An Automated Tool for Deriving FARSITE Canopy Fuel Parameters from Airborne LiDAR Data

HyPerspectives proposes to address a serious obstacle to wildfire management by providing a software solution roadmap for the creation of crown fuel layers for the FARSITE fire simulator. By doing so we will connect recent advances in LiDAR technology with an end-user community who is in need of LiDAR-derived fuel data products. HyPerspectives will draw upon its successful experience in LiDAR software development, wildfire fuels research, and extensive ground-truth data to validate methods for extracting fire fuel parameters from LiDAR datasets and to design a software module, ELF-Forest, that holds a strong potential for commercialization. The ELF-Forest module will build upon a successful suite of software products for LiDAR processing (ELF-Base) that HyPerspectives has developed for use within the ENVI/IDL (ENvironment for Visualizing Imagery/Interactive Data Language) program environment. At the same time, we will address an issue of national importance: the management of costly and dangerous wildfires. The proposed work will also capitalize on USDAs investment in the FARSITE model by providing enhanced crown fuel layers that are FARSITE-ready and allow for increased accuracy of crown fire simulation. In addition to addressing the need for canopy fuel parameters, our proposed software has many additional applications such as monitoring agricultural resources, combating bioterrorism, monitoring energy sources, and measuring sequestered carbon in vegetation.