This was a map developed during my Internship with the United States Geological Survey during the Summer of 2012. This map was developed using a batch toolset written using python scripting.
The workflow to create this particular map was a 5 step process as follows
Step 1: Obtain DEM of the test site and digitize boundary where control fire was located.
Steps 2, 3, and 4: Run the batched toolsets in order to calculate pre-fire and post-fire Normalized Burn Ratios (NBR), and then subsequently create a dNBR or the difference between the pre/post fire heat imagery.
Step 5: Join the Land Cover and dNBR imagery in order to create the map seen here. Each land cover was assigned a specific value based on the expected propensity of that coverage to burn in a wildfire. The dNBR image was also reclassified in a similar manner, and then a python scripted equation then calculated the final "Burn Severity Index" value. The values ranged from 1 to 7 (Light Green=1, Red=7) which were interpreted as how severe the landscape had changed pre and post fire.
More about the Monitoring Trends In Burn Severity (MTBS) here: MTBS
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