Imaging Spectrometry: A Strategy to Move From 'Remote Sensing' to 'Remote Measurement' for
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Publications and source records attributed to Green, Robert O..
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This publication is the first of three containing summaries for the Fifth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 23-26, 1995. The main workshop is divided into three smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on January 23-24. The summaries for this workshop appear in this volume; (2) The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on January 25-26. The summaries for this workshop appear in Volume 3; and (3) The Thermal Infrared Multispectral Scanner (TIMS) workshop, on January 26. The summaries for this workshop appear in Volume 2.
A complete spectral unmixing of a complicated AVIRIS scene may not always be possible or even desired. High quality data of spectrally complex areas are very high dimensional and are consequently difficult to fully unravel. Partial unmixing provides a method of solving only that fraction of the data inversion problem that directly relates to the specific goals of the investigation. Many applications of imaging spectrometry can be cast in the form of the following question: 'Are my target signatures present in the scene, and if so, how much of each target material is present in each pixel?' This is a partial unmixing problem. The number of unmixing endmembers is one greater than the number of spectrally defined target materials. The one additional endmember can be thought of as the composite of all the other scene materials, or 'everything else'. Several workers have proposed partial unmixing schemes for imaging spectrometry data, but each has significant limitations for operational application. The low probability detection methods described by Farrand and Harsanyi and the foreground-background method of Smith et al are both examples of such partial unmixing strategies. The new method presented here builds on these innovative analysis concepts, combining their different positive attributes while attempting to circumvent their limitations. This new method partially unmixes AVIRIS data, mapping apparent target abundances, in the presence of an arbitrary and unknown spectrally mixed background. It permits the target materials to be present in abundances that drive significant portions of the scene covariance. Furthermore it does not require a priori knowledge of the background material spectral signatures. The challenge is to find the proper projection of the data that hides the background variance while simultaneously maximizing the variance amongst the targets.
The AVIRIS instrument uses an onboard calibration system to provide auxiliary calibration data. The system consist of a tungsten halogen cycle lamp imaged onto a fiber bundle through an eight position filter wheel. The fiber bundle illuminates the back side of the foreoptics shutter during a pre-run and post-run calibration sequence. The filter wheel contains two neutral density filters, five spectral filters and one blocked position. This paper reviews the general workings of the onboard calibrator system and discusses recent modifications.
Recent laboratory calibrations of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) include new methods for the characterization of the geometric, spectral, temporal and radiometric properties of the sensor. New techniques are desired in order to: (1) increase measurement accuracy and precision, (2) minimize measurement time and expense, (3) prototype new field and inflight calibration systems, (4) resolve measurement ambiguities, and (5) add new measurement dimensions. One of the common features of these new methods is the use of the full data collection and processing power of the AVIRIS instrument and data facility. This allows the collection of large amounts of calibration data in a short period of time and is well suited to modular data analysis routines.
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. Depending on the amount of support data, this can be a formidable task. This paper examines four methods of calibration: (1) a radiative transfer model from the University of Colorado (ATREM: Gao and Goetz, 1990; Gao et al., 1992), (2) a MODTRAN-based method developed at the Jet Propulsion Lab by Green et al., (1191), (3) a ground calibration using known sites as standards, and (4) a combined approach using radiative transfer methods and ground calibration. Data from the Airborne Visual and Infra-Red Imaging Spectrometer (AVIRIS) instrument were evaluated from data sets obtained over multiple years and multiple sites.
In this paper, we evaluate the potential for extracting the 'photochemical reflectance index' (PRI; previously called the 'physiological reflectance index') from AVIRIS data. This index, which is derived from narrow-band reflectance at 531 and 570 nm, has proven to be a useful indicator of photosynthetic function at the leaf and canopy scales. At the leaf level, PRI varies with photosynthetic capacity, radiation-use efficiency, and vegetation type (unpublished data). This finding is consistent with the hypothesis that vegetation types exhibiting chronically reduced photosynthesis during periods of stress (e.g. drought-tolerant evergreens) invest proportionally more in photoprotective processes than vegetation with high photosynthetic capacity (e.g. crops or deciduous perennials). Vertical transects in tropical and boreal forest canopies have indicated declines in PRI associated with downregulation of photosynthesis at the canopy tops under sunny, dry midday conditions (unpublished data). This reduced PRI in upper canopy levels provides a further basis for examining this signal with the 'view from above' afforded by aircraft overflights. Although many factors could confound interpretation of a subtle physiological signal at the landscape scale, we conducted a preliminary examination of PRI extracted from existing, AVIRIS imagery of Stanford University's Jasper Ridge Biological Preserve obtained on the June 2nd, 1992, overflight. The goal was to use the hyperspectral capabilities of AVIRIS to evaluate the potential of this index for obtaining useful physiological data at the landscape scale. The expectation based on leaf- and canopy-level studies was that regions containing vegetation of reduced photosynthetic capacity (e.g. chaparral or evergreen woodland) would exhibit lower PRI values than regions of high capacity (e.g. deciduous woodland).
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.
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.
