerals and/or mineraloids. Reflectance spectra of iron-rich tailing materials are shown. Also shown are spectra of hematite and goethite. The broad bandwidth and long band center (near 1 micron) of the Fe(3+) crystal-field band of the iron-rich sediment samples combined with the lack of features on the Fe(3+) -O(2-) charge transfer absorption edge indicates that the ferric oxide and/or oxyhydroxide in these sediments is poorly crystalline to amorphous in character. Similar features are seen in poorly crystalline basaltic weathering products (e.g., palagonites). The problem of mapping and analyzing the downriver occurrences of iron rich tailings in the Coeur d'Alene (CDA) River Valley using remotely sensed data is complicated by the full vegetation cover present in the area. Because exposures of rock and soil were sparse, the data processing techniques used in this study were sensitive to detecting materials at subpixel scales. The methods used included spectral mixture analysis and a constrained energy minimization technique.

Farrand, W. H.↗
NASA NTRS1995

Determination of the in-flight spectral calibration of AVIRIS using atmospheric absorption features

Spectral calibration of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) as data are acquired in flight is essential to quantitative analysis of the measured upwelling spectral radiance. In each spectrum measured by AVIRIS in flight, there are numerous atmospheric gas absorption bands that drive this requirement for accurate spectral calibration. If the surface and atmospheric properties are measured independently, these atmospheric absorption bands may be used to deduce the in-flight spectral calibration of an imaging spectrometer. Both the surface and atmospheric characteristics were measured for a calibration target during an in-flight calibration experiment held at Lunar Lake, Nevada on April 5, 1994. This paper uses upwelling spectral radiance predicted for the calibration target with the MODTRAN radiative transfer code to validate the spectral calibration of AVIRIS in flight.

Green, Robert O.↗
NASA NTRS1995

An improved spectral calibration requirement for AVIRIS

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures spectra from 400 to 2500 nm through 224 contiguous spectral channels. These spectra are used to identify and determine the abundances of constituents of the earth's surface and atmosphere through the analysis of spectral molecular absorptions and scattering properties of materials. Spectral calibration of the AVIRIS is required to pursue these determinations, which are based on these fundamental spectral characteristics. The spectral calibration of AVIRIS consists of a description of the spectral response function for each of the 224 spectral channels. The spectral response function of AVIRIS channels was measured in the laboratory and shown to be Gaussian in shape. A subset of nine AVIRIS spectral channels is shown with channel centers at 10 nm intervals and channel shapes of Gaussian form with 10 nm full width and half maximum (FWHM). For AVIRIS the spectral calibration is described by the spectral center and FWHM of a Gaussian function for each channel. Uncertainty in the determination of the spectral center and FWHM for each channel are also reported. This paper presents results from an investigation of the sensitivity of AVIRIS-measured upwelling radiance to errors in spectral calibration. Based on this sensitivity analysis in conjunction with earlier work, an improved spectral calibration requirement for AVIRIS is proposed.

Green, Robert O.↗
NASA NTRS1995

Measurement of atmospheric water vapor, leaf liquid water and reflectance with AVIRIS in the Boreal Ecosystem-Atmosphere Study: Initial results

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) acquired data as part of the Boreal Ecosystem-Atmosphere Study (BOREAS) in 1994. Flights occurred over the northern study area (NSA) in the region of 56 degrees north latitude and 98.5 degrees west longitude and over the southern study area (SSA) at 54 degrees north latitude and 105 degrees west longitude. These data will be used to directly derive spectral properties of the surface and atmosphere and to provide supporting data for other instruments, models, and experiments in support of the BOREAS objectives. We present a preliminary evaluation of the AVIRIS data collected in BOREAS in terms of the AVIRIS-derived parameters: water vapor, leaf water, and apparent spectral reflectance.

Green, Robert O.↗
NASA NTRS1995

AVIRIS user's guide

This paper serves as a brief overview of the AVIRIS instrument (Airborne Visible/Infrared Imaging Spectrometer). The AVIRIS sensor collects data that will be used for quantitative characterization of the Earth's surface and atmosphere from geometrically coherent spectroradiometric measurements. This data can be applied to studies in the fields of oceanography, environmental science, snow hydrology, geology, volcanology, soil and land management, atmospheric and aerosol studies, agriculture, and limnology. Applications under development include the assessment and monitoring of environmental hazards such as toxic waste, oil spills, and land/air/water pollution. Mission planning and flight operations are discussed, and recommendations are given regarding the deployment of ground truth experiments.

