Daytime fire detection using airborne hyperspectral data

The shortwave infrared region of the electromagnetic spectrum, covering wavelengths from 1400 to 2500 nm, can include significant emitted radiance from fire. There have been relatively few evaluations of the utility of shortwave infrared remote sensing data, and in particular hyperspectral remote sensing data, for fire detection. We used an Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) scene acquired over the 2003 Simi Fire to identify the hyperspectral index that was able to most accurately detect pixels containing fire. All AVIRIS band combinations were used to calculate normalized difference indices, and kappa was used to compare classification ability of these indices for three different fire temperature ranges. The most accurate index was named the Hyperspectral Fire Detection Index (HFDI). The HFDI uses shortwave infrared bands centered at 2061 and 2429 nm. These bands are sensitive to atmospheric attenuation, so the impacts of variable elevation, solar zenith angle, and atmospheric water vapor concentration on HFDI were assessed using radiative transfer modeling. While varying these conditions did affect HFDI values, relative differences between background HFDI and HFDI for 1% fire pixel coverage were maintained. HFDI is most appropriate for detection of flaming combustion, and may miss lower temperature smoldering combustion at low percent pixel coverage due to low emitted radiance in the shortwave infrared. HFDI, two previously proposed hyperspectral fire detection indices, and a broadband shortwave infrared-based fire detection index were applied to AVIRIS scenes acquired over the 2007 Zaca Fire and 2008 Indians Fire. A qualitative comparison of the indices demonstrated that HFDI provides improved detection of fire with less variability in background index values. (C) 2009 Elsevier Inc. All rights reserved.