| 光谱学与光谱分析 |
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| Using the Distance between Hyperspectral Red Edge Position and Yellow Edge Position to Identify Wheat Yellow Rust Disease |
| JIANG Jin-bao1, CHEN Yun-hao2, HUANG Wen-jiang3 |
1. College of Geoscience and Surveying Engineering, China Univeristy of Mine and Technology，Beijing 100083, China
2. College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China
3. National Engineering Research Center for Information Technology in Agriculture, Beijing 100089, China |
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Abstract The objective of the present paper is to identify healthy wheat and disease wheat by using hyeprspectral remote sensing as soon as possible. The canopy spectral reflectance of winter wheat infected by different severity yellow rust was measured and the disease indices (DI) were investigated in the field respectively. Smoothing the canopy spectra and calculating the first derivative values, the two methods were used to calculate the red edge position (REP) and yellow edge position (YEP) of the first derivative values: (a) maximum of the first derivative value; (b) Cho and Skidmore method. The result showed that REP gradually shifted to short-wave band, and the YEP gradually shifted to long-wave band with disease severity increasing, however, REP-YEP quickly became smaller. Analyzing and comparing the prediction precision of REP, YEP and REP-YEP for DI, the result indicated that the model REP-YEP as variable has the best estimation precision for DI than REP and YEP, the model estimation error is 6.22, and relative error is 14.3%, and it could identify healthy and disease wheat 12 days before the disease symptom apparently appeared. Therefore, this study not only can provide theory and technology for large areas monitoring of wheat disease by using hyperspectral remote sensing in the future, but also has the important meaning and practical application value for implementing precision agriculture.
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Received: 2009-09-22
Accepted: 2009-12-26
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Corresponding Authors:
JIANG Jin-bao
E-mail: jjb@ires.cn，ahdsjjb@126.com
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[1] ZHAO De-long, LI Jian-hua, SONG Zi-jian(赵德龙, 李建华, 宋子健). Advances in Earth Sciences(地球科学进展), 2003, 18(1): 94.
[2] PU Rui-liang, GONG Peng(蒲瑞良, 宫 鹏). Hyperspectral Remote Sensing and Its Application(高光谱遥感及其应用). Beijing: Higher Education Press(北京：高等教育出版社)，2000.
[3] XUE Li-hong, YANG Lin-zhang(薛利红，杨林章). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2008，24(9)：165.
[4] HUANG Jing-feng, WANG Yuan, WANG Fu-min, et al(黄敬峰，王 渊，王福民，等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2006，22(8)：22.
[5] ZHANG Xue-hong, LIU Shao-min, HE Bei-bei(张雪红，刘绍民，何蓓蓓). Journal of Beijing Normal University·Natural Science(北京师范大学学报·自然科学版)，2007，43(3)：245.
[6] WANG Yuan-yuan, CHEN Yun-hao, LI Jing, et al(王圆圆，陈云浩, 李 京, 等). Journal of Remote Sensing(遥感学报)，2007，11(6)：875.
[7] Cho M A, Skidmore A K. Remote Sensing of Environment, 2006, 101: 181.
[8] Clevers J G PW, de Jong SM, Epema G F, et al. International Journal of Applied Earth Observation and Geoinformation, 2001, 3(4): 313.
[9] Horler D H N. International Journal of Remote Sensing, 1983, 4: 273.
[10] Horler D H N, Barber J P, Ferns D C, et al. Advanced Space Research，1983, 3: 175.
[11] Boochs F, Kupfer G, Dockter K，et al. International Journal of Remote Sensing, 1990, 11：1741.
[12] de JONG S. California ITC Journal, 1998, 1: 1.
[13] Rock B N, Hoshizaki T, Miller J R. Remote Sensing of Environment, 1988, 24: 109.
[14] Vane Gregg, Goetz Alexander F H. Remote Sensing of Environment, 1988, 24: 1.
[15] Adams M L, Philpot W D，Norvell W A. International Journal of Remote Sensing, 1999, 20: 3663.
[16] Baret F, Champion I, Guyot G，et al. Remote Sensing of Environment, 1987, 22: 367.
[17] Gates D M, Keegan H J, Schleter J C，et al. Applied Optics, 1965, 4: 11.
[18] Gong P, Pu R，Heald R C. International Journal of Remote Sensing, 2002, 23(9)：1827.
[19] Noomen M F，Skidmore A K. International Journal of Remote Sensing, 2009, 30: 2, 481 .
[20] LI Guang-bo, ZENG Shi-mai, LI Zhen-qi(李光博, 曾士迈, 李振歧). Integrated Management of Wheat Pests(小麦病虫草鼠害综合治理). Beijing: Press of Agriculture Science and Technology of China(北京: 中国农业科技出版社), 1989. 185.
[21] LIU Liang-yun, HUANG Mu-yi, HUANG Wen-jiang, et al(刘良云, 黄木易, 黄文江，等). Journal of Remote Sensing(遥感学报)，2004, 8(3): 275.
[22] Huang W J, Huang M Y, Liu L Y, et al. Transactions of the CASE, 2005, 4(21): 97.
[23] JIANG Jin-bao, CHEN Yun-hao, HUANG Wen-jiang(蒋金豹，陈云浩，黄文江). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2007，27(12)：2475.
[24] CHEN Yun-hao, JIANG Jin-bao, HUANG Wen-jiang, et al(陈云浩，蒋金豹，黄文江, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2009, 29(8)：2161.
[25] Savitzky A, Golay M J E. Analytical Chemistry, 1964, 36：1627.
[26] Berrenger M. Digital Processing of Signals. Theory and Practice, 3rd Edition. New York: John Wiley and Sons, 2000.
[27] Smith K L. University of Nottingham, Ph. D thesis, 2003.
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