Where the Fire Burns, Sifting Through the Data
The occurrence of wildfires on our public lands is an ever increasing threat. Generally when we think of a wildfire the scene of a heavily timbered mountain landscape comes to mind, however today wildfires are reaching father into previously unaffected ecosystems including our own desert backyard.
According to the BLM’s records, prior to 2005, there is no documented occurrence of a wildfire in the Gold Butte region. In June of 2005, following heavy spring rains, there was a large wildfire in the Gold Butte region started by a lightning strike.
In my goal to implement better community stewardship of our public lands, I am working to better understand the wildfire events that have occurred in the Gold Butte region. I do this in the possibility of better management, from better understanding, of our desert landscape. Through a better understanding of our environment, we can better manage the devastating effects of another wildfire event on the desert ecosystem.
My goal is to build a model that will create a risk index for the Gold Butte region to predict the likelihood of where the next fire will start and spread. The first step in building this model is to understand the landscape of the area that has previously burned. I chose for my area of interest the Fork and Tramp fires. The BLM provides the geospatial data for the location of the burn areas.
The data that I was able to locate on the web for this area included elevation, vegetation, soils, geology, landforms, average rainfall by year, intermittent washes and roads. The next step is to clip all of this data to the perimeter of the burn area. After the data is clipped to the boundary of the fire I performed spatial analysis to calculate the percent area of each type of feature within the data to see if there is any correlation as to why the fire burned in the area that it did. The following are some of the results that I found.
There were two different vegetation datasets that I found so i used both to try and create the best model that I could.
There will be more information and data coming...