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NASA NTRS1992

AVIRIS study of Death Valley evaporite deposits using least-squares band-fitting methods

Minerals found in playa evaporite deposits reflect the chemically diverse origins of ground waters in arid regions. Recently, it was discovered that many playa minerals exhibit diagnostic visible and near-infrared (0.4-2.5 micron) absorption bands that provide a remote sensing basis for observing important compositional details of desert ground water systems. The study of such systems is relevant to understanding solute acquisition, transport, and fractionation processes that are active in the subsurface. Observations of playa evaporites may also be useful for monitoring the hydrologic response of desert basins to changing climatic conditions on regional and global scales. Ongoing work using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to map evaporite minerals in the Death Valley salt pan is described. The AVIRIS data point to differences in inflow water chemistry in different parts of the Death Valley playa system and have led to the discovery of at least two new North American mineral occurrences. Seven segments of AVIRIS data were acquired over Death Valley on 31 July 1990, and were calibrated to reflectance by using the spectrum of a uniform area of alluvium near the salt pan. The calibrated data were subsequently analyzed by using least-squares spectral band-fitting methods, first described by Clark and others. In the band-fitting procedure, AVIRIS spectra are fit compared over selected wavelength intervals to a series of library reference spectra. Output images showing the degree of fit, band depth, and fit times the band depth are generated for each reference spectrum. The reference spectra used in the study included laboratory data for 35 pure evaporite spectra extracted from the AVIRIS image cube. Additional details of the band-fitting technique are provided by Clark and others elsewhere in this volume.

Crowley, J. K.↗

NASA NTRS1999

Quantifying BRDF Effects in Comparing Landsat-7 and AVIRIS Near-Simultaneous Acquisitions for Studies of High Plains Vegetation Cover

Approximately 100,000 sq. km of the High Plains of the central United States are covered by sand dunes and sand sheets deposited during the Holocene. Soil-dating evidence shows that there were at least four periods of dune reactivation during major droughts in the last 10,000 years. The dunes in this region are anchored by vegetation. We have undertaken a study of land-use change in the High Plains from 1985 to the present using Landsat 5 TM and Landsat 7 ETM+ images to map variation in vegetation cover during wet and dry years. Mapping vegetation cover of less than 20% is important in modeling potential surface reactivation since at this level the vegetation no longer sufficiently shields sandy surfaces from movement by wind. Landsat TM data have both the spatial resolution and temporal coverage to facilitate vegetation cover analysis for model development and verification. However, there is still the question of how accurate TM data are for the measurement of both growing and senescent vegetation in and and semi-arid regions. AVIRIS provides both high spectral resolution as well as high signal-to-noise ratio and can be used to test the accuracy of Landsat TM and ETM+ data. We have analyzed data from AVIRIS flown nearly concurrently with a Landsat 7 overpass. The comparison between an AVIRIS image swath of 11 km width subtending a 30 deg. angle and the same area covered by a 0.8 deg. angle from Landsat required accounting for the BRDF. A normalization technique using the ratio of the reflectances from registered AVIRIS and Landsat data proved superior to the techniques of column averaging on AVIRIS data alone published previously by Kennedy et al. This technique can be applied to aircraft data covering a wider swath angle than AVIRIS to develop BRDF responses for a wide variety of surfaces more efficiently than from ground measurements.

Goetz, A. F. H.↗

NASA NTRS2001

Sensing, Spectra and Scaling: What's in Store for Land Observations

Bill Pecora's 1960's vision of the future, using spacecraft-based sensors for mapping the environment and exploring for resources, is being implemented today. New technology has produced better sensors in space such as the Landsat Thematic Mapper (TM) and SPOT, and creative researchers are continuing to find new applications. However, with existing sensors, and those intended for launch in this century, the potential for extracting information from the land surface is far from being exploited. The most recent technology development is imaging spectrometry, the acquisition of images in hundreds of contiguous spectral bands, such that for any pixel a complete reflectance spectrum can be acquired. Experience with Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has shown that, with proper attention paid to absolute calibration, it is possible to acquire apparent surface reflectance to 5% accuracy without any ground-based measurement. The data reduction incorporates in educated guess of the aerosol scattering, development of a precipitable water vapor map from the data and mapping of cirrus clouds in the 1.38 micrometer band. This is not possible with TM. The pixel size in images of the earth plays and important role in the type and quality of information that can be derived. Less understood is the coupling between spatial and spectral resolution in a sensor. Recent work has shown that in processing the data to derive the relative abundance of materials in a pixel, also known is unmixing, the pixel size is an important parameter. A variance in the relative abundance of materials among the pixels is necessary to be able to derive the endmembers or pure material constituent spectra. In most cases, the 1 km pixel size for the Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is too large to meet the variance criterion. A pointable high spatial and spectral resolution imaging spectrometer in orbit will be necessary to make the major next step in our understanding of the solid earth surface and its changing face.

Goetz, Alexander F. H.↗

NASA NTRS2001

An Approach to Application of Multispectral Sensors, using AVIRIS Data

High spatial resolution multispectral/hyperspectral sensors are being developed by private industry with science/research customers as end users. With an increasingly wide range of sensor choices, it is important for the remote sensing science community and commercial community alike to understand the trade-offs between ground sample distance (GSD), spectral resolution, and signal-to-noise ratio (SNR) in selecting a sensor that will best meet their needs. High spatial resolution hyperspectral imagery and super resolution multispectral charge-coupled device imagery can be used to develop prototypes of proposed data acquisition systems without building new systems or collecting large sets of additional data. By using these datasets to emulate proposed and existing systems, imaging systems may be optimized to meet customer needs in a virtual environment. This approach also enables one to determine, a priori, whether an existing dataset will be useful for a given application.

