This PDF file contains the front matter associated with SPIE Proceedings Volume 9104, including the Title Page, Copyright information, Table of Contents, Invited Panel Discussion, and Conference Committee listing.

The forest biome is vital to the health of the earth. Canada and the United States have a combined forest area of 4.68 Mkm². The monitoring of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of improved information products to land managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory (major forest species), forest health, foliar biochemistry, biomass, and aboveground carbon. Operationally there is a requirement for a mix of airborne and satellite approaches. This paper surveys some methods and results in hyperspectral sensing of forests and discusses the implications for space initiatives with hyperspectral sensing

Sysiphe is an airborne hyperspectral imaging system, result of a cooperation between France (Onera and DGA) and Norway (NEO and FFI). It is a unique system by its spatial sampling -0.5m with a 500m swath at a ground height of 2000m- combined with its wide spectral coverage -from 0.4μm to 11.5μm in the atmospheric transmission bands. Its infrared component, named Sieleters, consists in two high étendue imaging static Fourier transform spectrometers, one for the midwave infrared and one for the longwave infrared. These two imaging spectrometers have very close design, since both are made of a Michelson interferometer, a refractive imaging system, and a large IRFPA (1016x440 pixels). Moreover, both are cryogenic and mounted on their own stabilization platform which allows at once to actively control and independently measure the line of sigh. These data are useful to reconstruct and to georeference the spectral image from the raw interferometric images. Sysiphe first flight occurred in September, 2013.

This paper describes a design concept for wide swath hyperspectral imager. The challenge is to meet the requirement of good image quality and high precision registration from 400nm to 2500nm. A new type spherical prism imaging spectrometer is presented in the paper. The swath of system can reach 60 kilometer from a 600km sun-synchronous orbit with 30 meter ground sample distance (GSD). The optical system consists of a TMA objective and 2 30mm-slit spherical prism spectrometer operating both VNIR and SWIR. Key features of the design include (1) high signal to noise ratio for high efficiency of F-silica prism; (2) high precision band registration for same spectrometer operating from 400nm to 2500nm.

Hyperspectral Imaging is used in many applications to identify or analyze materials in a scene based on the materials’ spectral signatures. Unique features in the spectral signatures can span beyond the spectral range of the hyperspectral imager. Additionally, lighting conditions and other factors can adversely affect the quality of data. Expanding the spectral range of hyperspectral imaging systems can therefore improve the accuracy of object/material recognition/analysis by allowing the system to “see” more of the spectral signatures as well as expand the number of objects/materials in a scene that can be identified/analyzed. This is particularly important in applications where erroneous identification or analysis can result in substantial risk or cost. More and more users are using two (or more) hyperspectral imagers to obtain different spectral ranges for their applications. Very few are effectively combining the data from the different hyperspectral imagers because it would require the hyperspectral imagers to be operated under tightly controlled conditions and the process of pixel coregistration is a very tedious and problematic post-processing step. In addition, this post-processing step prevents the use of the combined data in real-time applications. This paper describes a co-boresighted Vis-NIR and SWIR hyperspectral imaging system which Headwall Photonics is currently developing. It integrates two hyperspectral imagers, each optimized for its respective spectral range, into a single system with real-time pixel co-registration resulting in a system capable of producing wide-spectrum hyperspectral images with high spectral resolution. Aside from enabling real-time wide spectrum applications, such a system significantly simplifies the data acquisition and analysis for the user.

