This PDF file contains the front matter associated with SPIE Proceedings Volume 8158, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

On March 11, 2011, the magnitude 9 Tohoku earthquake and resulting tsunami struck off the coast of Japan. An estimated over 400,000 persons were displaced from their homes and the damage to the coastline and nearby urban areas was extensive. Additionally, the combined effects of the earthquake and tsunami caused damage to the Fukushima Dai'ichi Nuclear Power Station. As part of the International Charter "Space and Major Disasters", the US Geological Survey coordinated a volunteer effort to aid in the response to the disaster. The goal of the project was to produce maps derived from civilian (NASA Landsat and ASTER) and commercially available (DigitalGlobe and GeoEye), high resolution satellite imagery to be delivered to the Japanese authorities. RIT, as part of our Information Products Laboratory for Emergency Response (IPLER) program, was one of the organizations involved in this effort. This paper describes the timeline of the response, the challenges faced in this effort, the workflow developed, and the products that were distributed. Lessons learned from the response will also be described to aid the remote sensing community in preparing for responses to future natural disasters.

This paper describes a design concept for a Landsat-class imaging spectrometer. The challenge is to match the Landsat data parameters, including a 185 Km swath and a 30 meter ground sample distance (GSD) from a 705 Km sun-synchronous orbit with a sensor that has contiguous spectral coverage of the solar reflected spectrum (400 to 2500 nm). The result is a remote sensing satellite that provides global access imaging spectrometer data at moderate spatial resolution. Key design trades exist for the spectrometer, focal plane array, dispersive element, and calibrator. Recent developments in large format imaging spectrometers at Raytheon are presented in support of a monolithic spectrometer approach. Features of the design include (1) high signal-to-noise ratio, (2) well-corrected spectral fidelity across a 6,000 pixel push-broom field-of-view, (3) straightforward calibration of the data to units of absolute spectral radiance, and (4) real-time simulation of Thematic Mapper bands, vegetation indices, and water vapor maps for direct continuous downlink.

Recent trends in focal plane array (FPA) technology have led naturally to the development of very large format remote sensors that require optically fast, wide field-of-view (FOV) imaging optics. Systems that cover broad spectral ranges, such as multispectral imagers (MSI) and hyperspectral imagers (HSI), require reflective optics to provide aberration and distortion control without the complication of wavelength dependent errors induced by powered refractive elements. These large format systems require even wider fields-of-view than offered by the conventional three-mirror anastigmat (TMA) and four-mirror anastigmat (4MA) designs. Recently, Raytheon has demonstrated in hardware the first-ever aligned and tested five-mirror anastigmat (5MA) imager. The 5MA was designed with an F/3.0 optical speed and a 36 degree cross-scan FOV for use with a large format imaging spectrometer. The 5MA imager has useful features such as: (1) a real entrance pupil to support a full-aperture calibrator or a small scan mirror, (2) an intermediate image for stray light control, and (3) a real exit pupil for optimal cold-shielding in infrared applications. A computer-aided alignment method was used to align the 5MA imager with a final target of balanced wavefront error (WFE) across the full 36 deg FOV. This paper discusses the design and development of the first-ever 5MA imager and some potential air- and space-borne remote sensing applications.

Coherent anti-Stokes Raman scattering (CARS) microscopy is a powerful technique to image the chemical composition of complex samples in biophysics, biology and materials science. CARS is a four-wave mixing process. The application of a spectrally narrow pump beam and a spectrally wide Stokes beam excites multiple Raman transitions, which are probed by a probe beam. This generates a coherent directional CARS signal with several orders of magnitude higher intensity relative to spontaneous Raman scattering. Recent advances in the development of ultrafast lasers, as well as photonic crystal fibers (PCF), enable multiplex CARS. In this study, we employed two scanning imaging methods. In one, the detection is performed by a photo-multiplier tube (PMT) attached to the spectrometer. The acquisition of a series of images, while tuning the wavelengths between images, allows for subsequent reconstruction of spectra at each image point. The second method detects CARS spectrum in each point by a cooled coupled charged detector (CCD) camera. Coupled with point-by-point scanning, it allows for a hyperspectral microscopic imaging. We applied this CARS imaging system to study biological samples such as oocytes.