Movement of water as vapor in the atmosphere is a fundamental process in the Earth's hydrological cycle. Investigations of spatial and time scales of water vapor transport in the atmosphere are important areas of research. Water vapor transmits energy as a function of its abundance across the spectrum. This is shown in the 400- to 2500-nm spectral region where the transmission of the terrestrial atmosphere has been modeled using the MODTRAN radiative transfer code for a range of water vapor abundances. Based on these model results, spectra measured by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) have been used to investigate the movement of water vapor at 20-m spatial resolution over an 11-by-30-km area at approximately 15-minute time intervals (1.25 hours total). AVIRIS measures the upwelling spectral radiance from 400 to 2500 nm at 10-nm spectral intervals and collects images of 11-by-up-to-1000 km at 20-m spatial resolution. Data are collected at a rate of 1 km of flight line per 4.5 seconds. A set of five AVIRIS flight lines was acquired in rapid succession over Rogers Dry Lake, CA on May 18, 1993 at 18:59, 19:13, 19:29, 19:47, and 19:59 UTC. Rogers Dry lake is located 2 hours north of Los Angeles, CA at 34.84 degrees north latitude and 117.83 degrees west longitude in the Mojave Desert.
The AVIRIS sensor must be calibrated at the time it measures spectra from the ER-2 airborne platform in order to achieve research and application objectives that are both quantitative and physically based. However, the operational environment inside the Q-bay of the ER-2 at 20 km altitude differs from that in the AVIRIS laboratory with respect to temperature, pressure, vibration, and high-frequency electromagnetic fields. Experiments at surface calibration targets are used in each flight season to confirm the accuracy of AVIRIS in-flight radiometric calibrations. For these experiments, the MODTRAN radiative transfer code is constrained by using in situ measurements to independently predict the upwelling spectral radiance arriving at AVIRIS for a specific calibration target. AVIRIS calibration is validated in flight by comparing the MODTRAN-predicted radiance to the laboratory-calibrated radiance measured by the AVIRIS sensor for the same time over the calibration target. We present radiometric calibration results for the AVIRIS in-flight calibration experiment held at the beginning of the 1994 flight season.
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.
Melting of the snowpack is a critical parameter that drives aspects of the hydrology in regions of the earth where snow accumulates seasonally. New techniques for measurement of snow melt over regional scales offer the potential to improve monitoring and modeling of snow-driven hydrological processes. We present the results of measuring the spectral absorption of liquid water in a melting snowpack with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data were acquired over Mammoth Mountain, in east central California on 21 May 1994 at 18:35 UTC. The air temperature at 2926 m on Mammoth Mountain at site A was measured at 15-minute intervals during the day preceding the AVIRIS data acquisition. At this elevation, the air temperature did not drop below freezing the night of May 20 and had risen to 6 degrees Celsius by the time of the overflight on May 21. These temperature conditions support the presence of melting snow at the surface as the AVIRIS data were acquired.
Plant species composition and plant architectural attributes are critical parameters required for the measuring, monitoring, and modeling of terrestrial ecosystems. Remote sensing is commonly cited as an important tool for deriving vegetation properties at an appropriate scale for ecosystem studies, ranging from local to regional and even synoptic scales. Classical approaches rely on vegetation indices such as the normalized difference vegetation index (NDVI) to estimate biophysical parameters such as leaf area index or intercepted photosynthetically active radiation (IPAR). Another approach is to apply a variety of classification schemes to map vegetation and thus extrapolate fine-scale information about specific sites to larger areas of similar composition. Imaging spectrometry provides additional information that is not obtainable through broad-band sensors and that may provide improved inputs both to direct biophysical estimates as well as classification schemes. Some of this capability has been demonstrated through improved discrimination of vegetation, estimates of canopy biochemistry, and liquid water estimates from vegetation. We investigate further the potential of leaf water absorption estimated from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data as a means for discriminating vegetation types and deriving canopy architectural information. We expand our analysis to incorporate liquid water estimates from two spectral regions, the 1000-nm region and the 2200-nm region. The study was conducted in the vicinity of Jasper Ridge, California, which is located on the San Francisco peninsula to the west of the Stanford University campus. AVIRIS data were acquired over Jasper Ridge, CA, on June 2, 1992, at 19:31 UTC. Spectra from three sites in this image were analyzed. These data are from an area of healthy grass, oak woodland, and redwood forest, respectively. For these analyses, the AVIRIS-measured upwelling radiance spectra for the entire Jasper Ridge scene were transformed to apparent surface reflectance using a radiative transfer code-based inversion algorithm.
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.
Surface albedo and snow-covered-area (SCA) are crucial inputs to the hydrologic and climatologic modeling of alpine and seasonally snow-covered areas. Because the spectral albedo and thermal regime of pure snow depend on grain size, areal distribution of snow grain size is required. Remote sensing has been shown to be an effective (and necessary) means of deriving maps of grain size distribution and snow-covered-area. Developed here is a technique whereby maps of grain size distribution improve estimates of SCA from spectral mixture analysis with AVIRIS data.
Water vapor in the atmosphere has been derived from the AVIRIS spectra measured in five overpasses acquired above Rogers Dry Lake, California. The abundance of water vapor in these data is shown to be spatially heterogeneous at the 25 percent level over a range of spatial scales.
Both the surface and atmospheric characteistics were measured for a calibration target during an inflight calibration experiment held at Lunar Lake, Nevada on April 5, 1994 (Green, et al., 1995). This paper uses upwelling spectral radiance predicted for the calibration target with the MODTRAN radiative transfer code (Berk, et al., 1986) to validage the spectral calibration of AVIRIS inflight.