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At least 289 records · Page 16

Radiative transfer code based estimation of atmospheric parameters for inversion of imaging spectrometer measured radiance to apparent surface reflectance

Surface reflectance is required to quantitatively investigate molecular absorption and particle scattering properties of materials on the Earth's surface. Atmospheric aerosol optical depth, surface pressure and water vapor are required to constrain a radiative transfer code for the inversion of measured spectral radiance to apparent surface reflectance. A suite of algorithms using nonlinear least squares fitting techniques are described that directly estimate these atmospheric parameters from spectral radiance measured by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The derived atmospheric parameters are used to constrain a radiative transfer code for the inversion of the imaging spectrometer radiance to apparent reflectance. The derived apparent reflectance is validated with respect to in situ measurement on the same target.

Green, Robert O.↗

Hyperspectral Image Classification using a Self-Organizing Map

The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

Martinez, P.↗

Movement of water vapor in the atmosphere measured by an imaging spectrometer at Rogers Dry Lake, CA

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.

Green, Robert O.↗

Passive Microwave Studies of Atmospheric Precipitation and State

The principal contributions of this research on novel passive microwave spectral techniques are in the areas of: (1) global precipitation mapping using the opaque spectral bands on research and operational weather satellites, (2) development and analysis of extensive aircraft observational imaging data sets obtained using the MIT instrument NAST-M near 54 and 118 GHz over hurricanes and weather ranging from tropical to polar; simultaneous data from the 8500-channel infrared spectrometer NAST-I was obtained and analyzed separately, (3) estimation of hydrometeor diameters in cell tops using data from aircraft and spacecraft, (4) continued improvement of expressions for atmospheric transmittance at millimeter and sub-millimeter wavelengths, (5) development and airborne use of spectrometers operating near 183- and 425-GHz bands, appropriate to practical systems in geosynchronous orbit, and (6) preliminary studies of the design and performance of future geosynchronous microwave sounders for temperature and humidity profiles and for continuous monitoring of regional precipitation through most clouds. This work was a natural extension of work under NASA Grant NAG5-2545 and its predecessors. This earlier work had developed improved airborne imaging microwave spectrometers and had shown their sensitivity to precipitation altitude and character. They also had prepared the foundations for precipitation estimation using the opaque microwave bands. The field demonstration and improvement of these capabilities was then a central part of the present research reported here, during which period the first AMSU data became available and several hurricanes were overflown by NAST-M, yielding unique data about their microwave signatures. This present work has in turn helped lay the foundation for future progress in incorporating the opaque microwave channels in systems for climatologically precise global precipitation mapping from current and future operational satellites. Extension of these techniques to global snowfall mapping, even over ice and snow, is one such opportunity signaled by this research.

Staelin, David H.↗

Summaries of the 4th Annual JPL Airborne Geoscience Workshop. Volume 2: TIMS Workshop

This is volume 2 of a three volume set of publications that contain the summaries for the Fourth Annual JPL Airborne Geoscience Workshop, held in Washington, D.C. on October 25-29, 1993. The main workshop is divided into three smaller workshops as follows: The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on October 25-26. The summaries for this workshop appear in Volume 1. The Thermal Infrared Multispectral Scanner (TIMS) workshop, on October 27. The summaries for this workshop appear in Volume 2. The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on October 28-29. The summaries for this workshop appear in Volume 3.

Realmuto, Vincent J.↗

Summaries of the 4th Annual JPL Airborne Geoscience Workshop. Volume 1: AVIRIS Workshop

This publication contains the summaries for the Fourth Annual JPL Airborne Geoscience Workshop, held in Washington, D. C. October 25-29, 1993 The main workshop is divided into three smaller workshops as follows: The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, October 25-26 (the summaries for this workshop appear in this volume, Volume 1); The Thermal Infrared Multispectral Scanner (TMIS) workshop, on October 27 (the summaries for this workshop appear in Volume 2); and The Airborne Synthetic Aperture Radar (AIRSAR) workshop, October 28-29 (the summaries for this workshop appear in Volume 3).

