| 光谱学与光谱分析 |
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| Study on Hyper-Spectral Remote Sensing Models for Monitoring Damage of Oedaleus Asiaticus (Orthoptera: Acrididae) |
| LU Hui1,2,HAN Jian-guo1*,ZHANG Lu-da3 |
1. College of Animal Science and Technology, China Agricultural University, Beijing 100094, China
2. Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Danzhou 571737, China
3. College of Science, China Agricultural University, Beijing 100094, China |
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Abstract In the present paper, the ASD Field Spec Pro FRTM spectroradiometer was used for measuring damages of O. asiaticus in Xilin GolLeague, Inner Mongolia. First, the hyper-spectral data were analyzed and the canopy reflectance spectral data were compared between the healthy leaves and the infected leaves of Leymus chinensis. Second, the regression models between the leaf area index (LAI) and the hyper-spectral parameters were built, and different varieties of the O. asiaticus damage were used to test its precision. The results showed that there was a high correlation of three hyper-spectral data between the LAI and the first derivative data. Moreover the disease index (DI) model, which is mostly suitable for use in indicating the intensity of grasshoppers damage in the study area, containing the ratio of the sum of first derivative within red peak regions (620-760 nm, SDr) to the sum of first derivative within blue peak regions (430-470 nm, SDb) was the best one. From the model, there were no damage if DI was over 72.43, slight damage if DI was between 51.57 and 79.83, and serious damage if DI was less than 51.57. The model had the highest prediction precision with the correlation coefficient of prediction of 0.948, and the mean relative error of 3.928%. These results showed a good prediction of the model and indicated that the grasshopper damage could be estimated at the canopy level using hyper-spectral reflectance.
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Received: 2007-11-28
Accepted: 2008-03-02
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Corresponding Authors:
HAN Jian-guo
E-mail: grassslab@public3.bta.net.cn
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[1] LU Hui, YU Ming, ZHANG Li-sheng, et al(卢 辉，余 鸣，张礼生，等). Plant Protection(植物保护), 2005, 31(4): 55.
[2] Hao S G, Kang L. Journal of Applied Entomology, 2004, 128: 95.
[3] HAO Shu-guang, QIN Qi-lian, WANG Zheng-jun, et al(郝树广，秦启联，王正军，等). Acta Entomologica Sinica(昆虫学报), 2002, 45(4): 531.
[4] SHI Rui-xiang, LIU Chuang, LI Dian-mo, et al(石瑞香，刘 闯，李典谟，等). Acta Ecologica Sinica(生态学报), 2003, 23(11): 2475.
[5] Tappan G G, Moore D G, Knausenberger W I. Int. J. Geographic Information System, 1991, 5: 123.
[6] Carter G A, Miller R L. Remote Sensing of Environment，1994, 50: 295.
[7] Voss F, Dreiser L. New Trends in Locust Control. GIZ, 1994. 23.
[8] WANG Hai-guang, MA Zhan-hong, WANG Tao, et al(王海光，马占鸿，王 韬, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2007, 27(9): 1811.
[9] Kemp W P, Kalaris T M. Journal of Economic Entomology, 1989, 82: 1270.
[10] Tucher C J, Heilkema J U, Roffey J. International Journal of Remote Sensing, 1985, 6: 127.
[11] Sinba P P, Satish C. Plant Protection Bulletin, 1994, 46(1): 38.
[12] LI Hong-chang, XI Rui-hua, CHEN Yong-lin(李鸿昌，希瑞华，陈永林). Acta Ecologica Sinica(生态学报), 1983, 3(3): 214.
[13] QIU Xing-hui, KANG Le, LI Hong-chang(邱星辉，康 乐，李鸿昌). Acta Entomologica Sinica(昆虫学报), 2004, 47(5): 595.
[14] Jeffrey A L, Richard A S, Scott P S. Crop Protection, 2002, 21: 551.
[15] Smith K L, Steven M D, Colls J J. Remote Sensing of Environment, 2004, 92: 207.
[16] AN Hu, WANG Hai-guang, LIU Rong-ying, et al(安 虎，王海光，刘荣英，等). China Plant Protection(中国植保导刊), 2005, 25(11): 8.
[17] 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(7): 1363.
[18] WU Tong, NI Shao-xiang, LI Yun-hai, et al(吴 彤，倪绍祥，李云海，等). Journal of Remote Sensing(遥感学报), 2007, 11(1): 103.
[19] Cigliano M M, Kemp W P, Kalaris T M. Journal of Orthoptera Research, 1995, 4: 111.
[20] WANG Jian-qiang(王建强). World Agriculture(世界农业), 2003, (10): 44.
[21] WANG Tao, ZHANG Lu-da, LAO Cai-lian et al(王 韬，张录达，劳彩莲，等). Spectroscopy and Spectral Analysis (光谱学与光谱分析), 2006, 26(10): 1915.
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