globalchange  > 影响、适应和脆弱性
DOI: 10.1016/j.foreco.2017.08.052
Scopus记录号: 2-s2.0-85028916284
论文题名:
Airborne laser scanning and tree crown fragmentation metrics for the assessment of Phytophthora ramorum infected larch forest stands
作者: Barnes C.; Balzter H.; Barrett K.; Eddy J.; Milner S.; Suárez J.C.
刊名: Forest Ecology and Management
ISSN:  0378-1127
出版年: 2017
卷: 404
起始页码: 294
结束页码: 305
语种: 英语
英文关键词: Larch ; LiDAR ; Phytophthora ramorum ; Tree disease
Scopus关键词: Laser applications ; Nearest neighbor search ; Neurodegenerative diseases ; Optical radar ; Surface analysis ; Airborne Laser scanning ; Canopy Height Models ; Healthy individuals ; Individual tree crown ; K nearest neighbours (k-NN) ; Larch ; Overall accuracies ; Phytophthora ramorum ; Forestry ; Coniferales ; Hexapoda ; Larix ; Phytophthora ramorum
英文摘要: The invasive phytopathogen Phytophthora ramorum has caused extensive infection of larch forest across areas of the UK, particularly in Southwest England, South Wales and Southwest Scotland. At present, landscape level assessment of the disease in these areas is conducted manually by tree health surveyors during helicopter surveys. Airborne laser scanning (ALS), also known as LiDAR, has previously been applied to the segmentation of larch tree crowns infected by P. ramorum infection and the detection of insect pests in coniferous tree species. This study evaluates metrics from high-density discrete ALS point clouds (24 points/m2) and canopy height models (CHMs) to identify individual trees infected with P. ramorum and to discriminate between four disease severity categories (NI: not infected, 1: light, 2: moderate, 3: heavy). The metrics derived from ALS point clouds include canopy cover, skewness, and bicentiles (B60, B70, B80 and B90) calculated using both a static (1 m) and a variable (50% of tree height) cut-off height. Significant differences are found between all disease severity categories, except in the case of healthy individuals (NI) and those in the early stages of infection (category 1). In addition, fragmentation metrics are shown to identify the increased patchiness and intra-crown height irregularities of CHMs associated with individual trees subject to heavy infection (category 3) of P. ramorum. Classifications using a k-nearest neighbour (k-NN) classifier and ALS point cloud metrics to classify disease presence/absence and severity yielded overall accuracies of 72% and 65% respectively. The results indicate that ALS can be used to identify individual tree crowns subject to moderate and heavy P. ramorum infection in larch forests. This information demonstrates the potential applications of ALS for the development of a targeted phytosanitary approach for the management of P. ramorum. © 2017
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/64096
Appears in Collections:影响、适应和脆弱性

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作者单位: University of Leicester, Leicester Institute for Space and Earth Observation (LISEO), Centre for Landscape and Climate Research, Department of Geography, University Road, Leicester, United Kingdom; NERC National Centre for Earth Observation (NCEO) at University of Leicester, University Road, Leicester, United Kingdom; Bluesky International Limited, The Old Toy Factory, Jackson Street, Coalville, Leicestershire, United Kingdom; Natural Resources Wales, Clawdd Newydd, Ruthin, Denbighshire, United Kingdom; Forest Research, Northern Research Station, Roslin, Midlothian, United Kingdom

Recommended Citation:
Barnes C.,Balzter H.,Barrett K.,et al. Airborne laser scanning and tree crown fragmentation metrics for the assessment of Phytophthora ramorum infected larch forest stands[J]. Forest Ecology and Management,2017-01-01,404
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