UAV-Based Estimate of Snow Cover Dynamics: Optimizing Semi-Arid Forest Structure for Snow Persistence

Seasonal snow cover in the dry forests of American West provides essential water resources to both human and natural systems. The structure trees their arrangement across landscape are important drivers distribution these forests, varying widely space time. We used unmanned aerial vehicle (UAV) multispectral imagery Structure-from-Motion (SfM) models quantify rapidly melting dynamics examine effects forest shading on persistent a recently thinned ponderosa pine forest. Using repeat UAV (n = 11 dates) 76 ha forest, we first developed rapid effective method for identifying with 90.2% overall accuracy. SfM model correctly identified 98% 1280) trees, when compared terrestrial laser scanner validation data. SfM-derived variables, then found that canopy associated vertical horizontal metrics was significant driver patches (R2 0.70). results indicate image-derived can be accurately predict patch size persistence. Our provide insight into importance structure, specifically shading, amount seasonal typical environment. An operational understanding will help drive management target addition health.