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At least 217 records · Page 12

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↗

Measuring dry plant residues in grasslands: A case study using AVIRIS

Grasslands, savannah, and hardwood rangelands are critical ecosystems and sensitive to disturbance. Approximately 20 percent of the Earth's surface are grasslands and represent 3 million ha. in California alone. Developing a methodology for estimating disturbance and the effects of cumulative impacts on grasslands and rangelands is needed to effectively monitor these ecosystems. Estimating the dry biomass residue remaining on rangelands at the end of the growing season provides a basis for evaluating the effectiveness of land management practices. The residual biomass is indicative of the grazing pressure and provides a measure of the system capacity for nutrient cycling since it represents the maximum organic matter available for decomposition, and finally, provides a measure of the erosion potential for the ecosystem. Remote sensing presents a possible method for measuring dry residue. However, current satellites have had limited application due to the coarse spatial scales (relative to the patch dynamics) and insensitivity of the spectral coverage to resolve dry plant material. Several hypotheses for measuring the biochemical constituents of dry plant material, particularly cellulose and lignin, using high spectral resolution sensors were proposed. The use of Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) to measure dry plant residues over an oak savannah on the eastern slopes of the Coast Range in central California was investigated and it was asked what spatial and spectral resolutions are needed to quantitatively measure dry plant biomass in this ecosystem.

Fitzgerald, Michael↗

Estimating Expressed Temperature and Fractional Area of Hot Lava at the Kilauea Vent with AVIRIS Spectral Measurements

Imaging spectroscopy offers a framework based in physics and chemistry for scientific investigation of a wide range of phenomena of interest in the Earth environment. In the scientific discipline of volcanology knowledge of lava temperature and distribution at the surface provides insight into the volcano status and subsurface processes. A remote sensing strategy to measure surface lava temperatures and distribution would support volcanology research. Hot targets such as molten lava emit spectral radiance as a function of temperature. A figure shows a series of Planck functions calculated radiance spectra for hot targets at different temperatures. A maximum Lambertian solar reflected radiance spectrum is shown as well. While similar in form, each hot target spectrum has a unique spectral shape and is distinct from the solar reflected radiance spectrum. Based on this temperature-dependent signature, imaging spectroscopy provides an innovative approach for the remote-sensing-based measurement of lava temperature. A natural site for investigation of the measurement of lava temperature is the Big Island of Hawaii where molten lava from the Kilauea vent is present at the surface. In the past, Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data sets have been used for the analysis of hot volcanic targets and hot burning fires. The research presented here builds upon and extends this earlier work. The year 2000 Hawaii AVIRIS data set has been analyzed to derive lava temperatures taking into account factors of fractional fill, solar reflected radiance, and atmospheric attenuation of the surface emitted radiance. The measurements, analyses, and current results for this research are presented here.

Green, Robert O.↗

Separation of cirrus cloud from clear surface from AVIRIS data using the 1.38 micron water vapor band

Cirrus clouds play an important role in climate systems because of their large area coverage, persistence, and radiative effects. Thin cirrus clouds are difficult to detect in visible images and infrared images in the 10-12 micron atmospheric window region, particularly over land, because these clouds are partially transparent. Ackerman recently developed a method for detecting cirrus clouds using three narrow channels centered near 8, 11, and 12 microns, respectively, based on the analysis of IR emission spectra measured with a high spectral resolution interferometer. Barton also described a method for estimating cirrus cloud height and amount from measurements with two narrow channel radiometers of the Selective Chopper Radiometer on Nimbus 5. Both channels are located within the strong 2.7 micron water vapor band absorption region. One of the channels includes additional carbon dioxide absorption. A differential absorption technique with sets of empirical coefficients was used in the estimation of cirrus cloud heights and amounts. A technique using narrow channels in the strong 1.38 micron water vapor band absorption region for detecting cirrus clouds from spectral imaging data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) on 5 Dec. 1991 during the FIRE (The First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment) Phase 2 Field Experiment is described.

