Identifying Likely Wildfire Ignition Points Using Topographic Analysis Statistical Investigations, and Artificial Intelligence Techniques

 
Brett Davis
Master of Science Candidate
Geomatics Program
Department of Forest Sciences
Colorado State University
Fort Collins, Colorado
 
Denis J. Dean
Associate Professor
Geomatics Program
Department of Forest Sciences
Colorado State University
Fort Collins, Colorado

 

ABSTRACT

Identifying likely wildfire ignition points has obvious significance to natural resource managers interested in effectively planning wildfire risk mitigation programs. Furthermore, it stands to reason that the risk of at least some types of wildfire ignition can be related to a variety of cartographic features (e.g., lightening strikes are more likely on ridge lines, accidental human-caused fire ignitions are more likely in heavily used areas, etc.). This study will use an extensive database from Yosemite National Park to investigate the feasibility of identifying wildfire ignition risk using standard GIS cartographic analysis procedures, statistical inquires, and artificial intelligence techniques.