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Boardman, J. W.

Publications and source records attributed to Boardman, J. W..

A New Lunar Globe as Seen by the Moon Mineralogy Mapper: Image Coverage Spectral Dimensionality and Statistical Anomalies

The Moon Mineralogy Mapper (M3), a NASA Discovery Mission of Opportunity, was launched October 22, 2008 from Shriharikota in India on board the Indian ISRO Chandrayaan- 1 spacecraft for a nominal two-year mission in a 100-km polar lunar orbit. M3 is a high-fidelity imaging spectrometer with 260 spectral bands in Target Mode and 85 spectral bands in a reduced-resolution Global Mode. Target Mode pixel sizes are nominally 70 meters and Global pixels (binned 2 by 2) are 140 meters, from the planned 100-km orbit. The mission was cut short, just before halfway, in August, 2009 when the spacecraft ceased operations. Despite the abbreviated mission and numerous technical and scientific challenges during the flight, M3 was able to cover more than 95% of the Moon in Global Mode. These data, presented and analyzed here as a global whole, are revolutionizing our understanding of the Moon. Already, numerous discoveries relating to volatiles and unexpected mineralogy have been published [1], [2], [3]. The rich spectral and spatial information content of the M3 data indicates that many more discoveries and an improved understanding of the mineralogy, geology, photometry, thermal regime and volatile status of our nearest neighbor are forthcoming from these data. Sadly, only minimal high-resolution Target Mode images were acquired, as these were to be the focus of the second half of the mission. This abstract gives the reader a global overview of all the M3 data that were collected and an introduction to their rich spectral character and complexity. We employ a Principal Components statistical method to assess the underlying dimensionality of the Moon as a whole, as seen by M3, and to identify numerous areas that are low-probability targets and thus of potential interest to selenologists.

Boardman, J. W.↗

Geologic Validation of EO-1 Hyperion using AVIRIS

Over the last few years, the field of imaging spectrometry has grown rapidly as new instruments and analysis techniques have been developed. The launch of Hyperion as part of NASA's EO-1 program represents a significant landmark in the progression of the technology; the first spaceborne imaging spectrometry system. AIG, in cooperation with CSIRO, is evaluating, validating, and demonstrating use of EO-1 Hyperion hyperspectral data for geologic applications. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) plays a pivotal role in this effort. This manuscript describes the geologic test sites being used and progress on preparing 'ground truth' for anticipated Hyperion data collects using AVIRIS data. Preliminary findings are extrapolated to predict the effect of instrument characteristics and performance on geologic mapping using Hyperion.

Kruse, F. A.↗

The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data

The Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, has developed a prototype interactive software system called the Spectral Image Processing System (SIPS) using IDL (the Interactive Data Language) on UNIX-based workstations. SIPS is designed to take advantage of the combination of high spectral resolution and spatial data presentation unique to imaging spectrometers. It streamlines analysis of these data by allowing scientists to rapidly interact with entire datasets. SIPS provides visualization tools for rapid exploratory analysis and numerical tools for quantitative modeling. The user interface is X-Windows-based, user friendly, and provides 'point and click' operation. SIPS is being used for multidisciplinary research concentrating on use of physically based analysis methods to enhance scientific results from imaging spectrometer data. The objective of this continuing effort is to develop operational techniques for quantitative analysis of imaging spectrometer data and to make them available to the scientific community prior to the launch of imaging spectrometer satellite systems such as the Earth Observing System (EOS) High Resolution Imaging Spectrometer (HIRIS).

Kruse, F. A.↗

The Spectral Image Processing System (SIPS): Software for integrated analysis of AVIRIS data

The Spectral Image Processing System (SIPS) is a software package developed by the Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, in response to a perceived need to provide integrated tools for analysis of imaging spectrometer data both spectrally and spatially. SIPS was specifically designed to deal with data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the High Resolution Imaging Spectrometer (HIRIS), but was tested with other datasets including the Geophysical and Environmental Research Imaging Spectrometer (GERIS), GEOSCAN images, and Landsat TM. SIPS was developed using the 'Interactive Data Language' (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system to provide rapid analysis of entire imaging spectrometer datasets. SIPS allows analysis of single or multiple imaging spectrometer data segments at full spatial and spectral resolution. It also allows visualization and interactive analysis of image cubes derived from quantitative analysis procedures such as absorption band characterization and spectral unmixing. SIPS consists of three modules: SIPS Utilities, SIPS_View, and SIPS Analysis. SIPS version 1.1 is described below.

Kruse, F. A.↗

Mineral mapping at Cuprite, Nevada with a 63-channel imaging spectrometer

Geophysical and Environmental Research Imaging Spectrometer (GERIS) 63-channel scanner data covering the spectral region 0.4 to 2.5 microns were analyzed for the Cuprite mining district, Esmeralda and Nye Counties, Nevada. Individual and spatially averaged spectra extracted from the GERIS data were used to identify the minerals alunite, kaolinite, buddingtonite, and hematite by their spectral characteristics. The images were classified in the spectral domain to produce color-coded image maps of mineral distribution that clearly show the zoned nature of the hydrothermal system. Comparison of the thematic mineral maps with existing geologic and alteration maps demonstrates the utility of imaging spectrometers for producing detailed maps for mineral exploration.

Kruse, F. A.↗