Results for “Airborne Imaging Spectrometer” — Page 17

NASA NTRS2001

AVIRIS Inflight Calibration Experiments, Analysis, and Results in 2000

The NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures spectra from 370 to 2500 nm with nominally 10-nm sampling and resolution. The spectra are acquired as images with an 11 km width and up to 800 km length from the ER-2 platform or 2.1 km width and 160 km length from the Twin Otter platform. AVIRIS measurements are used for a range of Earth science research and application objectives. The molecular absorption and particle scattering properties expressed in the calibrated AVIRIS measurements are used. For both science research and application objectives, calibration of the AVIRIS spectra is required to produce useful results. Each year prior to the flight season AVIRIS is calibrated in the laboratory. However, the temperature, pressure, vibration, and observational geometry, as well as mechanical, electrical, and operational interfaces of the laboratory are different than the environment on board the airborne platform. To validate the calibration of AVIRIS in the flight environment, an inflight calibration experiment is orchestrated at the beginning of each flight season. In most years additional inflight calibration experiments occur towards the middle and end of the flight season as well. For an inflight calibration experiment, AVIRIS acquires airborne data over a designated calibration target. In concert with the airborne data acquisition, surface and atmospheric properties at the calibration target are measured in situ. These in situ measurements are used to constrain a radiative transfer code and predict the radiance incident at the AVIRIS instrument from the calibration target. This prediction is compared with the AVIRIS-measured radiance to validate the calibration of AVIRIS in the flight environment. Additional properties (such as the AVIRIS inflight measurement precision) are determined as well. This paper presents measurements, analyses, and results from the inflight calibration experiment held on the dry lake bed surface of Rogers Dry Lake, California, on June 5, 2000.

Green, Robert O.↗

NASA NTRS2002

Low Altitude AVIRIS Data for Mapping Land Form Types on West Ship Island, Mississippi

Barrier islands help protect the southern and southeastern U.S. shoreline from hurricanes and severe storms. They are important for coastal resource management and geologic research, especially in studies that involve changes in island areas and surface environments, and they display a dynamically changing and diverse mix of landform and vegetative cover habitats. Many Gulf Coast barrier islands have undergone dramatic decreases in areal extent, often due to hurricane and severe storm damage. For example, Louisiana's barrier islands have lost 55 percent of their surface area over the past 100 years. Aerial photography and Landsat data have been used to monitor changes in barrier island areal extent, although neither data source is optimal for making maps of detailed landform types at site-specific scales. High spatial resolution hyperspectral imagery, such as that obtained from the high spatial resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor, may enable improved mapping of landform types, which would benefit studies of the dynamics of barrier island environments. During the summers of 2000 and 2001, a study was conducted to assess low-altitude AVIRIS data for mapping the landform types of West Ship Island, a barrier island in Harrison County, Mississippi. This study area was selected because of the availability of low-altitude AVIRIS data acquired on July 22, 1999, and because of the area's accessibility to the investigating team. West Ship Island is one of the six barrier islands that belong to the Gulf Shores National Seashore, which is managed by the National Park Service. This island contains an impressive range of landform categories. Surface types include beach, dune, and sand flat environments. West Ship Island also harbors Fort Massachusetts, a historic fort used during the Civil War. Because it is located near Stennis Space Center, the island is frequently imaged by NASA's airborne and spaceborne sensors.

Spruce, Joseph P.↗

NASA NTRS1993

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.↗

NASA NTRS2021

Cutting out the Middleman: Calibrating and Validating a Dynamic Vegetation Model (ED2-PROSPECT5) Using Remotely Sensed Surface Reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types. Using a single common set of parameters across all sites, the calibrated model was able to accurately reproduce surface reflectance for sites with highly varied forest composition and structure. However, the calibrated model's predictions of leaf area index (LAI) were less robust, capturing only 46 % of the variability in the observations. Comparing the ED2 radiative transfer model with another two-stream soil–leaf–canopy radiative transfer model commonly used in remote sensing studies (PRO4SAIL) illustrated structural errors in the ED2 representation of direct radiation backscatter that resulted in systematic underestimation of reflectance. In addition, we also highlight that, to directly compare with a two-stream radiative transfer model like EDR, we had to perform an additional processing step to convert the directional reflectance estimates of AVIRIS to hemispherical reflectance (also known as “albedo”). In future work, we recommend that vegetation models add the capability to predict directional reflectance, to allow them to more directly assimilate a wide range of airborne and satellite reflectance products. We ultimately conclude that despite these challenges, using dynamic vegetation models to predict surface reflectance is a promising avenue for model calibration and validation using remote sensing data.

