光谱学与光谱分析 |
|
|
|
|
|
Using Hyperspectral Derivative Index to Monitor Winter Wheat Disease |
JIANG Jin-bao1,2,CHEN Yun-hao1*,HUANG Wen-jiang3 |
1. College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China 2. College of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China 3. National Engineering Research Center for Information Technology in Agriculture, Beijing 100089, China |
|
|
Abstract The canopy reflectance of winter wheat that infected different severity stripe rust was measured through artificial inoculation, the disease index (DI) of the wheat corresponding to the spectra was acquired in the field, and the parameters of biochemistry and biophysics were measured indoors. The 1st derivatives were analyzed. The results show that the 1st derivative values increase at the green edge (500-560 nm), while decrease at the red edge (680-760 nm) with DI increasing. The ratio of the sum of derivatives within the red edge (SDr′) to the sum of derivatives within the green edge (SDg′) has a higher negative linear correlation with DI, with a coefficient of determination r2=0.921 0(n=28), and that can be use to identify the healthy and disease crops 12 days before symptoms appearing. Therefore, the derivative vegetation index SDr/SDg can be used to monitor crops disease information. The conclusion is significant and may find application in acquiring crops disease information using hyperspectral remote sensing, and has a important meaning for increasing yields of crops and ensuring security of food supplies.
|
Received: 2006-06-05
Accepted: 2007-08-20
|
|
Corresponding Authors:
CHEN Yun-hao
E-mail: cyh@ires.cn
|
|
Cite this article: |
JIANG Jin-bao,CHEN Yun-hao,HUANG Wen-jiang. Using Hyperspectral Derivative Index to Monitor Winter Wheat Disease[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(12): 2475-2479.
|
|
|
|
URL: |
https://www.gpxygpfx.com/EN/Y2007/V27/I12/2475 |
[1] WAN An-min(万安民). World Agriculture(世界农业),2000,(5):39. [2] 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. [3] Carter G A, Miller R L. Remote Sensing of Environment, 1994, 50: 295. [4] Rinehart G L, Cathoun J H, Schabbenberger O. Australian Turfgrass Management. 2002. 4. [5] ZHANG Hong-ming(张宏名). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 1994, 14(5): 25. [6] 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. [7] HUANG Mu-yi, WANG Ji-hua, HUANG Wen-jiang, et al(黄木易, 王纪华, 黄文江, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2003, 19(6): 154. [8] HUANG Mu-yi, HUANG Wen-jiang, LIU Liang-yun, et al(黄木易, 黄文江, 刘良云, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2004, 20(1): 176. [9] JIANG Jin-bao, CHEN Yun-hao, HUANG Wen-jiang, et al(蒋金豹,陈云浩,黄文江,等). Optical Techniqiue(光学技术), 2007, 33(4): 620. [10] JIANG Jin-bao, CHEN Yun-hao, HUANG Wen-jiang, et al(蒋金豹,陈云浩,黄文江,等). Journal of Nanjing Agricultural University(南京农业大学学报),2007,30(3):63. [11] HUANG Wen-jiang, HUANG Mu-yi, LIU Liang-yun, et al(黄文江, 黄木易, 刘良云, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2005, 21(4): 97. [12] Smith K L, Steven M D, Colls J J. Remote Sensing of Environment, 2004, 92: 207. [13] PU Rui-liang, GONG Peng(浦瑞良,宫 鹏). Hyperspectral Remote Sensing and Its Applications(高光谱遥感及其应用). Beijing:Higher Education Press(北京:高等教育出版社), 2000. [14] Gausman H W, Allen W A, Cardenas R,et al. Appl. Optics,1970,9:545. [15] Sims D A,Gamon J A. Remote Sening Environment,2002,81:337. [16] MEI An-xin, PENG Wang-lu, QIN Qi-ming, et al(梅安新, 彭望琭,秦其明,等). Introductory of Remote Sensing(遥感导论). Beijing: Higher Education Press(北京:高等教育出版社), 2001. [17] Horler D N H, Barber J P, Ferns D C, et al. Advanced Space Reseach, 1983, 3: 175. [18] LI Jing, CHEN Yun-hao, JIANG Jin-bao, et al(李 京,陈云浩,蒋金豹,等). Science & Technology Review(科技导报), 2007, 25(6): 23. |
[1] |