Gao, Bo-Cai↗

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

VandeVen, C.↗

Spatial/Spectral Identification of Endmembers from AVIRIS Data using Mathematical Morphology

During the last several years, a number of airborne and satellite hyperspectral sensors have been developed or improved for remote sensing applications. Imaging spectrometry allows the detection of materials, objects and regions in a particular scene with a high degree of accuracy. Hyperspectral data typically consist of hundreds of thousands of spectra, so the analysis of this information is a key issue. Mathematical morphology theory is a widely used nonlinear technique for image analysis and pattern recognition. Although it is especially well suited to segment binary or grayscale images with irregular and complex shapes, its application in the classification/segmentation of multispectral or hyperspectral images has been quite rare. In this paper, we discuss a new completely automated methodology to find endmembers in the hyperspectral data cube using mathematical morphology. The extension of classic morphology to the hyperspectral domain allows us to integrate spectral and spatial information in the analysis process. In Section 3, some basic concepts about mathematical morphology and the technical details of our algorithm are provided. In Section 4, the accuracy of the proposed method is tested by its application to real hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer. Some details about these data and reference results, obtained by well-known endmember extraction techniques, are provided in Section 2. Finally, in Section 5 we expose the main conclusions at which we have arrived.

Plaza, Antonio↗

Integrating remote sensing techniques at Cuprite, Nevada: AVIRIS, Thematic Mapper, and field spectroscopy

The Cuprite mining district in southwestern Nevada has become a test site for remote sensing studies with numerous airborne scanners and ground sensor data sets collected over the past fifteen years. Structurally, the Cuprite region can be divided into two areas with slightly different alteration and mineralogy. These zones lie on either side of a postulated low-angle structural discontinuity that strikes nearly parallel to US Route 95. Hydrothermal alternation at Cuprite was classified into three major zones: silicified, opalized, and argillized. These alteration types form a bulls-eye pattern east of the highway and are more linear on the west side of the highway making a striking contrast from the air and the imagery. Cuprite is therefore an ideal location for remote sensing research as it exhibits easily identified hydrothermal zoning, is relatively devoid of vegetation, and contains a distinctive spectrally diagnostic mineral suite including the ammonium feldspar buddingtonite, several types of alunite, different jarosites, illite, kaolinite, smectite, dickite, and opal. This present study brings a new dimension to these previous remote sensing and ground data sets compiled for Cuprite. The development of a higher resolution field spectrometer now provides the capability to combine extensive in-situ mineralogical data with a new geologic field survey and detailed Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) images. The various data collection methods and the refinement of the integrated techniques are discussed.

Hill, Bradley↗

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↗

Imaging systems for the delineation of spectral properties of geologic materials in the visible and near-infrared

The current status of imaging systems for the identification of the spectral properties of geologic minerals in the visible and near infrared ranges is reviewed. The technical characteristics of the most important instruments are given, including the MSS and TM, the Airborne Imaging Spectrometer, (AIS) the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and the Shuttle Imaging Spectrometer Experiment (SISEX). It is pointed out that none of the current systems have sufficient spectral resolution to identify mineralogy on the basis of absorption characteristics in the visible, near-infrared or shortwave-infrared bands. The development of new systems with higher spectral resolution is discussed.

Marsh, S. E.↗

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.↗

Evaluation of Airborne Visible/Infrared Imaging Spectrometer Data of the Mountain Pass, California carbonatite complex

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data of the Mountain Pass, California carbonatite complex were examined to evaluate the AVIRIS instrument performance and to explore alternative methods of data calibration. Although signal-to-noise estimates derived from the data indicated that the A, B, and C spectrometers generally met the original instrument design objectives, the S/N performance of the D spectrometer was below expectations. Signal-to-noise values of 20 to 1 or lower were typical of the D spectrometer and several detectors in the D spectrometer array were shown to have poor electronic stability. The AVIRIS data also exhibited periodic noise, and were occasionally subject to abrupt dark current offsets. Despite these limitations, a number of mineral absorption bands, including CO3, Al-OH, and unusual rare earth element bands, were observed for mine areas near the main carbonatite body. To discern these bands, two different calibration procedures were applied to remove atmospheric and solar components from the remote sensing data. The two procedures, referred to as the single spectrum and the flat field calibration methods gave distinctly different results. In principle, the single spectrum method should be more accurate; however, additional fieldwork is needed to rigorously determine the degree of calibration success.

