Assessing Tree Water Balance after Forest Thinning Treatments Using Thermal and Multispectral Imaging

Abstract

The health of coniferous forests in the western U.S. is under threat from mega-drought events, increasing vulnerability to insects, disease, and mortality. Forest densification resulting from fire exclusion increases these susceptibilities. Silvicultural treatments to reduce stand density and promote resilience to both fire and drought have been used to reduce these threats but there are few quantitative evaluations of treatment effectiveness. This proof-of-concept study focused on such an evaluation, using field and remote sensing metrics of mature ponderosa pine (Pinus ponderosa Doug. Laws) in central Oregon. Ground metrics included direct measures of transpiration (sapflow), branch and needle measures and chlorosis; drone imagery included thermal (TIR) and five-band spectra (R, G, B, Re, NIR). Thermal satellite imagery was derived from ECOSTRESS, a space-borne thermal sensor that is on-board the International Space Station (ISS). All metrics were compared over 2 days at a time of maximum seasonal drought stress (August). Tree water status in unthinned, light, and heavy thinning from below density reduction treatments was evaluated. Tree crowns in the heavy thin site had greater transpiration and were cooler than those in the unthinned site, while the light thin site was not significantly cooler than either unthinned or the heavy thin site. There was a poor correlation (Adj. R2 0.10–0.13) between remotely sensed stand temperature and stand-averaged transpiration, and tree level temperature and transpiration (Adj. R2 0.04–0.19). Morphological attributes such as greater needle chlorosis and reduced elongation growth supported transpirational indicators of tree drought stress. The multispectral indices CCI and NDRE, along with the NIR and B bands, show promise as proxies for crown temperature and transpiration, and may serve as a proof of concept for an approach to evaluate forest treatment effectiveness in reducing tree drought stress.

Keywords

• remote sensing
• thermal
• multispectral
• ponderosa pine
• vegetation index
• sapflow