Instead of outsourcing the whole FORMOSAT-2 satellite to a foreign prime contractor, the National Space Organization in Taiwan is stepping ahead to take the full responsibility of consolidating self-reliant space technology capabilities. A newly initiated program FORMOSAT-5 satellite, not only to build a heritage design of a spacecraft bus but also, selfreliantly, to leap a big step toward Remote Sensing Instrument payload development, is sailing on its voyage. Among the payload development effort, an integrated circuit of the kind Complementary Metal Oxide Semiconductor instead of Charge-coupled Device is chosen as the image sensor playing the lead role for the instrument. Despite the foreseen technical concerns, management issues over scheduling and documentation are constantly emerging owing to the payload development underwent is collaborated by several domestic industries and research centers. Regardless of challenges we may confront with, a carefully planned strategy especially emphasizing on the product realization processes is considered, discussed, and implemented.

One of the fundamental challenges for a hyperspectral imaging system is the detection and discrimination of subpixel objects in background clutter. The background surrounding the object, which acts as interference, provides the major obstacle to successful detection and discrimination. In many applications we look for a single signature and discrimination among different signatures is not required. However, there are important applications where we are interested for multiple signatures. In these cases, the use of spectral discrimination algorithms is both necessary and valuable. In this paper, we develop an approach to spectral discrimination based on the adaptive cosine estimation (ACE) algorithm. The basic idea is to jointly exploit the detection statistics from the various signatures and set a common threshold that ensures larger separation between signatures of interest and background. The operation of the proposed detection-discrimination approach is illustrated using real-world hyperspectral imaging data.

It is well known that in multi- and hyperspectral imaging, the spatial coregistration of bands is important for the quality of image data. In practice, all spectral imaging sensors exhibit some degree of coregistration error, so that in any given pixel, different bands have a somewhat different "footprint" in the scene. Such coregistration errors may be in the form of differences in the position, size and shape of the spatial responsivity distribution, here termed pixel response function (PRF). There appears to be no standardized way to quantify the combined effect of these errors. This paper proposes a common metric for different types of coregistration error. Basically, the metric is the integrated difference between the PRFs of two bands in a given pixel. It is shown that under reasonable assumptions, this metric reflects the worst-case error in the signal resulting from coregistration errors between the two bands. To specify the coregistration of multiple bands, or in multiple pixels, an aggregate metric can be defined. The metric may be used for design optimization and should also be experimentally measurable. Extension to spectral and temporal coregistration is briefly discussed. The metric is proposed as a standardized way to report the coregistration performance of spectral image sensors.

We demonstrate a visible and near-infrared prototype pushbroom hyperspectral imager for Earth climate studies that is capable of using direct solar viewing for on-orbit cross calibration and degradation tracking. Direct calibration to solar spectral irradiances allow the Earth-viewing instrument to achieve required climate-driven absolute radiometric accuracies of <0.2% (1σ). A solar calibration requires viewing scenes having radiances 10⁵ higher than typical Earth scenes. To facilitate this calibration, the instrument features an attenuation system that uses an optimized combination of different precision aperture sizes, neutral density filters, and variable integration timing for Earth and solar viewing. The optical system consists of a three-mirror anastigmat telescope and an Offner spectrometer. The as-built system has a 12.2° cross track field of view with 3 arcmin spatial resolution and covers a 350-1050 nm spectral range with 10 nm resolution. A polarization compensated configuration using the Offner in an out of plane alignment is demonstrated as a viable approach to minimizing polarization sensitivity. The mechanical design takes advantage of relaxed tolerances in the optical design by using rigid, non-adjustable diamond-turned tabs for optical mount locating surfaces. We show that this approach achieves the required optical performance. A prototype spaceflight unit is also demonstrated to prove the applicability of these solar cross calibration methods to on-orbit environments. This unit is evaluated for optical performance prior to and after GEVS shake, thermal vacuum, and lifecycle tests.

The Atmospheric Infrared Sounder (AIRS) on NASA's Earth Observing System Aqua spacecraft was launched in May of 2002 and acquires hyperspectral infrared spectra used to generate a wide range of atmospheric products including temperature, water vapor, and trace gas species including carbon dioxide. Here we present monthly representations of global concentrations of mid-tropospheric carbon dioxide produced from 8 years of data obtained by AIRS between the years of 2003 and 2010. We define them as "representations" rather than "climatologies" to reflect that the files are produced over a relatively short time period and represent summaries of the Level 3 data. Finally, they have not yet been independently validated. The representations have a horizontal resolution of 2.0° × 2.5° (Latitude × Longitude) and faithfully reproduce the original 8 years of monthly L3 CO₂ concentrations with a standard deviation of 1.48 ppm and less than 2% outliers. The representations are intended for use in studies of the global general circulation of CO₂ and identification of anomalies in CO₂ typically associated with atmospheric transport. The seasonal variability and trend found in the AIRS CO₂ data are discussed.

