TREE-LEVEL FUEL CONNECTIVITY TO ASSESS CROWN WILDFIRE POTENTIAL BY UAS-BASED PHOTOGRAMMETRY

Abstract

Evaluating the potential for crown fires remains a pivotal concern in wildfire management because it affects fire behavior, causing them to spread further. In this work, we propose a methodology to assess crown fire potential based on the tree connectivity at crown level from UAS (Unmanned Aircraft Systems)-based Structure-from-Motion Photogrammetry. The approach is usable in a large landscape with the aim of reducing crown fire potential by considering the spatial variability of fuels within a stand. The utilization of UAS for photogrammetry holds immense promise in transforming the approach to assessing and managing forest fires. This cutting-edge technology offers the potential to deliver highly precise and comprehensive data concerning forest structure and connectivity, thereby presenting a groundbreaking opportunity for enhanced forest fire analysis and control.