Alexey N Shiklomanov↗

DOE OSTI2021

Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

AVIRIS foreoptics, fiber optics and on-board calibrator

The foreoptics, fiber optic system and calibration source of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) are described. The foreoptics, based on a modified Kennedy scanner, is coupled by optical fibers to the four spectrometers. The optical fibers allow convenient positioning of the spectrometers in the limited space and enable simple compensation of the scanner's thermal defocus (at the -23 C operating temp) by active control of the fiber focal plane position. A challenging requirement for the fiber optic system was the transmission to the spectral range 1.85 to 2.45 microns at .45 numerical aperture. This was solved with custom fluoride glass fibers from Verre Fluore. The onboard calibration source is also coupled to the spectrometers by the fibers and provides two radiometric levels and a reference spectrum to check the spectrometers' alignment. Results of the performance of the assembled subsystems are presented.

Chrisp, Michael P.↗

NASA NTRS1987

AVIRIS scan drive design and performance

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) images the ground with an instantaneous field of view (IFOV) of 1 mrad. The IFOV is scanned 30 deg from left to right to provide the cross-track dimension of the image, while the aircraft's motion provides the along-track dimension. The scanning frequency is 12 Hz, with a scan efficiency of 70 percent. The scan mirror has an effective diameter of 5.7 in, and its positional accuracy is a small fraction of a milliradian of the nominal position-time profile. Described are the design and performance of the scan drive mechanism. Tradeoffs among various approaches are discussed, and the reasons given for the selection of the cam drive.

Miller, D. C.↗

NASA NTRS1987

AVIRIS onboard data handling and control

The timing and flow of detector and ancillary data for the Airborne Visible/Infrared imaging spectrometer (AVIRIS) are controlled within the instrument by its digital electronics assembly. In addition to providing detector and signal chain timing, the digital electronics receives, formats, and rate-buffers digitized science data; collects and formats ancillary (calibration and engineering) data; and merges both into a single tape record. Overall AVIRIS data handling is effected by a combination of dedicated digital electronics to control instrument timing, image data flow, and data rate buffering and a microcomputer programmed to handle real-time control of instrument mechanisms and the coordinated preparation of ancillary data.

Steinkraus, Ronald E.↗

NASA NTRS1987

AVIRIS ground data-processing system

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been under development at JPL for the past four years. During this time, a dedicated ground data-processing system has been designed and implemented to store and process the large amounts of data expected. This paper reviews the objectives of this ground data-processing system and describes the hardware. An outline of the data flow through the system is given, and the software and incorporated algorithms developed specifically for the systematic processing of AVIRIS data are described.

Reimer, John H.↗

NASA NTRS1988

Estimating the signal-to-noise ratio of AVIRIS data

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.

Curran, Paul J.↗

NASA NTRS1988

Zones of information in the AVIRIS spectra

To make the best use of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data an investigator needs to know the ratio of signal to random variability or noise (S/N ratio). The signal is land-cover dependent and decreases with both wavelength and atmospheric absorption and random noise comprises sensor noise and intra-pixel variability. The three existing methods for estimating the S/N ratio are inadequate as typical laboratory methods inflate, while dark current and image methods deflate the S/N ratio. We propose a new procedure 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 intra-pixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season.