The National Ecological Observatory Network (NEON) will be the first observatory network of its kind designed to detect and enable forecasting of ecological change at continental scales over multiple decades. NEON will collect data at sites distributed at 20 ecoclimatic domains across the United States on the impacts of climate change, land use change, and invasive species on natural resources and biodiversity. The NEON Airborne Observation Platform (AOP) is an aircraft platform carrying remote sensing instrumentation designed to achieve sub-meter to meter scale ground resolution, bridging the scales from organisms and individual stands to satellite-based remote sensing. AOP instrumentation consists of a VIS/SWIR imaging spectrometer, a scanning small-footprint waveform LiDAR, and a high resolution airborne digital camera. AOP data will provide quantitative information on land use change and changes in ecological structure and chemistry including the presence and effects of invasive species. A Pathfinder Flight Campaign was conducted over a two week period during late August to early September 2010 in order to collect representative AOP data over one NEON domain site. NASA JPL flew the AVIRIS imaging spectrometer and NCALM flew an Optech Gemini waveform LiDAR over the University of Florida Ordway-Swisher Biological Station and Donaldson tree plantation near Gainesville Florida. The pathfinder data are discussed in detail along with how the data are being used for early algorithm and product development prototyping activities. The data collected during the campaign and prototype products are openly available to scientists to become more familiar with representative NEON AOP data.

The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principles-based synthetic image generation model, developed at the Rochester Institute of Technology (RIT) over the past 20+ years. By calculating the sensor reaching radiance between the bandpass 0.2 to 20μm, it produces multi or hyperspectral remote sensing images. By integrating independent first principles based sub-models, such as MODTRAN, DIRSIG generates a representation of what a sensor would see with high radiometric fidelity. Currently, DIRSIG only models spatial/spectral synthetic images. In order to detect temporal changes in a process within the scene, a process model, which links the observable signatures of interest temporally, should be developed and incorporated into DIRSIG. These process models could be external time-dependent sub-models or pre-defined process models by the users to predict the state of the objects in the scene at a specific time. In this paper, a notional system of two tanks connected by a pipe is built, with hot water coming into tank A through a second pipe and with cooled water released from tank B through a third pipe. This is a simple hydrodynamic & thermodynamic model, controlled by the state of valves in the scenario. The initial temperature and height of the water in the two tanks are pre-defined by the user. Surface temperatures as a function of time are then predicted and captured as characterization maps, which are then mapped onto DIRSIG geometry using UV mapping technique. Finally, a spatial-spectral-temporal synthetic remote sensing image is produced.

In a previous paper in this series, we described how The Aerospace Corporation's Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) tool may be used to model space and airborne imaging systems operating in the visible to near-infrared (VISNIR). PICASSO is a systems-level tool, representative of a class of such tools used throughout the remote sensing community. It is capable of modeling systems over a wide range of fidelity, anywhere from conceptual design level (where it can serve as an integral part of the systems engineering process) to as-built hardware (where it can serve as part of the verification process). In the present paper, we extend the discussion of PICASSO to the modeling of Thermal Infrared (TIR) remote sensing systems, presenting the equations and methods necessary to modeling in that regime.

Imaging spectrometers require precise adjustments, in some cases at the sub-micrometer level, in order to achieve a uniform response over both the spectral and spatial dimensions. We describe a set of measurement techniques and their corresponding alignment adjustments to achieve the 95% or higher uniformity specifications required for Earthobserving imaging spectrometers. The methods are illustrated with measurements from the Next Generation Imaging Spectrometer system that has been built at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

We present the optical design and performance of the Ultra-Compact Imaging Spectrometer (UCIS) currently under development at Caltech's Jet Propulsion Laboratory. The new instrument demonstrates a low optical bench mass of less than 0.5 kg and compact size that enables Mars Rover or other in situ planetary applications. UCIS is an F/4, wide field (30°) design, covering the spectral range 600-2600 nm and is enabled by a simple all aluminum two-mirror telescope and Offner spectrometer. We discuss here the optical design and alignment method that enables this compact and low mass imaging spectrometer and demonstrate successful spectrometer alignment with smile and keystone levels at 2-3% of a pixel width.