Imaging spectrometers provide the unique combination of both spatially contiguous spectra and spectrally contiguous images of the Earth's surface that allows spatial mapping of these minerals. One of the successful applications of imaging spectrometers remote sensing identified was geological mapping and mineral exploration. A Light weight Airborne Imaging Spectrometer System (LAISS) has been developed in China. The hardware of the compact LAISS include a VNIR imaging spectrometer, a SWIR imaging spectrometer, a high resolution camera and a position and attitude device. The weight of the system is less than 20kg. The VNIR imaging spectrometer measures incoming radiation in 344 contiguous spectral channels in the 400–1000 nm wavelength range with spectral resolution of better than 5 nm and creates images of 464 pixels for a line of targets with a nominal instantaneous field of view (IFOV) of ~1 mrad. The SWIR imaging spectrometer measures incoming radiation in the 1000–2500 nm wavelength range with spectral resolution of better than 10 nm with a nominal instantaneous field of view (IFOV) of ~2 mrad. The 400 to 2500nm spectral range provides abundant information about many important Earth-surface minerals. A ground mineral scan experiment and an UAV carried flying experiment has been done. The experiment results show the LAISS have achieved relative high performance levels in terms of signal to noise ratio and image quality. The potential applications for light weight airborne imaging spectrometer system in mineral exploration are tremendous.

Short wave infrared (SWIR) spectral imaging systems are vital for Intelligence, Surveillance, and Reconnaissance (ISR) applications because of their abilities to autonomously detect targets and classify materials. Typically the spectral imagers are incapable of providing Full Motion Video (FMV) because of their reliance on line scanning. We enable FMV capability for a SWIR multi-spectral camera by creating a repeating pattern of 3x3 spectral filters on a staring focal plane array (FPA). In this paper we present the imagery from an FMV SWIR camera with nine discrete bands and discuss image processing algorithms necessary for its operation. The main task of image processing in this case is demosaicking of the spectral bands i.e. reconstructing full spectral images with original FPA resolution from spatially subsampled and incomplete spectral data acquired with the choice of filter array pattern. To the best of author's knowledge, the demosaicking algorithms for nine or more equally sampled bands have not been reported before. Moreover all existing algorithms developed for demosaicking visible color filter arrays with less than nine colors assume either certain relationship between the visible colors, which are not valid for SWIR imaging, or presence of one color band with higher sampling rate compared to the rest of the bands, which does not conform to our spectral filter pattern. We will discuss and present results for two novel approaches to demosaicking: interpolation using multi-band edge information and application of multi-frame super-resolution to a single frame resolution enhancement of multi-spectral spatially multiplexed images.

Traditional airborne environmental monitoring has frequently deployed hyperspectral imaging as a leading tool for characterizing and analyzing a scene’s critical spectrum-based signatures for applications in agriculture genomics and crop health, vegetation and mineral monitoring, and hazardous material detection. As the acceptance of hyperspectral evaluation grows in the airborne community, there has been a dramatic trend in moving the technology from use on midsize aircraft to Unmanned Aerial Systems (UAS). The use of UAS accomplishes a number of goals including the reduction in cost to run multiple seasonal evaluations over smaller but highly valuable land-areas, the ability to use frequent data collections to make rapid decisions on land management, and the improvement of spatial resolution by flying at lower altitudes (< 150 m). Despite this trend, there are several key parameters affecting the use of traditional hyperspectral instruments in UAS with payloads less than 0.5 kg (~1lb) where size, weight and power (SWaP) are critical to how high and how far a given UAS can fly. Additionally, on many of the light-weight UAS, users are frequently trying to capture data from one or more instruments to augment the hyperspectral data collection, thus reducing the amount of SWaP available to the hyperspectral instrumentation. The following manuscript will provide an analysis on a newly-developed miniaturized hyperspectral imaging platform that provides full hyperspectral resolution and traditional hyperspectral capabilities without sacrificing performance to accommodate the decreasing SWaP of smaller and smaller UAS platforms.

The mining industry is plagued with socioeconomic and safety roadblocks with not many solutions in the midst of a demanding market. As more and more geologic research using hyperspectral technology has been performed, along with an affordable price point for commercial use of hyperspectral technology, the benefits of hyperspectral imaging to the mining industry has become apparent. This study identifies the key areas of use for hyperspectral imaging in the mining industry through a case study of gypsum mine samples obtained from a mine in central Tuscany.