Analytical Imaging and Geophysics LLC

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Analytical Imaging and Geophysics LLC

Boulder City, CO, United States
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Thompson D.R.,Jet Propulsion Laboratory | Boardman J.W.,Analytical Imaging and Geophysics LLC | Eastwood M.L.,Jet Propulsion Laboratory | Green R.O.,Jet Propulsion Laboratory
Optics Express | Year: 2017

The intrinsic spectral dimensionality indicates the observable degrees of freedom in Earth's solar-reflected light field, quantifying the diversity of spectral content accessible by visible and infrared remote sensing. The solar-reflected regime spans the 0.38-2.5 μm interval, and is captured by a wide range of current and planned instruments on both airborne and orbital platforms. To date there has been no systematic study of its spectral dimensionality as a function of space, time, and land cover. Here we report a multi-site, multi-year statistical survey by NASA's "Classic" Airborne Visible Near InfraRed Spectrometer (AVIRIS-C). AVIRIS-C measured large regions of California, USA, spanning wide latitudinal and elevation gradients containing all canonical MODIS land cover types. The spectral uniformity of the AVIRIS-C design enabled consistent in-scene assessment of measurement noise across acquisitions. The estimated dimensionality as a function of cover type ranged from the low 20s to the high 40s, and was approximately 50 for the combined dataset. This result indicates the high diversity of physical processes distinguishable by imaging spectrometers like AVIRIS-C for one region of the Earth. © 2017 Optical Society of America.


Dhingra D.,Brown University | Pieters C.M.,Brown University | Boardman J.W.,Analytical Imaging and Geophysics LLC | Head J.W.,Brown University | And 2 more authors.
Geophysical Research Letters | Year: 2011

Analysis of high resolution Moon Mineralogy Mapper (M3) data reveals the presence of a prominent Mg-spinel-rich lithology in the central peaks of Theophilus crater on the lunar nearside. Other peak-associated lithologies are comprised of plagioclase, olivine, and pyroxene-bearing materials. A consistent spatial association of Mg-spinel with mafic-free anorthosite is recognized. Documentation of Theophilus central peaks brings the global inventory of Mg-spinel-rich lithology to two widely separated occurrences, namely Theophilus on the lunar nearside and Moscoviense basin on the farside. The Theophilus crater target region lies on one of the inner rings of the Nectaris basin, indicating that the Mg-spinel-bearing lithology source was deep in the lunar crust. Copyright 2011 by the American Geophysical Union.


Boardman J.W.,Analytical Imaging and Geophysics LLC | Pieters C.M.,Brown University | Green R.O.,Jet Propulsion Laboratory | Lundeen S.R.,Jet Propulsion Laboratory | And 6 more authors.
Journal of Geophysical Research E: Planets | Year: 2011

The Moon Mineralogy Mapper (M3), a high-resolution, high-precision imaging spectrometer, flew on board India's Chandrayaan-1 Mission from October 2008 through August 2009. This paper describes some of the spatial sampling aspects of the instrument, the planned mission, and the mission as flown. We also outline the content and context of the resulting Level 1B spatial products that form part of the M3 archive. While designed and planned to operate for 2 years in a 100 km lunar orbit, M3 was able to meet its lunar coverage requirements despite the shortened mission; an increase of the orbit altitude to 200 km; and several relevant problems with spacecraft attitude, timing, and ephemeris. The unexpected spacecraft issues required us to invent a novel two-step approach for selenolocation. Leveraging newly available Lunar Reconnaissance Orbiter-Lunar Orbiter Laser Altimeter (LOLA) topography and an improved spacecraft ephemeris, we have created a method that permits us to bootstrap spacecraft attitude estimates from the image data themselves. This process performs a nonlinear optimization to honor a set of data-derived image-to-image tie points and image-to-LOLA control points. Error analysis of the final results suggests we have converged to a selenolocation result that has image-to-image root-mean-square (RMS) errors less than 200 m and image-to-LOLA RMS errors less than 450 m, despite using data-derived spacecraft attitude results. The Level 1B products include the lunar coordinates resulting from this inversion process and 10 relevant observational geometry parameters that fully characterize the ray tracing geometry on a pixel-by-pixel basis. Copyright © 2011 by the American Geophysical Union.


