NH31A-1879
Texas Disasters: Mapping and Analyzing Fuel Loads and Phenology in the Texas Grasslands
Wednesday, 16 December 2015
Poster Hall (Moscone South)
Ben Beasley, University of New Orleans, New Orleans, LA, United States, Alex Holland, University of Oklahoma Norman Campus, Norman, OK, United States and Kristen Kelehan, University of Southern Mississippi, Long Beach, MS, United States
Abstract:
In recent years, the risk of severe wildfires has been increasing, in part due to weather phenomena such as sequences of wet and drought years and increasing urban expansion into wildland areas that are vulnerable to seasonal wildfires. This is particularly the case in Texas where grassland ecosystems accrue vegetative growth during wet years that when senesced can be vulnerable to wildfire during a subsequent drought year. The Texas Forest Service (TFS) is tasked with estimating and evaluating potential fire risk to manage and allocate resources for the prevention and containment of possible wildfires across the state. Some of the main components for assessing fire risk in this region are understanding the location and fire risk for available vegetative fuel types, as well as fuel load dynamics. NASA Earth Observations help provide a means for vegetative conditions of wildfire fuels (i.e. land cover types) and related land surface phenology across large temporal and spatial scales. The project was conducted in collaboration with the TFS, using Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat OLI to calculate vegetation indices such as Normalized Difference Vegetation Index, and produce fuel type and fuel load maps. The relative strengths of two satellite sensors were combined, leveraging the temporal resolution of MODIS with the higher spatial resolution of Landsat OLI. The project applied data fusion techniques, resulting in wildfire fuel maps that were created for the 2010-2011 fire season, which saw some of the worst wildfires in recent history, and for the 2014-2015 season to provide a current assessment of wildfire fuels. The end products provided a means to identify and assess wildfire risk in terms of fuel load type. The TFS is using project results to assess the potential for combined use of MODIS and Landsat data in order to better understand potential wildfire fuel loads and risks across the state.
