Developing a User-Friendly Tool for Determining and Mapping the Differenced Normalized Burn Ratio
Presentation Time: Fri, 04/28/2023 - 12:00
Keywords: wildfire, python, burn ratio, automate
When it comes to wildfire recovery efforts, time is of the essence. Analyses to plan restoration efforts need to be conducted within seven days of wildfire containment. This window ensures that the data collected is most reflective of postfire conditions. It is necessary for the satellite images to capture the near infrared and shortwave infrared reflectance values from the ground before vegetation begins to grow back. This project aims to create a user-friendly tool for analyzing burn severity of wildfires. The goal is to be able to automate these analyses so they can be used for post wildfire land rehabilitation. The difference between pre-fire and post-fire normalized burn ratio provides information regarding where the land was most and least damaged from a wildfire, helpful for informing land managers with post fire recovery efforts, if necessary. A tool developed in this project uses Landsat imagery from before and after the wildfire and runs it through a python script to automatically calculate the difference between pre-fire and post-fire normalized burn ratio and map it. From here, the tool can be applied to any wildfire that has imagery available from before it started and shortly after its containment. The results of this project are a python script to automate mapping the differenced normalized burn ratio that is customizable to be run on any computer with any data saved.