The Deepwater Horizon oil spill covered a very large geographical area in the Gulf of Mexico creating potentially serious environmental impacts on both marine life and the coastal shorelines. Knowing the oil's areal extent and thickness as well as denoting different categories of the oil's physical state is important for assessing these impacts. High spectral resolution data in hyperspectral imagery (HSI) sensors such as Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) provide a valuable source of information that can be used for analysis by semi-automatic methods for tracking an oil spill's areal extent, oil thickness, and oil categories. However, the spectral behavior of oil in water is inherently a highly non-linear and variable phenomenon that changes depending on oil thickness and oil/water ratios. For certain oil thicknesses there are well-defined absorption features, whereas for very thin films sometimes there are almost no observable features. Feature-based imaging spectroscopy methods are particularly effective at classifying materials that exhibit specific well-defined spectral absorption features. Statistical methods are effective at classifying materials with spectra that exhibit a considerable amount of variability and that do not necessarily exhibit well-defined spectral absorption features. This study investigates feature-based and statistical methods for analyzing oil spills using hyperspectral imagery. The appropriate use of each approach is investigated and a combined feature-based and statistical method is proposed.

The use of a hyperspectral imaging system for the detection of gases has been investigated, and algorithms have been developed for various applications. Of particular interest here is the ability to use these algorithms in the detection of the wake disturbances trailing an aircraft. A dataset of long wave infrared (LWIR) hyperspectral datacubes taken with a Telops Hyper-Cam at Hartsfield-Jackson International Airport in Atlanta, Georgia is investigated. The methodology presented here assumes that the aircraft engine exhaust gases will become entrained in wake vortices that develop; therefore, if the exhaust can be detected upon exiting the engines, it can be followed through subsequent datacubes until the vortex disturbance is detected. Gases known to exist in aircraft exhaust are modeled, and the Adaptive Coherence/Cosine Estimator (ACE) is used to search for these gases. Although wake vortices have not been found in the data, an unknown disturbance following the passage of the aircraft has been discovered.

A point-and-shoot, passive remote sensing technology is highly desired to accurately monitor the combustion efficiency (CE) of petrochemical flares. A Phase II DOE-funded SBIR effort is being led by Spectral Sciences, Inc. to develop the methodologies needed to enable remote CE measurements via spectral remote sensing. Part of this effort entails standing up a laboratory-scale flare measurement laboratory to develop and validate CE measurements. This paper presents an overview and summarizes current progress of the Air Force Institute of Technology's (AFIT) contribution to this multi-organization, two-year effort. As a first step, a Telops Hyper-Cam longwave infrared (LWIR, 750-1300cm^-1 or 7.7-13.3μm) imaging Fourier-transformspectrometer (IFTS) is used to examine a laminar, calibration flame produced by a Hencken burner. Ethylene and propane were combusted under several different fuel/air mixing ratios. For each event, 300 hyperspectral datacubes were collected on a 172(W)×200(H) pixel window at a 1.5cm^-1 spectral resolution. Each pixel had approximately a 1.5×1.5mm² instantaneous field-of-view (IFOV). Structured emission is evident throughout the combustion region with several lines arising from H₂O; other lines have not yet been assigned. These first known IFTS measurements of a laminar Hencken-burner flame are presented along with some preliminary analysis. While the laminar flame appears stationary to the eye, significant flame flicker at a fundamental frequency of 17Hz was observed in the LWIR, and this is expected to complicate spectral interpretation for species concentrations and temperature retrieval. Changes to the fuel-air ratio (FAR) produced sizable changes in spectral intensity. Combustion spectra of ethylene and propane corresponding to ideal FAR were nearly identical.

The performance of a face recognition system degrades when the expression in the probe set is different from the expression in the gallery set. Previous studies use either spatial or spectral information to address this problem. In this paper, we propose an algorithm that uses spatial and spectral information for expression-invariant face recognition. The algorithm uses a set of 3D Gabor filters to exploit spatial and spectral correlations, and a principal-component analysis (PCA) to model expression variation. We demonstrate the effectiveness of the algorithm on a database of 200 subjects.

A prototype R-G-B imaging system for mapping of skin hemoglobin distribution has been designed and tested. Device basically consists of a commercial RGB sensor (CMOS, max. frame rate 87 fps for VGA resolution), RGB LED ringlight illuminator and orthogonally orientated polarizers for reducing specular reflectance. The system was examined for monitoring of hemoglobin concentration changes during specific provocations - arterial/venous occlusions and heat test. Hemoglobin distribution maps of several skin malformations were obtained, as well.