Curran, Paul J.↗

NASA NTRS1988

Calibration and evaluation of AVIRIS data: Cripple Creek in October 1987

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were obtained over Cripple Creek and Canon City Colorado on October 19, 1987 at local noon. Multiple ground calibration sites were measured within both areas with a field spectrometer and samples were returned to the laboratory for more detailed spectral characterization. The data were used to calibrate the AVIRIS data to ground reflectance. Once calibrated, selected spectra in the image were extracted and examined, and the signal to noise performance was computed. Images of band depth selected to be diagnostic of the presence of certain minerals and vegetation were computed. The AVIRIS data were extremely noisy, but images showing the presence of goethite, kaolinite and lodgepole pine trees agree with ground checks of the area.

Clark, Roger N.↗

NASA NTRS1988

Assessment of AVIRIS data from vegetated sites in the Owens Valley, California

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired from the Bishop, CA area, located at the northern end of the Owens Valley, on July 30, 1987. Radiometrically-corrected AVIRIS data were flat-field corrected, and spectral curves produced and analyzed for pixels taken from both native and cultivated vegetation sites, using the JPS SPAM software program and PC-based spreadsheet programs. Analyses focussed on the chlorophyll well and red edge portions of the spectral curves. Results include the following: AVIRIS spectral data are acquired at sufficient spectral resolution to allow detection of blue shifts of both the chlorophyll well and red edge in moisture-stressed vegetation when compared with non-stressed vegetation; a normalization of selected parameters (chlorophyll well and near infrared shoulder) may be used to emphasize the shift in red edge position; and the presence of the red edge in AVIRIS spectral curves may be useful in detecting small amounts (20 to 30 pct cover) of semi-arid and arid vegetation ground cover. A discussion of possible causes of AVIRIS red edge shifts in respsonse to stress is presented.

Rock, B. N.↗

NASA NTRS1988

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.↗

NASA NTRS1988

AVIRIS foreoptics, fiber optics and on-board calibrator

The foreoptics, fiber optic system and calibration source of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) are described. The foreoptics, based on a modified Kennedy scanner, is coupled by optical fibers to the four spectrometers. The optical fibers allow convenient positioning of the spectrometers in the limited space and enable simple compensation of the scanner's thermal defocus (at the -23 C operating temp) by active control of the fiber focal plane position. A challenging requirement for the fiber optic system was the transmission to the spectral range 1.85 to 2.45 microns at .45 numerical aperture. This was solved with custom fluoride glass fibers from Verre Fluore. The onboard calibration source is also coupled to the spectrometers by the fibers and provides two radiometric levels and a reference spectrum to check the spectrometers' alignment. Results of the performance of the assembled subsystems are presented.

Chrisp, M. P.↗

NASA NTRS1988

AVIRIS scan drive design and performance

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) images the ground with an instantaneous field of view (IFOV) of 1 mrad. The IFOV is scanned 30 deg from left to right to provide the cross-track dimension of the image, while the aircraft's motion provides the along-track dimension. The scanning frequency is 12 Hz, with a scan efficiency of 70 percent. The scan mirror has an effective diameter of 5.7 in, and its positional accuracy is a small fraction of a milliradian of the nominal position-time profile. Described are the design and performance of the scan drive mechanism. Tradeoffs among various approaches are discussed, and the reasons given for the selection of the cam drive.

Miller, D. C.↗

NASA NTRS1988

AVIRIS onboard data handling and control

The timing and flow of detector and ancillary data for the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) are controlled within the instrument by its digital electronics assembly. In addition to providing detector and signal chain timing, the digital electronics receives, formats, and rate-buffers digitized science data; collects and formats ancillary (calibration and engineering) data; and merges both into a single tape record. Overall AVIRIS data handling is effected by a combination of dedicated digital electronics to control instrument timing, image data flow, and data rate buffering and a microcomputer programmed to handle real-time control of instrument mechanisms and the coordinated preparation of ancillary data.

Steinkraus, Ronald E.↗

NASA NTRS1988

AVIRIS ground data-processing system

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been under development at JPL for the past four years. During this time, a dedicated ground data-processing system has been designed and implemented to store and process the large amounts of data expected. This paper reviews the objectives of this ground data-processing system and describes the hardware. An outline of the data flow through the system is given, and the software and incorporated algorithms developed specifically for the systematic processing of AVIRIS data are described.

Reimer, John H.↗