Airborne hyperspectral data have been available to researchers since the early 1980s and their use for geologic applications is well documented. The launch of the National Aeronautics and Space Administration Earth Observing 1 Hyperion sensor in November 2000 marked the establishment of a test bed for spaceborne hyperspectral capabilities. Hyperion covers the 0.4–2.5m range with 242 spectral ba...

Satellite-based hyperspectral imaging became a reality in November 2000 with the successful launch and operation of the Hyperion system on board the EO-1 platform. Hyperion is a pushbroom imager with 220 spectral bands in the 400-2500 nm wavelength range, a 30 meter pixel size and a 7.5 km swath. Pre-launch characterization of Hyperion measured low signal to noise (SNR<40:1) for the geologicall...

We present the design and initial implementation of Hyperion, an environment for the high-performance execution of Java programs. Hy-perion supports high performance by utilizing a Java-bytecode-to-C translator and by supporting parallel execution via the distribution of Java threads across the multiple processors of a cluster of Linux machines. The Hyperion run-time system implements the Java ...

Hyperion, a hyperspectral sensor, and the Advanced Land Imager (ALI) are carried on NASA’s EO-1 satellite. The Evaluation and Validation of EO-1 for Sustainable Development (EVEOSD) is our project supporting the EO-1 mission. With 10% of the world’s forests and the second largest country by area in the world, Canada has a natural requirement for effective monitoring of its forests. Eight test s...

The Aliso Canyon gas storage facility near Porter Ranch, California, produced a large accidental CH4 release from October 2015 to February 2016. The Hyperion imaging spectrometer on board the EO-1 satellite successfully detected this event, achieving the first orbital attribution of CH4 to a single anthropogenic superemitter. Hyperion measured shortwave infrared signatures of CH4 near 2.3 μm at...

Parameters derived from remote sensing that can be used to assess fire danger include surface reflectance, live and dead biomass, canopy water content, species composition, and fuel state. Spectral bands and wavelength locations of traditional multispectral data make assessment of fire danger in Mediterranean shrublands difficult, although fire danger parameters have been derived from Airborne ...