Quantifying snow cover and persistence in a post restoration environment: UAV-derived forest structure data and forest gap radiation modeling

Abstract

Snow cover and persistence are important drivers of late spring and early summer water availability in forest ecosystems. The structure and orientation of ponderosa pine (Pinus ponderosa) forest patches and interspaces regulate the localized net radiation and ultimately the interaction between snowmelt patterns and surrounding forest structure. Quantifying the relationship between post-treatment forest structure and snow cover can provide valuable information for considering soil water availability in restoration planning and forest management. We model snow area extent and patch persistence across a mechanically thinned ponderosa pine forest in northern Arizona. Using unmanned aerial vehicle (UAV) image-derived structure from motion (SfM) models, we estimate several key predictor variables for snow area extent and patch persistence: individual tree heights (R2 = 0.93, RMSE = 1.84 m), crown diameter (R2 = 0.23, RMSE = 1.89 m), and locations (XY coordinate mean difference = 1.45 m), and a collection of patch-level characteristics. The addition of terrestrial LiDAR data provide further improvements in crown diameter estimates as well as crown base heights for all individual trees. Model validation leverages a series of UAV-acquired multi-spectral orthomosaic images (n = 12) in 15 cm spatial resolution to quantify snow cover extent and persistence across the study site. Each image captures a specific date in the melt-off period for precipitation events (n = 4) spanning two consecutive winters over 2017-2018 and 2018-2019. Our estimates of the relationship between individual tree structure, aggregated to the forest patch level, and snow cover and persistence will provide the first comprehensive framework for assessing mechanical forest thinning impacts on site-specific snow retention. Specifically, the UAV data and model fusion workflows, the detailed relationship between forest patch structure and snow area persistence, as well as the forest management implications are the key findings that will be emphasized.