Spectral Characteristic Wavelengths of Moso Bamboo Leaves Damaged by Pantana Phyllostachysae Chao
HUANG Xu-ying1, XU Zhang-hua1, 2, 3, 4*, LIN Lu1, LIU Jian3, ZHONG Zhao-quan5, ZHOU Hua-kang6
1. College of Environment and Resources, Fuzhou University, Fuzhou 350116, China
2. Postdoctoral Research Station of Information and Communication Engineering, Fuzhou University, Fuzhou 350116, China
3. Fujian Provincial Key Laboratory of Resources and Environment Monitoring & Sustainable Management and Utilization, Sanming 365004, China
4. Key Lab of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou 350002, China
5. State-owned Forest Farm of Shunchang County, Nanping 353200, China
6. Yanping District Forestry Bureau of Nanping, Nanping 353000, China
Abstract：The paper aims to obtain the characteristic wavelengths of moso bamboo leaves damaged by Pantana phyllostachysae chao, with which the pest can be identified effectively and accurately. 105 hyperspectral data collected in Shunchang County, Fujian Province were randomly divided into two groups, i.e. the experimental group (71) and verificantion group (34). Selecting wavelengths which were highly significant differences between different pest levels group by One-way ANOVA. The wavelengths were screened by combining the wave band of the commonly used remote sensing satellite. The ability to discriminate between the pests of the selected wavelengths was analyzed by the Euclidean distance method, spectral angle mapping method and correlation coefficient method. According to the analysis results, the characteristic wavelengths were obtained and verified. The results showed that: (1) the spectral reflectance of moso bamboo leaves damaged by P. phyllostachysae were significantly lower than that of healthy leaves, and the higher the pest level is, the lower the reflectance will be; (2) with the increase in pest level, the spectral reflectance curves’ “green peak” and “red balley” of Pinus massoniana gradually disappeared, and the red edge was leveled; (3) the characteristic wavelengths of 703.43~898.56 nm (original spectrum) and 497.68~540.72, 554.53~585.25, 596.24~618.23 nm (first derivative spectrum) were determined, which had good response ability at different pest levels. Our findings will not only provide the theoretical guidliances for “ground-space” coupling, but also provide important basis for establishing the system of pest remote sensing monitoring technology.
[1] Radeloff V C, Mladenoff D J, Boyce M S. Remote Sensing of Envionment, 1999, 69(2): 156.
[2] Latifi H, Schumann B, Kautz M, et al. Environmental Monitoring and Assessment, 2014, 186(1): 441.
[3] ZHU Chen-hao, QU Shuai, ZHANG Xiao-li(朱程浩, 瞿 帅, 张晓丽). Journal of Remote Sensing(遥感学报), 2016, 20(4): 653.
[4] LIANG Guang-hong(梁光红). Journal of Fujian Forestry Science and Technology(福建林业科技), 2003, 30(1): 34.
[5] CHEN De-liang, ZHAO Ren-you, QU Qiao-wen(陈德良, 赵仁友, 瞿巧文). Forest Pest and Disease(中国森林病虫), 2006, 25(6): 14.
[6] WU Jian-qin(吴建勤). Plant Protection(植物保护), 2010, 36(3): 172.
[7] LI Xing-tian(李兴天). Modern Horticulture(现代园艺), 2013, (1): 153.
[8] Niemann K O, Quinn G, Stephen R, et al. Canadian Journal of Remote Sensing, 2015, 41(3): 191.
[9] Ju Y W, Pan J, Wang X T, et al. Nematology, 2014, 16: 1197.
[10] LIU Fei, FENG Lei, CHAI Rong-yao, et al(刘 飞, 冯 雷, 柴荣耀, 等). Acta Optica Sinica(光学学报), 2010, 30(2): 585.
[11] Agrios G N. Plant Pathology(植物病理学). Beijing: China Agricultural Press(北京: 中国农业大学出版社), 2009.
[12] LI Min-zan(李民赞). Spectral Analysis Techniques and Applications(光谱分析技术及其应用). Beijing: Science Press(北京: 科学出版社), 2006.
[13] Jia J, Quan W. Ecological Informatics, 2016, 35: 1.
[14] WU Wei-bin, ZHI Lei, HONG Tian-sheng, et al(吴伟斌, 支 磊, 洪添胜, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2013, 29(10): 175.
[15] WANG Qiang, YI Qiu-xiang, BAO An-ming, et al(王 强, 易秋香, 包安明, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2012, 28(15): 125.
[16] LI Ying, ZHANG Li-fu, YAN-Wei, et al(李 颖, 张立福, 严 薇, 等). Journal of Remote Sensing(遥感学报), 2013, 17(4): 855.
[17] Pu R L, Gong P, Biging G S, et al. IEEE Transactions on Geoscience and Remote Sensing, 2003, 341(4): 916.
[18] Cho M A, Debba P, Mutanga O, et al. International Journal of Applied Earth Observation and Geoinformation, 2012, 16(16): 85.
[19] GONG Zhao-ning, ZHAO Ya-li, ZHAO Wen-ji, et al(宫兆宁, 赵雅莉, 赵文吉, 等). Acta Ecologica Sinica(生态学报), 2014, 34(20): 5736.
[20] JI Rong-hua, ZHENG Li-hua, DENG Xiao-lei, et al(冀荣华, 郑立华, 邓小蕾, 等). Transactions of The Chinese Society of Agricultural Machinery(农业机械学报), 2014, 45(8): 269.
[21] LIU Xiao-jun, TIAN Yong-chao, YAO Xia, et al(刘小军, 田永超, 姚 霞, 等). Scientia Agricultura Sinica(中国农业科学), 2012, 45(3): 435.