Johnson, Howell K.↗
NASA NTRS1994

Effect of radiance-to-reflectance transformation and atmosphere removal on maximum likelihood classification accuracy of high-dimensional remote sensing data

Many analysis algorithms for high-dimensional remote sensing data require that the remotely sensed radiance spectra be transformed to approximate reflectance to allow comparison with a library of laboratory reflectance spectra. In maximum likelihood classification, however, the remotely sensed spectra are compared to training samples, thus a transformation to reflectance may or may not be helpful. The effect of several radiance-to-reflectance transformations on maximum likelihood classification accuracy is investigated in this paper. We show that the empirical line approach, LOWTRAN7, flat-field correction, single spectrum method, and internal average reflectance are all non-singular affine transformations, and that non-singular affine transformations have no effect on discriminant analysis feature extraction and maximum likelihood classification accuracy. (An affine transformation is a linear transformation with an optional offset.) Since the Atmosphere Removal Program (ATREM) and the log residue method are not affine transformations, experiments with Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were conducted to determine the effect of these transformations on maximum likelihood classification accuracy. The average classification accuracy of the data transformed by ATREM and the log residue method was slightly less than the accuracy of the original radiance data. Since the radiance-to-reflectance transformations allow direct comparison of remotely sensed spectra with laboratory reflectance spectra, they can be quite useful in labeling the training samples required by maximum likelihood classification, but these transformations have only a slight effect or no effect at all on discriminant analysis and maximum likelihood classification accuracy.

Hoffbeck, Joseph P.↗
NASA NTRS1996

Mapping Volcanic Gas Emissions in the Mammoth Mountain Area Using AVIRIS

The Long Valley Caldera located in the eastern Sierra Nevada (California) shows new signs of volcanic activity. This renewed activity is expressed by gas emissions, hydrothermal activity and frequent earthquakes. Analysis of the gas composition regarding the percentage biogenic carbon and the He-3/He-4 ratio revealed that the gas source is the magma body approximately 7 km beneath the Long Valley Caldera. The gas from the magma body surfaces not only via the fumaroles but also emerges along geological faults. Some of the spots where gas surfaces are marked by dead or stressed trees. Other spots may not yet be identified. It is only recently known, from research at 'Vulcano Island' in southern Italy, that volcanoes release abundant carbon dioxide from their flanks as diffuse soil emanations. Mammoth Mountain seems to behave in a similar manner. The research described in this paper is designed to determine whether AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) can be used to identify areas of volcanic gas emissions.

deJong, Steven M.↗
NASA NTRS1996

Subpixel Snow-Covered-Area and Snow Grain Size From Mixture Analysis with AVIRIS Data

Snow-covered-area (SCA) and snow grain size are crucial inputs to hydrologic and climatologic modeling of alpine and other seasonally snow-covered regions. SCA is necessary to parameterize energy budget calculations in climate models, to determine in which regions point snowmelt models are to be run for distributed snowmelt modeling efforts and to provide a basis from which estimates of snow water equivalent (SWE) may be made. Snow grain size, SWE and snow impurities determine the spectral albedo of snow, which controls the net solar flux at the snowpack surface. Snow albedo is of the utmost importance in snowmelt modeling, yet the difficulty with which grain size, SWE, and impurities are mapped has left the spatial distribution of snow albedo in alpine catchments poorly understood. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been used to estimate sub-pixel snow-covered-area and snow grain size independently. In this paper we present a technique which improves estimates of both snow parameters by treating their mapping simultaneously.

Green Robert O.↗
NASA NTRS1996

Mapping Chaparral in the Santa Monica Mountains Using Multiple Spectral Mixture Models

California chaparral is one of the most important natural vegetation communities in Southern California, representing a significant source of species diversity and, through a high susceptibility to fire, playing a major role in ecosystem dynamics. Due to steep topographic gradients, harsh edaphic conditions and variable fire histories, chaparral typically forms a complex mosaic of different species dominants and age classes, each with unique successional responses to fire and canopy characteristics (e.g. moisture content, biomass, fuel load) that modify fire susceptibility. The high human cost of fire and intimate mixing along the urban interface combine to modify the natural fire regime as well as provide additional impetus for a better understanding of how to predict fire and its management. Management problems have been further magnified by nearly seventy years of fire suppression and drought related die-back over the last few years resulting in a large accumulation of highly combustible fuels. Chaparral communities in the Santa Monica Mountains exemplify many of the management challenges associated with fire and biodiversity. A study was initiated in the Santa Monica Mountains to investigate the use of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) for providing improved maps of chaparral coupled with direct estimates of canopy attributes (e.g. biomass, leaf area, fuel load). The Santa Monica Mountains are an east-west trending range located approximately 75 kilometers north of Los Angeles extending westward into Ventura County. Within the Santa Monica Mountains a diverse number of ecosystems are located, including four distinct types of chaparral, wetlands, riparian habitats, woodlands, and coastal sage scrub. In this study we focus on mapping three types of chaparral, oak woodlands and grasslands. Chaparral mapped included coastal sage scrub, chamise chaparral and mixed chaparral that consisted predominantly of two species of Ceanothus.

Green Robert O.↗