Data Facility of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)
This paper describes recent improvements in the AVIRIS data facility.
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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In-Flight Calibration and Validation of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)
To validate AVIRIS in flight, and in-flight calibration experiment was performed for an over-flight on May 9, 1995, at Ivanpah Playa, California, USA. In-situ measurements were used to constrain a radiative transfer code and predict the total upwelling spectral radiance incident at AVIRIS.
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Multifrequency remote sensing of soil moisture
Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using NASA's C-130 aircraft were used to determine which of the all-weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture.
Theis, S. W.↗
Microwave remote sensing of soil moisture, volume 1
Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.
Mcfarland, M. J.↗
Spaceborne SAR sensor architecture
Spaceborne imaging radars for the decade of the '90s will be called upon to provide increased illumination parameter flexibility, polar orbital coverage, and to operate from the same platform with other advanced sensors such as multilinear arrays. The potential information content in accurately merged microwave infrared, or microwave visible images is enormous by comparison to either radar images alone or visible/infrared images alone, since microwave images are principally responsive to surface geometry whereas visible/infrared images are highly sensitive to surface chemistry. A strawman system concept in which a SAR and multilinear array (MLA) are flown on a polar orbiting free flyer at 800 km altitude is discussed. Data would be relayed to ground via the TDRSS (or equivalent).
Carver, K. R.↗
Detection of lowland flooding using active microwave systems
The development of radar systems with longer wavelenths (greater than 3 cm) has provided new possibilities regarding the utilization of radar. Thus, it has been found that the interpretation of data from radar images can be a valuable classification aid for applications related to water resources. In the case of an interpreter accustomed to photographic or visible/infrared images, an evaluation of radar images presents some problems, because the radar is sensing a set of surface characteristics which have little influence on visible/infrared systems. Detectable features in radar images caused by differences in dielectric properties are usually associated with the water content of either soils or vegetation. The present paper is concerned with studies which were initiated in 1976. The studies had the objective to define the magnitude of the effects on radar data caused by flood waters under vegetation. The obtained results indicate the feasibility to detect flood conditions beneath a forest canopy, and to obtain an improved definition of the land-water boundary.
Ormsby, J. P.↗
Imaging spectroscopy II; Proceedings of the Meeting, San Diego, CA, Aug. 20, 21, 1987
The conference presents papers on airborne imaging spectrometers, imaging spectrometry analysis, and spaceborne imaging spectrometers. Consideration is given to an imaging spectrometer for ocean and land remote sensing, an advanced solid-state array spectroradiometer, airborne visible/infrared imaging spectrometer design and performance, and a signal chain for the airborne visible/infrared imaging spectrometer. Other topics include imaging spectrometry as a tool for botanical mapping, the estimation of forest canopy characteristics and nitrogen cycling using lasing spectrometry, and a continuous readout photon counting imaging detector.
Vane, Gregg↗
VIIRS ZEMAX and FORTRAN Polarization Models
The Visible/Infrared Imager/Radiometer Suite (VIIRS) collects visible/infrared imagery and radiometric data. The radiometric requirements are such that the instrument's polarization sensitivity must be very well understood. This paper presents the ZEMAX and FORTRAN polarization ray trace models of the instrument's visible light path. This will include the measured optical surface reflectance data, the bandpass shapes and a comparison of the results of the two models.
