Title of article :
Synergy of VSWIR (0.4–2.5 μm) and MTIR (3.5–12.5 μm) data for post-fire assessments
Author/Authors :
Veraverbeke، نويسنده , , S. E. Hook، نويسنده , , S.J. and Harris، نويسنده , , S.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Abstract :
Post-fire effects assessments are crucial to evaluate the impact of fire on ecosystems. They are helpful in planning post-fire rehabilitation and useful for reducing uncertainties in current wildfire emission estimates. We have used MODIS/ASTER (MASTER) airborne simulator data over the 2011 Canyon fire in California, USA to evaluate the potential synergy between visible to short-wave infrared (VSWIR, 0.4–2.5 μm) and mid to thermal infrared (MTIR, 3.5–12.5 μm) data in a post-fire environment. We applied Multiple Endmember Spectral Mixture Analysis (MESMA) inputting five endmembers: char, green vegetation, non-photosynthetic vegetation (NPV), substrate and shadow. Results revealed that fractional cover estimates of char, NPV and substrate are 5–7% better when VSWIR–MTIR data were combined, compared to using only VSWIR data. Combined VSWIR–MTIR imagery will become available at pixel sizes smaller than 100 m with future satellite sensors, such as the Hyperspectral Infrared Imager (HyspIRI). The MESMA-derived char fractional cover was also shown to be strongly correlated with the Geo Composite Burn Index (GeoCBI, Radj2 = 0.82) and the percentage of black trees and shrubs (Radj2 = 0.66) measured in the field. SMA-derived char fractions provide quantitative abundance maps which should prove valuable for improving wildfire emission estimates by refining burning efficiency values.
Keywords :
Multiple Endmember Spectral Mixture Analysis (MESMA) , Wildfire emission , carbon , fire severity , Differenced Normalized Burn Ratio (dNBR) , char , Spectral unmixing , Burn severity , charcoal
Journal title :
Remote Sensing of Environment
Journal title :
Remote Sensing of Environment