Authors: James Brenton, Tiffany Keeton, Katelyn Salem, Nathan Bledsoe, JuliÌÁn GonzÌÁlez-Otoya, AndrÌ©s Marmolejo
Mentors/Advisors (affiliation): Dr. Jeff Luvall (Marshall Space Flight Center, Global Hydrology and Climate Center), Dr. Max Moreno Madri̱ÌÁn (NASA SERVIR), Mr. Victor Hugo Ramos (Wildlife Conservation Society)
Past/Other Contributors: Khamis Alabdouli, Florida State University
Team Location: Marshall Space Flight Center, Huntsville, Alabama
Abstract: Fires across Colombia have imposed a significant threat to biodiversity, rural communities, and established infrastructure. NASA’s Earth Observing System (EOS) can play a major role in monitoring fires and natural disasters. SERVIR, the Regional Visualization and Monitoring Network, constitutes a platform for the observation, forecasting and modeling of environmental processes in Central America. A SERVIR project called ÛÏThe GIS for Fire Management in Guatemala (SIGMA-I)Û was conducted to address fire forecasting in Guatemala, with successful results. This project builds upon research from the DEVELOP summer 2012 term with continued use of SIGMA-I as a reference and builds upon the methodology. The summer session feasibility study proved that NASA EOS data was reliable for monitoring the parameters contributing to wildfires. During the fall term, in-situ data from Colombia helped distinguish between anthropogenic, controlled fires, and wildfires. The in-situ data were used to improve the statistical accuracy of the correlation matrices. Using social information, such as the burn schedule of local farmers, fires were identified as either anthropogenic or naturally occurring. Naturally occurring fires were used to create a cause ignition model. The environmental factors included in the model were the accumulated precipitation recorded by Tropical Rainfall Measuring Mission (TRMM), in-situ weather station data, and the Normalized Difference Vegetation Index (NDVI) product produced by MODIS. From the correlations produced by the cause ignition model, an algorithm based on historical data was used to create a dynamic fire risk map with real-time satellite data. Incorporating environmental and social parameters in a fire risk evaluation model will benefit end-users in Colombia by enhancing their decision-making capacity and improving wildfire monitoring capabilities.
Transcript available here.