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At least 235 records · Page 13

Impact of differences in the solar irradiance spectrum on surface reflectance retrieval with different radiative transfer codes

Surface reflectance retrieval from imaging spectrometer data as acquired with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has become important for quantitative analysis. In order to calculate surface reflectance from remotely measured radiance, radiative transfer codes such as 5S and MODTRAN2 play an increasing role for removal of scattering and absorption effects of the atmosphere. Accurate knowledge of the exo-atmospheric solar irradiance (E(sub 0)) spectrum at the spectral resolution of the sensor is important for this purpose. The present study investigates the impact of differences in the solar irradiance function, as implemented in a modified version of 5S (M5S), 6S, and MODTRAN2, and as proposed by Green and Gao, on the surface reflectance retrieved from AVIRIS data. Reflectance measured in situ is used as a basis of comparison.

Staenz, K.↗

Imaging spectrometers for remote sensing from space

Three imaging spectrometers and two camera systems for remote sensing are described. Two of the imaging spectrometers are versions of the Visible and Infrared Mapping Spectrometer (VIMS) for Mars Observer and the Comet Rendezvous Asteroid Flyby (CRAF) mission. The other spectrometer is the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) which is currently under construction. The optical imaging systems are the wide angle and narrow angle cameras for the CRAF mission.

Chrisp, M. P.↗

Physical Interpretation of the Correlation Between Multi-Angle Spectral Data and Canopy Height

Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally

Schull, M. A.↗

Imager-to-Radiometer In-flight Cross Calibration: RSP Radiometric Comparison with Airborne and Satellite Sensors

This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP), which takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI). First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.

calibrating↗

Radiometric and spectral stray light correction for the Portable Remote Imaging Spectrometer (PRISM) coastal ocean sensor

The airborne Portable Remote Imaging Spectrometer (PRISM) instrument is based on a fast (F/1.8) Dyson spectrometer operating at 350-1050 nm and a two-mirror telescope combined with a Teledyne HyViSI 6604A detector array. Raw PRISM data contain electronic and optical artifacts that must be removed prior to radiometric calibration. We provide an overview of the process transforming raw digital numbers to calibrated radiance values. Electronic panel artifacts are first corrected using empirical relationships developed from laboratory data. The instrument spectral response functions (SRF) are reconstructed using a measurement-based optimization technique. Removal of SRF effects from the data improves retrieval of true spectra, particularly in the typically low-signal near-ultraviolet and near-infrared regions. As a final step, radiometric calibration is performed using corrected measurements of an object of known radiance. Implementation of the complete calibration procedure maximizes data quality in preparation for subsequent processing steps, such as atmospheric removal and spectral signature classification.

Thompson, David R.↗

HyTES: Thermal Imaging Spectrometer Development

The Jet Propulsion Laboratory has developed the Hyperspectral Thermal Emission Spectrometer (HyTES). It is an airborne pushbroom imaging spectrometer based on the Dyson optical configuration. First low altitude test flights are scheduled for later this year. HyTES uses a compact 7.5-12 micrometer m hyperspectral grating spectrometer in combination with a Quantum Well Infrared Photodetector (QWIP) and grating based spectrometer. The Dyson design allows for a very compact and optically fast system (F/1.6). Cooling requirements are minimized due to the single monolithic prism-like grating design. The configuration has the potential to be the optimal science-grade imaging spectroscopy solution for high altitude, lighter-than-air (HAA, LTA) vehicles and unmanned aerial vehicles (UAV) due to its small form factor and relatively low power requirements. The QWIP sensor allows for optimum spatial and spectral uniformity and provides adequate responsivity which allows for near 100mK noise equivalent temperature difference (NEDT) operation across the LWIR passband. The QWIP's repeatability and uniformity will be helpful for data integrity since currently an onboard calibrator is not planned. A calibration will be done before and after eight hour flights to gage any inconsistencies. This has been demonstrated with lab testing. Further test results show adequate NEDT, linearity as well as applicable earth science emissivity target results (Silicates, water) measured in direct sunlight.

remote sensing↗

Thermal Infrared Imaging Spectrometer - An advanced optics technology instrument

Through the use of a special optical filter, the Thermal Infrared Imaging Spectrometer, an airborne multispectral IR imaging instrument operating in the thermal emission region (7.5-14 microns), will achieve signal-to-noise ratios greater than 600 with ambient temperature optics. This instrument will be used to do compositional surface mapping of the terrain, and will refine the ability to categorize rock families and types by providing much higher spectral resolution in the emission region than was previously available. Details of the optical system, the detector, the cooler system, and the support electronics are described.

Mahoney, Colin↗

Summaries of the Seventh JPL Airborne Earth Science Workshop January 12-16, 1998: AVIRIS Workshop - Volume 1

This publication contains the summaries for the Seventh JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 12-16, 1998. The main workshop is divided into three smaller workshops, and each workshop has a volume as follows: (1) Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Workshop; (2) Airborne Synthetic Aperture Radar (AIRSAR) Workshop; and (3) Thermal Infrared Multispectral Scanner (TIMS) Workshop. This Volume 1 publication contains 58 papers taken from the AVIRIS workshop.

Robert O Green↗

Estimation of crown closure from AVIRIS data using regression analysis

Crown closure is one of the input parameters used for forest growth and yield modelling. Preliminary work by Staenz et al. indicates that imaging spectrometer data acquired with sensors such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) have some potential for estimating crown closure on a stand level. The objectives of this paper are: (1) to establish a relationship between AVIRIS data and the crown closure derived from aerial photography of a forested test site within the Interior Douglas Fir biogeoclimatic zone in British Columbia, Canada; (2) to investigate the impact of atmospheric effects and the forest background on the correlation between AVIRIS data and crown closure estimates; and (3) to improve this relationship using multiple regression analysis.