Waluschka, Eugene↗
Imaging spectroscopy algorithms for mapping canopy foliar chemical and morphological traits and their uncertainties
A major goal of remote sensing is the development of generalizable algorithms to repeatedly and accurately map ecosystem properties across space and time. Imaging spectroscopy has great potential to map vegetation traits that cannot be retrieved from broadband spectral data, but rarely have such methods been tested across broad regions. Here we illustrate a general approach for estimating key foliar chemical and morphological traits through space and time using NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-Classic). We apply partial least squares regression (PLSR) to data from 237 field plots within 51 images acquired between 2008 and 2011. Using a series of 500 randomized 50/50 subsets of the original data, we generated spatially explicit maps of seven traits (leaf mass per area (M area ), percentage nitrogen, carbon, fiber, lignin, and cellulose, and isotopic nitrogen concentration, δ 15 N) as well as pixel-wise uncertainties in their estimates based on error propagation in the analytical methods. Both Marea and %N PLSR models had a R 2 > 0.85. Root mean square errors (RMSEs) for both variables were less than 9% of the range of data. Fiber and lignin were predicted with R 2 > 0.65 and carbon and cellulose with R 2 > 0.45. Although R 2 of %C and cellulose were lower than Marea and %N, the measured variability of these constituents (especially %C) was also lower, and their RMSE values were beneath 12% of the range in overall variability. Model performance for δ 15 N was the lowest (R 2 = 0.48, RMSE = 0.95‰), but within 15% of the observed range. The resulting maps of chemical and morphological traits, together with their overall uncertainties, represent a first-of-its-kind approach for examining the spatiotemporal patterns of forest functioning and nutrient cycling across a broad range of temperate and sub-boreal ecosystems. These results offer an alternative to categorical maps of functional or physiognomic types by providing non-discrete maps (i.e., on a continuum) of traits that define those functional types. A key contribution of this work is the ability to assign retrieval uncertainties by pixel, a requirement to enable assimilation of these data products into ecosystem modeling frameworks to constrain carbon and nutrient cycling projections.
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Assessment of AVIRIS Laboratory and In-Flight Uniformity
An assessment of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) laboratory and in-flight uniformity is presented in this Slide presentation. The ideal uniform system is described, being a system where every spectrum is intercomparable to every other spectrum. Two types of failures to achieve this uniformity are described. Graphs showing measured spectral upwelling radiance, the expanded spectral convolution, the radiometric error from spectral error, the results from the hyperion Arizaro calibration experiment and a AVIRIS cross-track uniformity are among those presented. The reasons why uniformity matters are presented.
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Design of a Pushbroom Imaging Spectrometer that Exceeds AVIRIS Performance
This slide presentation reviews the design of a Pushbroom Imaging Spectrometer, that will exceed the performance of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The approach for the AVIRIS-II instrument is reviewed as are the specifications for the new spectrometer. Even though the pushbroom spectrometer is inherently non-uniform, the design of the AVIRIS-II provides for uniformity. Spot diagrams at the slit and at the detector inside the 27micron box are presented. A few of the challenges in the mechanical design and the making of the slit are discussed. The specifications of the 6604A detector array are reviewed. Slides showing the expected Signal to Noise Ratio performance are presented.
Airborne Visible/Infrared Imaging Spectrometer (AV↗
Radiometric Performance Model for AVIRIS
This slide presentation reviews the radiometric performance model for Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This model allows for an estimation of the signal throughput and noise properties of AVIRIS for the components. This understanding can point to areas for improvements of the components.. The signal to noise ratio properties may be estimated. An accurate radiometric performance model is essential for the use of existing instruments and the design of new instruments. Included in the presentation is a design view and a picture of the AVIRIS instrument. There is discussion of the signal, the signal area solid angle product, aspects of area solid angle time, the idealized radiometer photon calculation and noise both instrument read and photon counting noise. Graphs of signal throughput efficiency, input radiance, photons at the detector, signal e-, noise e- and the signal to noise ratio are presented.
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Proceedings of the 11th JPL Airborne Earth Science Workshop
This publication contains the proceedings of the JPL Airborne Earth Science Workshop 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 from March 5-8, 2001. Electronic versions of these papers may be found at the A VIRIS Web http://popo.jpl.nasa.gov/pub/docs/workshops/aviris.proceedings.html
Airborne Visible/Infrared Imaging Spectrometer (AV↗
AVIRIS User's Guide
This paper serves as a brief overview of the AVIRIS instrument (Airborne Visible/Infrared Imaging Spectrometer) and its role in the field of imaging spectrometry. Mission planning and flight operations are discussed, and recommendations are given regarding the deployment of ground truth experiments.
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Inflight Validation of AVIRIS Calibration in 1996 and 1997
The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures spectral radiance in the solar reflected spectrum from 400 to 2500 nm.
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Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models
A new technique, called multiple endmember spectral mixture analysis (MESM) was developed and tested in the Santa Monica Mountains, using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acqired in the fall of 1994 to map California chaparral.
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