Besse S.,University of Maryland University College | Sunshine J.M.,University of Maryland University College | Staid M.I.,Planetary Science Institute | Petro N.E.,NASA | And 6 more authors.
Journal of Geophysical Research E: Planets | Year: 2011

Using the Moon Mineralogy Mapper(M3), we examine the Marius Hills volcanic complex for the first time from 0.46 to 2.97 m. The integrated band depth at 1 m separates the mare basalts on the plateau in two units: (1) a strong 1 m band unit of localized lava flows within the plateau that has similar olivine-rich signatures to those of the nearby Oceanus Procellarum and (2) a weaker 1 m band unit that characterizes most of the basalts of the plateau, which is interpreted as having a high-calcium pyroxene signature. Domes and cones within the complex belong to the high-calcium pyroxene plateau unit and are associated with the weakest 1 m band observed on the plateau. This difference could be the result of higher silica content, more opaque minerals, and/or a weaker olivine content of the magma. Finally, the floor of Marius crater has one of the strongest olivine-rich signatures of the entire Marius Hills complex. These compositional differences are indicative of the long and complex volcanic history of the region. The first episode started before the emplacement of the surrounding basalts of the plateau and produced the high-calcium pyroxene flows present on the plateau and their associated domes and cones. The second episode occurred concurrently or slightly after the emplacement of the adjacent Procellarum basalts and produced the olivine-rich basalts seen within the plateau, outside the plateau, and in Marius crater. If the olivine content of the lava flows increases with time, the olivine-rich region on the floor of Marius crater may represent one of the latest episodes of volcanism exposed on the Marius Hills complex. Copyright 2011 by the American Geophysical Union.


Besse S.,University of Maryland University College | Sunshine J.,University of Maryland University College | Staid M.,Planetary science Institute | Boardman J.,Analytical Imaging and Geophysics LLC | And 6 more authors.
Icarus | Year: 2013

Observations of the Moon obtained by the Moon Mineralogy Mapper (M3) instrument were acquired at various local viewing geometries. To compensate for this, a visible near-infrared photometric correction for the M3 observations of the lunar surface has been derived. Images are corrected to the standard geometry of 30° phase angle with an incidence of 30° and an emission of 0°. The photometric correction is optimized for highland materials but is also a good approximation for mare deposits. The results are compared with ground-based observations of the lunar surface to validate the absolute reflectance of the M3 observations. This photometric model has been used to produce the v1.0 Level 2 delivery of the entire set of M3 data to the Planetary Data System (PDS). The photometric correction uses local topography, in this case derived from an early version of the Lunar Orbiter Laser Altimeter data, to more accurately determine viewing geometry. As desired, this photometric correction removes most of the topography of the M3 measurements. In this paper, two additional improvements of the photometric modeling are discussed: (1) an extrapolated phase function long ward of 2500nm to avoid possible misinterpretation of spectra in the wavelength region that includes possible OH/H2O absorptions and (2) an empirical correction to remove a residual cross-track gradient in the data that likely is an uncorrected instrumental effect. New files for these two effects have been delivered to PDS and can be applied to the M3 observations. © 2012 Elsevier Inc.


Clark R.N.,U.S. Geological Survey | Pieters C.M.,Brown University | Green R.O.,Jet Propulsion Laboratory | Boardman J.W.,Analytical Imaging and Geophysics LLC | Petro N.E.,NASA
Journal of Geophysical Research E: Planets | Year: 2011

In the near-infrared from about 2 μm to beyond 3 μm, the light from the Moon is a combination of reflected sunlight and emitted thermal emission. There are multiple complexities in separating the two signals, including knowledge of the local solar incidence angle due to topography, phase angle dependencies, emissivity, and instrument calibration. Thermal emission adds to apparent reflectance, and because the emission's contribution increases over the reflected sunlight with increasing wavelength, absorption bands in the lunar reflectance spectra can be modified. In particular, the shape of the 2 μm pyroxene band can be distorted by thermal emission, changing spectrally determined pyroxene composition and abundance. Because of the thermal emission contribution, water and hydroxyl absorptions are reduced in strength, lowering apparent abundances. It is important to quantify and remove the thermal emission for these reasons. We developed a method for deriving the temperature and emissivity from spectra of the lunar surface and removing the thermal emission in the near infrared. The method is fast enough that it can be applied to imaging spectroscopy data on the Moon. Copyright © 2011 by the American Geophysical Union.


Ohtake M.,Japan Aerospace Exploration Agency | Pieters C.M.,Brown University | Isaacson P.,University of Hawaii at Manoa | Besse S.,European Space Agency | And 8 more authors.
Icarus | Year: 2013

Remote-sensing datasets obtained by each instrument aboard Selenological and Engineering Explorer (SELENE) and Chandrayaan-1 have not been compared directly, and the characteristics of each instrument's data, which may reflect the observation conditions of each instrument and/or residual error in instrument calibration, are unknown. This paper describes the basic characteristics of the data derived by each instrument, briefly describes the data-processing conversion from radiance to reflectance, and demonstrates what we can achieve by combining data obtained by different instruments on different missions (five remote-sensing instruments and an Earth-based telescope). The results clearly demonstrate that the spectral shapes of the instruments are comparable and thus enable us to estimate the composition of each geologic unit, although absolute reflectances differ slightly in some cases. © 2013 Elsevier Inc.