Crowley, James↗

The Shuttle Imaging Spectrometer Experiment (SISEX)

The concept of the imaging spectrometer is becoming established as a major new thrust in remote sensing of the earth. For several years, JPL has operated the airborne imaging spectrometer on a NASA C-130; this instrument has demonstrated the direct identification of surface materials using imaging spectrometry. An advanced aircraft instrument, the airborne visible/infrared imaging spectrometer (AVIRIS), began operation on a NASA U-2 in 1987. The Shuttle Imaging Spectrometer Experiment (SISEX) was conceived as the next step in the sequence, and would provide a relatively inexpensive demonstration of the concept in earth orbit. This paper describes the design and development status of SISEX and the status of the enabling technology.

Herring, Mark↗

Calibration Of Airborne Visible/IR Imaging Spectrometer

Paper describes laboratory spectral and radiometric calibration of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) applied to all AVIRIS science data collected in 1987. Describes instrumentation and procedures used and demonstrates that calibration accuracy achieved exceeds design requirements. Developed for use in remote-sensing studies in such disciplines as botany, geology, hydrology, and oceanography.

Vane, G. A.↗

Evaluation of the airborne visible-infrared imaging spectrometer for mapping subtle lithological variation

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), flown aboard the NASA ER-2 aircraft in 1987 and 1989, used four linear arrays and four individual spectrometers to collect data simultaneously from the 224 bands in a scanned 614 pixel-wide swath perpendicular to the aircraft direction. The research had two goals. One was to evaluate the AVIRIS data. The other was to look at the subtle lithological variation at the two test sites to develop a better understanding of the regional geology and surficial processes. The geometric characteristics of the data, adequacy of the spatial resolution, and adequacy of the spectral sampling interval are evaluated. Geologic differences at the test sites were mapped. They included lithological variation caused by primary sedimentary layering, facies variation, and weathering; and subtle mineralogical differences caused by hydrothermal alterations of igneous and sedimentary rocks. The investigation used laboratory, field, and aircraft spectral measurements; known properties of geological materials; digital image processing and spectrum processing techniques; and field geologic data to evaluate the selected characteristics of the AVIRIS data.

Kruse, Fred A.↗

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.↗

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.↗

Artificial intelligence for geologic mapping with imaging spectrometers

This project was a three year study at the Center for the Study of Earth from Space (CSES) within the Cooperative Institute for Research in Environmental Science (CIRES) at the University of Colorado, Boulder. The goal of this research was to develop an expert system to allow automated identification of geologic materials based on their spectral characteristics in imaging spectrometer data such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This requirement was dictated by the volume of data produced by imaging spectrometers, which prohibits manual analysis. The research described is based on the development of automated techniques for analysis of imaging spectrometer data that emulate the analytical processes used by a human observer. The research tested the feasibility of such an approach, implemented an operational system, and tested the validity of the results for selected imaging spectrometer data sets.

Kruse, F. A.↗

Cirrus cloud detection from airborne imaging spectrometer data using the 1.38 micron water vapor band

Using special images acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) at 20 km altitude, we show that wavelengths close to the center of the strong 1.38 micron water vapor band are useful for detecting thin cirrus clouds. The detection makes use of the fact that cirrus clouds are located above almost all the atmospheric water vapor. Because of the strong water vapor absorption in the lower atmosphere, AVIRIS channels near 1.38 micron receive little scattered solar radiance from the surface of low level clouds. When cirrus clouds are present, however, these channels receive large amounts of scattered solar radiance from the cirrus clouds. Our ability to determine cirrus cloud cover using space-based remote sensing will be improved if channels near the center of the 1.38 micron water vapor band are added to future satellites.

Gao, Bo-Cai↗