Pre-Visual Spectral Responses of Pine Trees Affected by Pine Wilt Disease Revealed by Onset-Aligned UAV Multispectral Monitoring

Early detection of pine wilt disease (PWD) before visible crown discoloration is important for field inspection, confirmatory sampling, and timely management. However, because individual trees reach visible discoloration at different times, calendar-based analyses can blur the development of pre-visual spectral responses. Weekly UAV multispectral data from two Pinus massoniana forest sites were therefore aligned to the first visible crown discoloration of each tree. Crown-level band reflectance and vegetation indices (VIs) were examined from eight to one weeks before first visible discoloration, and healthy reference observations at each relative week were used to define 5th–95th percentile reference ranges for detection-rate (DR) analysis. Several VIs showed significant group-level differences from approximately seven weeks before first visible discoloration, whereas mean VI-based DR increased markedly to 0.52 at two weeks and 0.68 at one week before discoloration; single-band DRs were less stable. These results indicate a progressive pre-visual spectral response, with an exploratory early group-level indication emerging approximately seven weeks before discoloration and a stronger, more consistent spectral departure during the final two weeks. This onset-aligned framework provides a practical basis for scheduling repeated UAV surveillance and prioritizing field verification before obvious symptoms emerge.

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Publication Details

Journal
Plants
Published
2026-09-04
DOI
https://doi.org/10.3390/plants15172720
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

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article

Pre-Visual Spectral Responses of Pine Trees Affected by Pine Wilt Disease Revealed by Onset-Aligned UAV Multispectral Monitoring

Ziyi You, Run Yu, Songqing Wu, Runkai Chen et al.
Plants
Remote Sensing in Agriculture
article

Pre-Visual Spectral Responses of Pine Trees Affected by Pine Wilt Disease Revealed by Onset-Aligned UAV Multispectral Monitoring

Ziyi You, Run Yu, Songqing Wu, Runkai Chen, Zhixuan Ye, Feiping Zhang, Nan Zheng, Zuliang Jiang
article en

Abstract

Early detection of pine wilt disease (PWD) before visible crown discoloration is important for field inspection, confirmatory sampling, and timely management. However, because individual trees reach visible discoloration at different times, calendar-based analyses can blur the development of pre-visual spectral responses. Weekly UAV multispectral data from two Pinus massoniana forest sites were therefore aligned to the first visible crown discoloration of each tree. Crown-level band reflectance and vegetation indices (VIs) were examined from eight to one weeks before first visible discoloration, and healthy reference observations at each relative week were used to define 5th–95th percentile reference ranges for detection-rate (DR) analysis. Several VIs showed significant group-level differences from approximately seven weeks before first visible discoloration, whereas mean VI-based DR increased markedly to 0.52 at two weeks and 0.68 at one week before discoloration; single-band DRs were less stable. These results indicate a progressive pre-visual spectral response, with an exploratory early group-level indication emerging approximately seven weeks before discoloration and a stronger, more consistent spectral departure during the final two weeks. This onset-aligned framework provides a practical basis for scheduling repeated UAV surveillance and prioritizing field verification before obvious symptoms emerge.

PlantsVol. 15(17)
Fujian Agriculture and Forestry University (CN)
National Key Research and Development Program of China
Life in Land
Openalex Percentile: Top 10%
Remote Sensing in Agriculture
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