Infrared imaging spectrometers are used to map and characterize wildland fire based on their sensitivity to fire-emitted thermal radiation and ability to resolve spectral emission or absorption features. There is a general paucity of research on the use of space-borne imaging spectroscopy to study active fires in the North American boreal forest. We used hyperspectral data acquired by the Hyperion sensor on the EO-1 satellite over three wildfires in Alaska's boreal forest to evaluate three fire detection methods: a metric to detect an emission feature from potassium emitted by biomass burning; a continuum-interpolated band ratio (CIBR) that measures the depth of a carbon dioxide absorption line at 2010 nm; and the Hyperspectral Fire Detection Index (HFDI), which is a normalized difference index based on spectral radiance in the short-wave infrared range. We found that a modified version of the HFDI produces a well-defined map of the active fire areas. The CO2 CIBR, though affected by sensor noise and smoke, contributes a slight improvement to the fire detection performance when combined with HFDI-type indices. In contrast, detecting a fire signal from potassium emission was not reliably possible in a practically useful way. We furthermore retrieved fire temperatures by modeling the at-sensor radiance as a linear mixture of two emitted and two reflected spectral radiance endmembers. High-temperature fire areas (the high-intensity fire front, modeled at 800–900 K) and low-temperature combustion (residual fire at 500-600 K), were mapped. High-temperature burning areas as small as half a percent of a Hyperion pixel (approx. 5 m2) were detectable. These techniques are of potential interest for fire characterization in the boreal areas of the circumpolar North using current and future satellite-borne imaging spectrometers.