JDJCSET | Earth and Environmental Sciences Poster Session
Quantifying Burn Severity using dNDVI and dNBR of the Dixie Fire
Academic Level at Time of Presentation
Senior
Major
EES/Geology
Minor
N/A
List all Project Mentors & Advisor(s)
Dr. Haluk Cetin
Presentation Format
Poster Presentation
Abstract/Description
Whenever people turn on the news, at some point during the year, California makes headlines for another wildfire sprawling across the state. Wildfires are typically a natural occurrence that opens the forest floor to more sunlight, providing nutrients for the soil and promoting vegetation growth. However, wildfires have been occurring more often in these ecosystems, particularly human-related incidents, potentially doing more harm than good. The purpose of this research was to observe vegetation before and after the Dixie Fire using proven remote sensing techniques, which included observing the difference in Normalized Difference Vegetation Index (dNDVI) and difference in Normalized Burn Ratio (dNBR), as both observe differences in the amount of vegetation in an area. By utilizing these techniques, the goal was to determine how accurately remotely sensed data matched the California Wildfire and Resilience Task Force’s (CAL FIRE) total area affected by the fire. Preliminary results showed that the remotely sensed data aligned with the officially collected data from CAL FIRE. Considering the utilization of this method proved to show similar results to field data, it can be used in the future to show total area affected by other natural disasters.
Fall Scholars Week 2022 Event
Earth and Environmental Sciences Poster Session
Quantifying Burn Severity using dNDVI and dNBR of the Dixie Fire
Whenever people turn on the news, at some point during the year, California makes headlines for another wildfire sprawling across the state. Wildfires are typically a natural occurrence that opens the forest floor to more sunlight, providing nutrients for the soil and promoting vegetation growth. However, wildfires have been occurring more often in these ecosystems, particularly human-related incidents, potentially doing more harm than good. The purpose of this research was to observe vegetation before and after the Dixie Fire using proven remote sensing techniques, which included observing the difference in Normalized Difference Vegetation Index (dNDVI) and difference in Normalized Burn Ratio (dNBR), as both observe differences in the amount of vegetation in an area. By utilizing these techniques, the goal was to determine how accurately remotely sensed data matched the California Wildfire and Resilience Task Force’s (CAL FIRE) total area affected by the fire. Preliminary results showed that the remotely sensed data aligned with the officially collected data from CAL FIRE. Considering the utilization of this method proved to show similar results to field data, it can be used in the future to show total area affected by other natural disasters.