Green, Robert O.↗

Integration of visible-through microwave-range multispectral image data sets for geologic mapping

Multispectral remote sensing data sets collected during the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 in the southwestern U.S. were used to produce thematic image maps showing details of the surface geology. LANDSAT TM (Thematic Mapper) images were used to map the distribution of clays, carbonates, and iron oxides. AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data were used to identify and map calcite, dolomite, sericite, hematite, and geothite, including mixtures. TIMS (Thermal Infrared Multispectral Scanner) data were used to map the distribution of igneous rock phases and carbonates based on their silica contents. AIRSAR (Airborne Synthetic Aperture Radar) data were used to map surface textures related to the scale of surface roughness. The AIRSAR also allowed identification of previously unmapped fault segments and structural control of lithology and minerology. Because all of the above data sets were geographically referenced, combination of different data types and direct comparison of the results with conventional field and laboratory data sets allowed improved geologic mapping of the test site.

Kruse, Fred A.↗

Summaries of the Third Annual JPL Airborne Geoscience Workshop. Volume 2: TIMS Workshop

This publication contains the preliminary agenda and summaries for the Third Annual JPL Airborne Geoscience Workshop, held at the Jet Propulsion Laboratory, Pasadena, California, on 1-5 June 1992. This main workshop is divided into three smaller workshops as follows: (1) the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on June 1 and 2; the summaries for this workshop appear in Volume 1; (2) the Thermal Infrared Multispectral Scanner (TIMS) workshop, on June 3; the summaries for this workshop appear in Volume 2; and (3) the Airborne Synthetic Aperture Radar (AIRSAR) workshop, on June 4 and 5; the summaries for this workshop appear in Volume 3.

Realmuto, Vincent J.↗

Summaries of the Third Annual JPL Airborne Geoscience Workshop. Volume 3: AIRSAR Workshop

This publication contains the preliminary agenda and summaries for the Third Annual JPL Airborne Geoscience Workshop, held at the Jet Propulsion Laboratory, Pasadena, California, on 1-5 June 1992. This main workshop is divided into three smaller workshops as follows: (1) the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on June 1 and 2; the summaries for this workshop appear in Volume 1; (2) the Thermal Infrared Multispectral Scanner (TIMS) workshop, on June 3; the summaries for this workshop appear in Volume 2; and (3) the Airborne Synthetic Aperture Radar (AIRSAR) workshop, on June 4 and 5; the summaries for this workshop appear in Volume 3.

Vanzyl, Jakob↗

Expert system-based mineral mapping using AVIRIS

Integrated analysis of imaging spectrometer data and field spectral measurements were used in conjunction with conventional geologic field mapping to characterize bedrock and surficial geology at the northern end of Death Valley, California and Nevada. A knowledge-based expert system was used to automatically produce image maps from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data showing the principal surface mineralogy. The imaging spectrometer data show the spatial distribution of spectrally distinct minerals occurring both as primary rock-forming minerals and as alteration and weathering products. Field spectral measurements were used to verify the mineral maps and field mapping was used to extend the remote sensing results. Geographically referenced image-maps produced from these data form new base maps from which to develop improved understanding of the processes of deposition and erosion affecting the present land surface. The 'northern Grapevine Mountains' (NGM) study area was reported on in numerous papers. This area is an unnamed northwestward extension of the range. Most of the research here has concentrated on mapping of Jurassic-age plutons and associated hydrothermal alteration, however, the nature and scope of these studies is much broader, pertaining to the geologic history and development of the entire Death Valley region. AVIRIS data for the NGM site were obtained during May 1989. Additional AVIRIS data were acquired during September 1989 as part of the Geologic Remote Sensing Field Experiment (GRSFE). The area covered by these data overlaps slightly with the May 1989 data. Three and one-half AVIRIS scenes total were analyzed.

Kruse, Fred A.↗

Monitoring of Volcanogenic CO2-Induced Tree Kills with AVIRIS Image Data at Mammoth Mountain, California

