Sponsor
This project was supported in part by DISPRO (PMIS # 119202), a joint U.S. Environmental Protection Agency and National Park Service funding from 1998 to 2002, and NIFA 2007-35101-18144 from 2007 to 2009 awarded to the senior author. From 2011–2017, funding was provided by the Western Wildlands Environmental Threats Assessment Center, of the USDA Forest Service.
Published In
Remote Sensing
Document Type
Article
Publication Date
7-2020
Subjects
Remote sensing, Jeffrey pine -- Effect of drought on, Jeffrey pine -- Effect of stress on, Jeffrey pine -- Adaptation, Plant physiology, Infrared imaging
Abstract
Drought, ozone (O3), and nitrogen deposition (N) alter foliar pigments and tree crown structure that may be remotely detectable. Remote sensing tools are needed that pre-emptively identify trees susceptible to environmental stresses could inform forest managers in advance of tree mortality risk. Jeffrey pine, a component of the economically important and widespread western yellow pine in North America was investigated in the southern Sierra Nevada. Transpiration of mature trees differed by 20% between microsites with adequate (mesic (M)) vs. limited (xeric (X)) water availability as described in a previous study. In this study, in-the-crown morphological traits (needle chlorosis, branchlet diameter, and frequency of needle defoliators and dwarf mistletoe) were significantly correlated with aerially detected, sub-crown spectral traits (upper crown NDVI, high resolution (R), near-infrared (NIR) Scalar (inverse of NDVI) and THERM Δ, and the difference between upper and mid crown temperature). A classification tree model sorted trees into X and M microsites with THERM Δ alone (20% error), which was partially validated at a second site with only mesic trees (2% error). Random forest separated M and X site trees with additional spectra (17% error). Imagery taken once, from an aerial platform with sub-crown resolution, under the challenge of drought stress, was effective in identifying droughted trees within the context of other environmental stresses.
Rights
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
This work is licensed under a Creative Commons Attribution 4.0 International License.
DOI
10.3390/rs12142338
Persistent Identifier
https://archives.pdx.edu/ds/psu/34400
Citation Details
Grulke, N., Maxfield, J., Riggan, P., & Schrader-Patton, C. (2020). Pre-Emptive Detection of Mature Pine Drought Stress Using Multispectral Aerial Imagery. Remote Sensing, 12(14), 2338.