The algorithm to calculate Greenhouse Gas (GHG) emissions from savanna fires relies upon a number of variables from the classification of satellite based optical imagery. The algorithm variables require continued refinement. Fire severity mapping will increase the accuracy of the spatial distribution of fuel consumed. Fire severity is the post-fire effect of fire on the vegetation. The fire severity mapping algorithm developed in this study correlated helicopter-based spectra collected over a site using a hand held spectrometer and ground data describing the fire severity within the spectrometer field of view. The differenced Normalized Burn Ratio (?NBR) quite clearly distinguished between severe and not-severe fires (r2 = 0.94). However, further discrimination into three or more classes required the development of other indices incorporating the region of the spectrum represented by MODIS band 6 (1628-1652 nm). This poses problems operationally as band 6 on Aqua is dysfunctional thus halving the available data.
|Number of pages||4|
|Publication status||Published - 2011|
|Event||International Symposium on Remote Sensing of Environment (ISRSE 2011 34th): The GEOSS Era: Towards Operational Environmental Monitoring - Sydney, Sydney, NSW, Australia|
Duration: 10 Apr 2011 → 15 Apr 2011
Conference number: 2011 (34th)
|Conference||International Symposium on Remote Sensing of Environment (ISRSE 2011 34th)|
|Period||10/04/11 → 15/04/11|