Elevated cold CO2 emissions from the flank of Mammoth Mountain volcano on the southwest rim of the Long Valley Caldera, eastern California, have been the cause of over 100 acres of dead trees in that area since 1990. The source of the CO2 gas is thought to be from one or more magmatic intrusion(s) beneath Mammoth Mountain and is probably related to a period of seismic unrest that began in 1989. The gas rises to the surface probably from depths of a few kilometers, along faults and fracture zones. The gas is at ambient temperature and diffuses from the soil rather than discharging from distinct vents. Typically, soil gas concentrations in tree-kill areas range from 10% to over 90% CO2 by volume, as compared to normal background of < 1% in healthy forest. The gas composition is predominantly CO2 mixed with air (sulfur gases are not elevated), and C and He isotopic ratios are consistent with a magmatic origin for the gas. The total CO2 emission has been estimated at 1200 tons/day, comparable to the emissions at Kilauea. Some of the dead trees are as old as 250 years, suggesting that similar anomalous gas discharge has not occurred over the previous few hundred years. The delta C-13/12 ratio in the Mammoth Mountain CO2 emission averages about -4.5 (PDB standard). This is consistent with a mantle source for the carbon. However, the large volume of the emission suggests that not all of the CO2 is necessarily being generated from the 1989 intrusion. The voluminous gas could be leaking from a vapor-rich zone, capped by an impermeable layer, that was supplied CO2 from degassing of many small magma bodies that intruded beneath the mountain over a period of decades or centuries. Earthquakes in 1989 could have fractured the capping layer and provided pathways for the escape Of CO2 to the surface. Alternatively, some of the CO2 could be derived from contact metamorphism of carbonate rocks intruded by magma. Carbonate-bearing Paleozoic roof pendents crop out in close proximity to Mammoth Mountain. It is possible that similar rocks could occur at depth beneath Mammoth Mountain, and could have contributed CO2 from thermal decomposition caused from recent intrusions. We hope to determine the C-13/12 ratio of a suite of samples to demonstrate if the carbonate rocks could be the source of at least part of the 1990-97 CO2 emission. To better understand the behavior of the CO2 gas, we have used hyperspectral imagery data of Mammoth Mountain acquired from the Airborne Visual/Infrared Imaging Spectrometer (AVIRIS) to map out areas of dead trees. The areas of tree kill have increased in size from about 50 acres in 1994 to about 100 acres in 1997. Tree kill is the major surface manifestation of the carbon dioxide flux at Mammoth Mountain, is widely dispersed, and has been cursorily mapped by regular field mapping techniques in the area. Initial investigations using airborne digital imagery from the Thematic Mapper Simulator (NS001) and AVIRIS instruments have shown extremely encouraging results for complete delineation of the vegetation anomalies. The most successful maps (when compared with ground truth) were developed using AVIRIS data with spectral angle mapper and matched filter algorithms with a data set that was reduced to maximum variance via the minimum noise fraction transformation. The result of this work is a series of maps that show the tree kill areas occurring in an halo-pattern surrounding the base of Mammoth Mountain. We are applying these same techniques to earlier AVIRIS images of Mammoth Mountain to examine the progression of the tree kill areas over time. Temporal maps of the tree kill areas may assist in constructing a picture of the structure beneath Mammoth Mountain.

Hausback, Brian P.↗

Portable Remote Imaging Spectrometer (PRISM): Laboratory and Field Calibration

We report the characteristics of the Portable Remote Imaging Spectrometer, an airborne sensor specifically designed for the challenges of coastal ocean research. PRISM has high signal to noise ratio and uniformity, as well as low polarization sensitivity. Acquisition of high quality data has been demonstrated with the first engineering flight.

imaging spectrometer↗

Abundance recovery error analysis using simulated AVIRIS data

Measurement noise and imperfect atmospheric correction translate directly into errors in the determination of the surficial abundance of materials from imaging spectrometer data. The effects of errors on abundance recovery were investigated previously using Monte Carlo simulation methods by Sabol et. al. The drawback of the Monte Carlo approach is that thousands of trials are needed to develop good statistics on the probable error in abundance recovery. This computational burden invariably limits the number of scenarios of interest that can practically be investigated. A more efficient approach is based on covariance analysis. The covariance analysis approach expresses errors in abundance as a function of noise in the spectral measurements and provides a closed form result eliminating the need for multiple trials. Monte Carlo simulation and covariance analysis are used to predict confidence limits for abundance recovery for a scenario which is modeled as being derived from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).

