气候变化领域集成服务门户(CCPortal): Combined use of spectral and structural characteristics for improved red band needle blight detection in pine plantation stands

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DOI	10.1016/j.foreco.2018.12.005
	Combined use of spectral and structural characteristics for improved red band needle blight detection in pine plantation stands
	Smigaj M.; Gaulton R.; Suárez J.C.; Barr S.L.
发表日期	2019
ISSN	0378-1127
起始页码	213
结束页码	223
卷号	434
英文摘要	Current trends in research for detection of infections in forests almost exclusively involve the use of a single imaging sensor. However, combining information from a range of sensors could potentially enhance the ability to diagnose and quantify the infection. This study investigated the potential of combining hyperspectral and LiDAR data for red band needle blight detection. A comparative study was performed on the spectral signatures retrieved for two plots established in lodgepole pine stands and on a range of LiDAR metrics retrieved at individual tree-level. Leaf spectroscopy of green and partially chlorotic needles affected by red band needle blight highlighted the green, red and short near-infrared parts of the electromagnetic spectrum as the most promising. A good separation was found between the two pine stands using a number of spectral indices utilising those spectral regions. Similarly, a distinction was found when intra-canopy distribution of LiDAR returns was analysed. The percentage of ground returns within canopy extents and the height-normalised 50th percentile (height normalisation was performed to each tree's canopy extents) were identified as the most useful features among LiDAR metrics for separation of trees between the plots. Analysis based on those metrics yielded an accuracy of 80.9%, indicating a potential for using LiDAR metrics to detect disease-induced defoliation. Stepwise discriminant function analysis identified Enhanced Vegetation Index, Normalised Green Red Difference Index, percentage of ground returns, and the height-normalised 50th percentile to be the best predictors for detection of changes in the canopy resulting from red band needle blight. Using a combination of these variables led to a substantial decrease of unexplained variance within the data and an improvement in discrimination accuracy (96.7%). The results suggest combining information from different sensors can improve the ability to detect red band needle blight. © 2018 Elsevier B.V.
英文关键词	Disease; Forest health; Hyperspectral; LiDAR; Tree stress
语种	英语
scopus关键词	Discriminant analysis; Diseases; Infrared devices; Needles; Optical radar; Discrimination accuracy; Electromagnetic spectra; Enhanced vegetation index; Forest health; HyperSpectral; Red band needle blight; Stepwise discriminant; Structural characteristics; Forestry; canopy architecture; comparative study; coniferous forest; defoliation; disease incidence; environmental stress; forest health; lidar; plantation; spectral analysis; structural analysis; vegetation index; Bands; Detection; Discriminant Analysis; Diseases; Forestry; Height; Needles; Pinus Contorta; Pinus contorta
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156215
作者单位	School of Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom; Forest Research, Northern Research Station, Roslin, Midlothian EH25 9SY, United Kingdom
推荐引用方式 GB/T 7714	Smigaj M.,Gaulton R.,Suárez J.C.,et al. Combined use of spectral and structural characteristics for improved red band needle blight detection in pine plantation stands[J],2019,434.
APA	Smigaj M.,Gaulton R.,Suárez J.C.,&Barr S.L..(2019).Combined use of spectral and structural characteristics for improved red band needle blight detection in pine plantation stands.Forest Ecology and Management,434.
MLA	Smigaj M.,et al."Combined use of spectral and structural characteristics for improved red band needle blight detection in pine plantation stands".Forest Ecology and Management 434(2019).