Staenz, K.↗

Innovative Imaging Spectrometer Calibration Techniques

A laboratory calibration of the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) allowed experimentation with several innovative calibration techniques that would improve calibration accuracy, provide independent checks for systematic errors, and reduce the time required to collect a calibration data set.

remote sensing AVIRIS Airborne Visible Infrared Im↗

Mapping Weathering and Alteration Minerals in the Comstock and Geiger Grade Areas using Visible to Thermal Infrared Airborne Remote Sensing Data

To support research into both precious metal exploration and environmental site characterization a combination of high spatial/spectral resolution airborne visible, near infrared, short wave infrared (VNIR/SWIR) and thermal infrared (TIR) image data were acquired to remotely map hydrothermal alteration minerals around the Geiger Grade and Comstock alteration regions, and map the mineral by-products of weathered mine dumps in Virginia City. Remote sensing data from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), SpecTIR Corporation's airborne hyperspectral imager (HyperSpecTIR), the MODIS-ASTER airborne simulator (MASTER), and the Spatially Enhanced Broadband Array Spectrograph System (SEBASS) were acquired and processed into mineral maps based on the unique spectral signatures of image pixels. VNIR/SWIR and TIR field spectrometer data were collected for both calibration and validation of the remote data sets, and field sampling, laboratory spectral analyses and XRD analyses were made to corroborate the surface mineralogy identified by spectroscopy. The resulting mineral maps show the spatial distribution of several important alteration minerals around each study area including alunite, quartz, pyrophyllite, kaolinite, montmorillonite/muscovite, and chlorite. In the Comstock region the mineral maps show acid-sulfate alteration, widespread propylitic alteration and extensive faulting that offsets the acid-sulfate areas, in contrast to the larger, dominantly acid-sulfate alteration exposed along Geiger Grade. Also, different mineral zones within the intense acid-sulfate areas were mapped. In the Virginia City historic mining district the important weathering minerals mapped include hematite, goethite, jarosite and hydrous sulfate minerals (hexahydrite, alunogen and gypsum) located on mine dumps. Sulfate minerals indicate acidic water forming in the mine dump environment. While there is not an immediate threat to the community, there are clearly sources of acidic drainage that were identified remotely.

imaging spectroscopy↗

Summaries of the Sixth Annual JPL Airborne Earth Science Workshop: AIRSAR Workshop - Volume 2

The Sixth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on March 4-8, 1996, was divided into two smaller workshops:(1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, and The Airborne Synthetic Aperture Radar (AIRSAR) workshop. This current paper, Volume 2 of the Summaries of the Sixth Annual JPL Airborne Earth Science Workshop, presents the summaries for The Airborne Synthetic Aperture Radar (AIRSAR) workshop.

Kim, Yun-Jin↗

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.↗

AVIRIS Spectrometer Maps Total Water Vapor Column

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) processes maps of vertical-column abundances of water vapor in atmosphere with good precision and spatial resolution. Maps provide information for meteorology, climatology, and agriculture.

Conel, James E.↗

Integrating very-high-resolution UAS data and airborne imaging spectroscopy to map the fractional composition of Arctic plant functional types in Western Alaska

Widespread changes in vegetation cover and composition are driving strong impacts on Arctic ecosystem functioning and global climate feedbacks. An accurate characterization of tundra vegetation composition is required to understand how the Arctic will respond to future climate change. However, quantifying tundra vegetation composition over large areas is challenging as commonly-used satellite observations are too coarse, spatially and spectrally, to differentiate low-lying tundra vegetation types. Recent airborne and spaceborne imaging spectroscopy platforms provide better data to characterize vegetation composition. Yet, our ability to characterize vegetation composition with imaging spectroscopy remains largely unexplored in the Arctic, particularly due to a lack of ground observations needed to train and test classification models. To address this problem, we collected very-high-resolution (VHR, ~5 cm) unoccupied aerial system (UAS) imagery at three low-Arctic tundra sites located on the Seward Peninsula, western Alaska. In this paper, we examine the feasibility of integrating imagery from the UAS and the hyperspectral Airborne Visible/Infrared Imaging Spectrometer, Next Generation (AVIRIS-NG) airborne instrument to map the fractional composition of 12 key Arctic plant functional types (PFTs). To this end, we first mapped the 12 PFTs from our VHR UAS imagery using random forest classification. We then used these UAS-derived PFT maps as ground truth to develop partial least squares regression (PLSR) models to predict the fractional cover (FCover) of each PFT from AVIRIS-NG imagery. Further, we evaluated the performance of our PLSR models using reserved UAS samples, as well as by mapping PFT FCover and dominant PFT for large tundra landscapes. Our results show that 1) Arctic PFTs can be effectively mapped using VHR UAS imagery, with overall accuracy between 86% and 92%, 2) when the UAS mapped PFTs were used to inform PLSR scaling models, the FCover of the 12 PFTs could be effectively estimated from AVIRIS-NG imagery with a mean absolute error (MAE) <0.13, and 3) our PLSR models outperformed traditional, fully constrained least-squares (FCLS) linear mixture analysis and produced high-quality, spatially contiguous PFT FCover and PFT maps that captured vegetation spatial patterns with similar accuracy to those developed from UAS imagery. The developed PLSR models have the potential to be broadly applied for quantifying vegetation composition with AVIRIS-NG images to help monitor tundra vegetation dynamics and improve process-based modeling of tundra ecosystems.

54 ENVIRONMENTAL SCIENCES↗