Asner G.P.,Carnegie Institution for Science | Knapp D.E.,Carnegie Institution for Science | Boardman J.,Carnegie Institution for Science | Boardman J.,Analytical Imaging and Geophysics LLC | And 6 more authors.
Remote Sensing of Environment | Year: 2012

The Carnegie Airborne Observatory (CAO) was developed to address a need for macroscale measurements that reveal the structural, functional and organismic composition of Earth's ecosystems. In 2011, we completed and launched the CAO-2 next generation Airborne Taxonomic Mapping Systems (AToMS), which includes a high-fidelity visible-to-shortwave infrared (VSWIR) imaging spectrometer (380-2510. nm), dual-laser waveform light detection and ranging (LiDAR) scanner, and high spatial resolution visible-to-near infrared (VNIR) imaging spectrometer (365-1052. nm). Here, we describe how multiple data streams from these sensors can be fused using hardware and software co-alignment and processing techniques. With these data streams, we quantitatively demonstrate that precision data fusion greatly increases the dimensionality of the ecological information derived from remote sensing. We compare the data dimensionality of two contrasting scenes - a built environment at Stanford University and a lowland tropical forest in Amazonia. Principal components analysis revealed 336 dimensions (degrees of freedom) in the Stanford case, and 218 dimensions in the Amazon. The Amazon case presents what could be the highest level of remotely sensed data dimensionality ever reported for a forested ecosystem. Simulated misalignment of data streams reduced the effective information content by up to 48%, highlighting the critical role of achieving high precision when undertaking multi-sensor fusion. The instrumentation and methods described here are a pathfinder for future airborne applications undertaken by the National Ecological Observatory Network (NEON) and other organizations. © 2012 Elsevier Inc.


Boardman J.,Analytical Imaging and Geophysics LLC | Cervantes D.,Jet Propulsion Laboratory | Frazier W.,Jet Propulsion Laboratory
Advances in the Astronautical Sciences | Year: 2016

Traditional space remote sensing systems invest large amounts of resources into ensuring that the space-based GN&C hardware and software supports essentially open-loop geolocation of imagery, based on precision attitude and ephemeris data, and numerous biases and correction factors, many of which must be constantly re-evaluated (e.g. alignments). Ground-based geolocation is typically assumed to be too risky, slow, and/or expensive to be considered anything but "Plan B", or an ancillary upgrade. However, with the ever-growing processing capabilities, current available ground software packages have made it possible to perform image orthorectification using only the image data (seeded with relatively course GN&C information), leveraging various feature recognition algorithms as an operationally-viable solution. Such algorithms have been developed of necessity for certain particular mission classes (e.g. small bodies and hosted payloads), and also have become commercially available for Earth applications. In this paper we evaluate the performance available from representative algorithms, and consider the implied system architecture trades of potentially foregoing the traditional high-performance GN&C solution altogether, in favor of currently- available ground processing. This can then become a mission-enabling strategy for low-cost Earth remote sensing missions such as NASA's Earth Ventures class.


Boardman J.W.,Analytical Imaging and Geophysics LLC | Kruse F.A.,Naval Postgraduate School, Monterey
IEEE Transactions on Geoscience and Remote Sensing | Year: 2011

Imaging spectrometers collect unique data sets that are simultaneously a stack of spectral images and a spectrum for each image pixel. While these data can be analyzed using approaches designed for multispectral images, or alternatively by looking at individual spectra, neither of these takes full advantage of the dimensionality of the data. Imaging spectrometer spectral radiance data or derived apparent surface reflectance data can be cast as a scattering of points in an n-dimensional Euclidean space, where n is the number of spectral channels and all axes of the n-space are mutually orthogonal. Every pixel in the data set then has a point associated with it in the n- d space, with its Cartesian coordinates defined by the values in each spectral channel. Given n-dimensional data, convex and affine geometry concepts can be used to identify the purest pixels in a given scene (the endmembers). N-dimensional visualization techniques permit human interpretation of all spectral information of all image pixels simultaneously and projection of the endmembers back to their locations in the imagery and to their spectral signatures. Once specific spectral endmembers are defined, partial linear unmixing (mixture-tuned matched filtering or MTMF) can be used to spectrally unmix the data and to accurately map the apparent abundance of a known target material in the presence of a composite background. MTMF incorporates the best attributes of matched filtering but extends that technique using the linear mixed-pixel model, thus leading to high selectivity between similar materials and minimizing classification and mapping errors for analysis of imaging spectrometer data. © 2006 IEEE.

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