Research on Classification of Pest and Disease Tree Samples Based on Hyperspectral Lidar

Jing Lu; Jiuying Chen; Wei Li; Mei Zhou; Jian Hu; Wenxin Tian; Chuanrong Li

doi:10.3788/LOP202158.1628004

Laser & Optoelectronics Progress, Volume. 58, Issue 16, 1628004(2021)

Research on Classification of Pest and Disease Tree Samples Based on Hyperspectral Lidar

Jing Lu^1,2, Jiuying Chen^1,2、*, Wei Li¹, Mei Zhou¹, Jian Hu¹, Wenxin Tian¹, and Chuanrong Li¹

¹Key Laboratory of Quantitative Remote Sensing Information Technology of CAS, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

²College of Optoelectronics, Chinese Academy of Sciences, Beijing 100049, China

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Figures & Tables(7)

Fig. 1. Schematic of hyperspectral lidar

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Fig. 2. Sample example of hyperspectral lidar data acquisition

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Fig. 3. Reflectivity of surface of healthy and infected samples. (a) Ailanthus altissima; (b) Pinus yunnanensis; (c) Koelreuteria paniculata paniculata

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Fig. 4. Classification accuracy trend of healthy tree samples and infected tree samples under different σ values. (a) Ailanthus altissima; (b) Pinus yunnanensis; (c) Koelreuteria paniculata

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Fig. 5. Classification accuracy trend of healthy tree samples and infected tree samples under different C values. (a) Ailanthus altissima; (b) Pinus yunnanensis; (c) Koelreuteria paniculata

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Table 1. Main parameters of hyperspectral lidar
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Table 1. Main parameters of hyperspectral lidar
Parameter Value
Spectral range/nm 400--2400
Spectral resolution/nm 2--10
Beam divergence/mmrad 0.4
Beam diameter/mm 10

Table 2. Classification accuracy of test set sample data
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Table 2. Classification accuracy of test set sample data
Test set sample Parameter Classification accuracy
Ailanthus altissima σ=2^-2^.⁷, C=47 0.9698
Pinus yunnanensis σ=2^-2^.¹, C=18 0.9121
Koelreuteria paniculata σ=2^-2^.⁵, C=48 0.6621

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Jing Lu, Jiuying Chen, Wei Li, Mei Zhou, Jian Hu, Wenxin Tian, Chuanrong Li. Research on Classification of Pest and Disease Tree Samples Based on Hyperspectral Lidar[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1628004

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