Pre-Emptive Detection of Mature Pine Drought Stress Using Multispectral Aerial Imagery
Drought, ozone (O<sub>3</sub>), 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 t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/12/14/2338 |
| _version_ | 1827712703613894656 |
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| author | Nancy Grulke Jason Maxfield Phillip Riggan Charlie Schrader-Patton |
| author_facet | Nancy Grulke Jason Maxfield Phillip Riggan Charlie Schrader-Patton |
| author_sort | Nancy Grulke |
| collection | DOAJ |
| description | Drought, ozone (O<sub>3</sub>), 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. |
| first_indexed | 2024-03-10T18:19:20Z |
| format | Article |
| id | doaj.art-e1f392c0bebe48cd8ebf7c9d3b8f706c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T18:19:20Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e1f392c0bebe48cd8ebf7c9d3b8f706c2023-11-20T07:27:24ZengMDPI AGRemote Sensing2072-42922020-07-011214233810.3390/rs12142338Pre-Emptive Detection of Mature Pine Drought Stress Using Multispectral Aerial ImageryNancy Grulke0Jason Maxfield1Phillip Riggan2Charlie Schrader-Patton3Pacific Northwest Research Station, USDA Forest Service, Bend, OR 97701, USABiology Department, Portland State University, Portland, OR 97201, USAPacific Southwest Research Station, USDA Forest Service, Riverside, CA 92507, USAWestern Wildlands Environmental Threats Assessment Center, USDA Forest Service, Bend, OR 97701, USADrought, ozone (O<sub>3</sub>), 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.https://www.mdpi.com/2072-4292/12/14/2338remote sensingphysiological drought stresswithin-crown resolutionjeffrey pinesierra nevadathermal imagery |
| spellingShingle | Nancy Grulke Jason Maxfield Phillip Riggan Charlie Schrader-Patton Pre-Emptive Detection of Mature Pine Drought Stress Using Multispectral Aerial Imagery Remote Sensing remote sensing physiological drought stress within-crown resolution jeffrey pine sierra nevada thermal imagery |
| title | Pre-Emptive Detection of Mature Pine Drought Stress Using Multispectral Aerial Imagery |
| title_full | Pre-Emptive Detection of Mature Pine Drought Stress Using Multispectral Aerial Imagery |
| title_fullStr | Pre-Emptive Detection of Mature Pine Drought Stress Using Multispectral Aerial Imagery |
| title_full_unstemmed | Pre-Emptive Detection of Mature Pine Drought Stress Using Multispectral Aerial Imagery |
| title_short | Pre-Emptive Detection of Mature Pine Drought Stress Using Multispectral Aerial Imagery |
| title_sort | pre emptive detection of mature pine drought stress using multispectral aerial imagery |
| topic | remote sensing physiological drought stress within-crown resolution jeffrey pine sierra nevada thermal imagery |
| url | https://www.mdpi.com/2072-4292/12/14/2338 |
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