WANG Hong-jian1, YU Hai-ye1, GAO Shan-yun1, LI Jin-quan1, LIU Guo-hong1, YU Yue1, LI Xiao-kai1, ZHANG Lei1, ZHANG Xin1, LU Ri-feng2, SUI Yuan-yuan1*. A Model for Predicting Early Spot Disease of Maize Based on Fluorescence Spectral Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3710-3718. |
[2] |
ZHU Zhi-cheng1, WU Yong-feng2*, MA Jun-cheng2, JI Lin2, LIU Bin-hui3*, JIN Hai-liang1*. Response of Winter Wheat Canopy Spectra to Chlorophyll Changes Under Water Stress Based on Unmanned Aerial Vehicle Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3524-3534. |
[3] |
FENG Hai-kuan1, 2, FAN Yi-guang1, TAO Hui-lin1, YANG Fu-qin3, YANG Gui-jun1, ZHAO Chun-jiang1, 2*. Monitoring of Nitrogen Content in Winter Wheat Based on UAV
Hyperspectral Imagery[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3239-3246. |
[4] |
ZHU Yu-chen1, 2, WANG Yan-cang3, 4, 5, LI Xiao-fang6, LIU Xing-yu3, GU Xiao-he4*, ZHAO Qi-chao3, 4, 5. Study on Quantitative Inversion of Leaf Water Content of Winter Wheat Based on Discrete Wavelet Technique[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2902-2909. |
[5] |
FENG Hai-kuan1, 2, YUE Ji-bo3, FAN Yi-guang2, YANG Gui-jun2, ZHAO Chun-jiang1, 2*. Estimation of Potato Above-Ground Biomass Based on VGC-AGB Model and Hyperspectral Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2876-2884. |
[6] |
JIN Chun-bai1, YANG Guang1*, LU Shan2*, LIU Wen-jing1, LI De-jun1, ZHENG Nan1. Band Selection Method Based on Target Saliency Analysis in Spatial Domain[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2952-2959. |
[7] |
GAO Yu1, SUN Xue-jian1*, LI Guang-hua2, ZHANG Li-fu1, QU Liang2, ZHANG Dong-hui1, CHANG Jing-jing2, DAI Xiao-ai3. Study on the Derivation of Paper Viscosity Spectral Index Based on Spectral Information Expansion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2960-2966. |
[8] |
KONG Bo1, YU Huan2*, SONG Wu-jie2, 3, HOU Yu-ting2, XIANG Qing2. Hyperspectral Characteristics and Quantitative Remote Sensing Inversion of Gravel Grain Size in the North Tibetan Plateau[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2381-2390. |
[9] |
ZHANG Xia1, WANG Wei-hao1, 2*, SUN Wei-chao1, DING Song-tao1, 2, WANG Yi-bo1, 2. Soil Zn Content Inversion by Hyperspectral Remote Sensing Data and Considering Soil Types[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2019-2026. |
[10] |
WANG Hui-min1, 2, YU Lei1, XU Kai-lei1, 2, JIANG Xiao-guang1, 2, WAN Yu-qing1, 2*. Estimation of Salt Content of Saline Soil in Arid Areas Based on GF-5 Hyperspectral Image[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2278-2286. |
[11] |
CAO Yang1, 2, LI Yan-hong1, 2*. Study on the Effects of NO2 Pollution Under COVID-19 Epidemic
Prevention and Control in Urumqi[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1981-1987. |
[12] |
ZHANG Chao1*, SU Xiao-yu1, XIA Tian2, YANG Ke-ming3, FENG Fei-sheng4. Monitoring the Degree of Pollution in Different Varieties of Maize Under Copper and Lead Stress[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1268-1274. |
[13] |
ZHANG Hai-yang, ZHANG Yao*, TIAN Ze-zhong, WU Jiang-mei, LI Min-zan, LIU Kai-di. Extraction of Planting Structure of Winter Wheat Using GBDT and Google Earth Engine[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 597-607. |
[14] |
LI Yun-xia1, MA Jun-cheng2, LIU Hong-jie3, ZHANG Ling-xian1*. Tillering Number Estimation of Winter Wheat Based on Visible
Spectrogram and Lightweight Convolutional Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 273-279. |
[15] |
XU Long-xin1, 2, 3, 4, SUN Yong-hua2, 3, 4*, WU Wen-huan1, ZOU Kai2, 3, 4, HE Shi-jun2, 3, 4, ZHAO Yuan-ming2, 3, 4, YE Miao2, 3, 4, ZHANG Xiao-han2, 3, 4. Research on Classification of Construction Waste Based on UAV Hyperspectral Image[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3927-3934. |
|
|
|
|