Stoner, William W.↗

AVIRIS spectra correlated with the chlorophyll concentration of a forest canopy

Imaging spectrometers have many potential applications in the environmental sciences. One of the more promising applications is that of estimating the biochemical concentrations of key foliar biochemicals in forest canopies. These estimates are based on spectroscopic theory developed in agriculture and could be used to provide the spatial inputs necessary for the modeling of forest ecosystem dynamics and productivity. Several foliar biochemicals are currently under investigation ranging from those with primary absorption features in visible to middle infrared wavelengths (e.g., water, chlorophyll) to those with secondary to tertiary absorption features in this part of the spectrum (e.g., nitrogen, lignin). The foliar chemical of interest in this paper is chlorophyll; this is a photoreceptor and catalyst for the conversion of sunlight into chemical energy and as such plays a vital role in the photochemical synthesis of carbohydrates in plants. The aim of the research reported here was to determine if the chlorophyll concentration of a forest canopy could be correlated with the reflectance spectra recorded by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).

Kupiec, John↗

Oregon transect: Comparison of leaf-level reflectance with canopy-level and modelled reflectance

The Oregon Transect Ecosystem Research (OTTER) project involves the collection of a variety of remotely-sensed and in situ measurements for characterization of forest biophysical and biochemical parameters. The project includes nine study plots located along an environmental gradient in west-central Oregon, extending from the Pacific coast inland approximately 300km. These plots represent a broad range in ecosystem structure and function. Within the OTTER project, the sensitivity of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) signal to absorption by foliar biochemicals is being examined. AVIRIS data were acquired over all plots in conjunction with the four OTTER Multi-sensor Aircraft Campaigns spanning the growing season. Foilage samples were gathered during each campaign for biochemical determination (at Ames Research Center), to estimate stand-level constituency at each plot. Directional-hemispheric leaf reflectance throughout the 400-2400nm region was measured in the laboratory as an aid to interpreting concurrent AVIRIS data. Obtaining leaf spectra in this manner reduces or eliminates the confounding influences of atmosphere, canopy architecture, and reflectance by woody components, understory, and exposed soils which are present in airborne observations. These laboratory spectra were compared to simulated spectra derived by inverting the PROSPECT leaf-level canopy reflectance derived from AVIRIS data by use of the LOWTRAN-7 atmospheric radiative-transfer model.

Johnson, Lee F.↗

Estimating snow grain size using AVIRIS data

Estimates of snow grain size for the near-surface snow layer were calculated for the Tioga Pass region and Mammoth Mountain in the Sierra Nevada, California, using an inversion technique and data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The Tioga Pass and Mammoth Mountain single-band AVIRIS radiance images were atmospherically corrected to obtain surface reflectance. A discrete-ordinate model was used to calculate directional reflectance as a function of snowpack grain size for a wide range of snow grain radii. The resulting radius vs. reflectance curves were each fit using a nonlinear least squares technique which provided a means of transforming surface reflectance in each AVIRIS image to optically equivalent grain size on a per-pixel basis. The model results and grain size estimates derived from the AVIRIS data show that, for solar incidence angles between 0 and 30, the technique provides good estimates of grain size. This work provides the first quantitative estimates for grain size using data acquired from an airborne remote sensing instrument and is an important step in improving our ability to retrieve snow physical properties independent of field measurements.

Nolin, Anne W.↗

Airborne imaging spectroscopy surveys of Arctic and boreal Alaska and northwestern Canada 2017–2023

Since 2015, NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) has investigated how climate change impacts the vulnerability and/or resilience of the permafrost-affected ecosystems of Alaska and northwestern Canada. ABoVE conducted extensive surveys with the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) during 2017, 2018, 2019, and 2022 and with AVIRIS-3 in 2023 to characterize tundra, taiga, peatlands, and wetlands in unprecedented detail. The ABoVE AVIRIS dataset comprises ~1700 individual flight lines covering ~120,000 km 2 with nominal 5 m × 5 m spatial resolution. Data include individual transects to capture important gradients like the tundra-taiga ecotone and maps of up to 10,000 km 2 for key study areas like the Mackenzie Delta. The ABoVE AVIRIS surveys enable diverse ecosystem science, provide crucial benchmark data for validating retrievals from the PACE, PRISMA, and EnMAP satellite sensors and help prepare for the SBG and CHIME missions. This paper guides interested researchers to fully explore the ABoVE AVIRIS spectral imagery and complements our guide to the ABoVE airborne synthetic aperture radar surveys.

Miller, Charles E. [California Institute of Techno↗

Vegetation species composition and canopy architecture information expressed in leaf water absorption measured in the 1000 nm and 2200 spectral region by an imaging spectrometer

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.

Green, Robert O.↗