Warner, Amanda↗

NASA NTRS1994

Remote Sensing of Seasonal Leaf Area Index Across the Oregon Transect

Remotely sensed data acquired from four remote-sensing instruments on three different aircraft platforms over a transect of coniferous forest stands in Oregon were analyzed with respect to seasonal leaf area index (LAI). Data from the four instruments were corrected for the varying seasonal and geographic atmospheric conditions present along the transect. Strong logarithmic relationships were observed between seasonal maximum and minimum LAI and the simple ratio (SR) (near infrared/red reflectance) calculated from the broad-spectral-band Thematic Mapper Simulator (TMS), as well as from the narrow-spectral-band Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), the Compact Airborne Spectrographic Imager (CASI), and a Spectron SE590 spectro-radiometer (R(exp 2) = 0.82-0.97). The TMS SR reached an asymptote at an LAI of approx. 7-8. However, the SE590 and the CASI SR continued to increase up to the maximum LAI of 10.6. The variability of the relationship between the AVIRIS SR and LAI increased at stands with LAIs greater than 7, making a trend in the AVIRIS SR-LAI relationship at LAIs greater than 7 difficult to discern. The SRs of the coniferous forest stands measured by the narrow-spectral-band instruments were higher than they were from the broad-spectral-band TMS. This is attributed partially to the integration of the TMS over a broad wavelength region in the red and more strongly to calibration differences between the sensors. Seasonal TMS SR trends for four time periods for some of the stands deviated from the expected seasonal LAI trends, possibly because of smoke and very low sun angles during some of the acquisition periods. However, the expected SR differences for the seasonal minimum and maximum LAI were observed for all of the sensors for nearly all of the forest stands. This study, demonstrates that remotely, sensed data from both broad- and narrow spectral band instruments can provide estimates of LAI for use in forest ecosystems simulation models to estimate evapotranspiration, photosynthesis, canopy turnover, and net primary production over large areas.

Spanner, Michael↗

NASA NTRS1992

Using AVIRIS images to measure temporal trends in abundance of photosynthetic and nonphotosynthetic canopy components

The Jasper Ridge Biological Preserve, Stanford, California is a good example of hardwood rangeland ecosystems in California. Structurally, it is composed of a mosaic of serpentine grasslands, oak savannah, coastal chaparral, and mixed evergreen woodland, representing a broad cross-section of physiognomic classes. The Mediterranean climate produces an extended seasonal drought lasting throughout most of the growing season and has significant impact on the expression of divergent phenological patterns related to contrasting ecological strategies of these taxa. The region is well understood biologically due to the rich history of ecological research at the site. Thus, community characteristics, physiological characteristics, phenology, and temporal dynamics are reasonably well understood for many of the dominant species. Because of its proximity to NASA Ames Research Center, it has been subject to a large number of aircraft data acquisitions over many years. A more complete examination of this database would provide an opportunity to test current remote sensing hypotheses for measurement and detection of ecological attributes, particularly those involving canopy chemistry and physiology. Better definition of ecological rules might permit development of remotely sensed surrogate variables for biological properties that cannot be directly measured or measured with sufficient accuracy.

Ustin, Susan L.↗

NASA NTRS2016

Scientific and Technical Assistance for the Deployment of a Flexible Airborne Spectrometer System During C-MAPExp and COMEX: COMEX Version - 1.9T

The COMEX (CO2 and MEthane eXperiment) campaign supports the mission definition of CarbonSat and HyspIRI (Hyperspectral Infrared Imager) by providing representative airborne remote sensing data ‐ MAMAP (Methane Airborne MAPper) for CarbonSat; the Airborne Visual InfraRed Imaging Spectrometer (Classic & Next Generation) AVIRIS‐C/AVIRIS‐NG for HyspIRI ‐ as well as ground-based and airborne in‐situ data. The objectives of the COMEX campaign activities are (see Campaign Implementation Plan (RD‐4)): 1. Investigate spatial/spectral resolution trade‐offs for CH4 anomaly detection and flux inversion by comparison of MAMAP‐derived emission estimates with AVIRIS/AVIRIS‐NG derived data. 2. Evaluate sun‐glint observation geometry on CH4 retrievals for marine sources. 3. Characterize the effect of Surface Spectral Reflectance (SSR) heterogeneity on trace gas retrievals of CO2 and CH4 for medium and low‐resolution spectrometry. 4. Identify benefits from joint SWIR/TIR (ShortWave InfraRed/Thermal InfraRed ) data for trace gas detection and retrieval by comparison of MAMAP and AVIRIS/AVIRIS‐NG NIR/SWIR data with MAKO (Aerospace Corp.)TIR data. The ability to derive emission source strength for a range of strong emitting targets by remote sensing will be evaluated from combined AVIRIS‐NG and MAMAP data, adding significant value to the HyspIRI campaign AVIRIS‐NG dataset. The data will be used to quantify anomalies in atmospheric CO2 and CH4 from strong local greenhouse gas sources e.g. localized industrial complexes, landfills, etc. and to derive CO2 and CH4 emissions estimates from atmospheric gradient measurements. The original campaign concept was developed by University of Bremen and BRI. The COMEX campaign is funded bilaterally by NASA and ESA (European Space Agency). Whereas NASA funds the US part of the project via a contract with Dr. Ira Leifer, BRI (Bubbleology Research International), the contribution of MAMAP to the COMEX campaign is funded by ESA within the COMEX‐E project and NASA with respect to a 50 percent contribution to the flight-related costs of flying MAMAP on a US aircraft. The Data Acquisition Report (RD‐9) describes the instrumentation used, the measurements made by the team during the COMEX campaign in May/June 2014 and August/September 2014 in California, and an initial assessment of the data quality.

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