红外与毫米波学报, 2011, 30 (5): 451, 网络出版: 2011-10-13  

基于TM影像光谱指数的棉花病害严重度估测

Estimating severity level of cotton disease based on spcctral indicse of TM image
作者单位
1 新疆兵团绿洲生态农业重点开放实验室,石河子大学,新疆 石河子 832003
2 新疆农垦科学院棉花研究所, 新疆 石河子 832000
3 中国农业科学院作物科学研究所/国家农作物基因资源与基因改良重大科学工程, 北京 100081
摘要
通过获取多时相试验区TM影像和大田同步调查棉花黄萎病,将TM影像光谱指数与病害严重度进行相关分析,建立棉花病害严重度估测模型.结果表明: 随着病害严重度的增加,TM影像光谱指数B2,B4,SATVI,OSAVI,MSAVI,TSAVI,SVNSWI,SNSWIa,SNSWIb,SVNI,DNSIa,DNSIb,NDSWIa,NDSWIb,RNSWIa,RNSWIb,DVNI,EVI,TVI,SAVI,DVI,NDVI,RVI 和PVI逐渐减小,B1,B3, B7和RI逐渐增加,NDGI呈现先增后降的趋势,而B5呈现先降后增的趋势.病害严重度与TM影像光谱指数B1,B3和RI均呈极显著正相关,与B4,OSAVI,MSAVI, TSAVI,SVNSWI,SNSWIa,SNSWIb,SVNI,DNSIa,DNSIb,NDSWIa,NDSWIb,RNSWIa,RNSWIb,DVNI,EVI,TVI,NDGI,SAVI,DVI,NDVI,RVI 和PVI均呈极显著负相关,与SATVI呈显著负相关,与B2,B5和B7均未达显著相关.建立的8个TM影像光谱指数估算棉花黄萎病模型均通过显著性检验,且以DVI和DNSIb为自变量的线性模型精度最高,表明利用多时相TM卫星影像光谱指数进行棉田病害定量诊断是可行的.
Abstract
The cotton field infected by Verticillum wilt was investigated with both the multi-temporal TM images and the field survey simultaneously. A model of evaluating disease severity of the cotton was established by analyzing the correlation between spectral indices of TM image and severity level (SL) of the disease. The results indicated that with an increase of disease SLs, the values of spectral indices B2,B4,SATVI,OSAVI,MSAVI,TSAVI,SVNSWI,SNSWIa,SNSWIb,SVNI,DNSIa,DNSIb,NDSWIa,NDSWIb,RNSWIa,RNSWIb,DVNI,EVI,TVI,SAVI,DVI,NDVI,RVI and PVI declined slowly, B1,B3,B7 and RI increased gradually,NDGI increased at first and then decreased,while B5 exhibited a trend of decrease-increase with an increase of disease SLs. The SLs of disease were highly significantly positive correlated with the spectral indices values of B1,B3 and RI, highly significantly negative correlated with the spectral indice values of B4,OSAVI,MSAVI,TSAVI,SVNSWI,SNSWIa,SNSWIb,SVNI,DNSIa,DNSIb,NDSWIa,NDSWIb,RNSWIa,RNSWIb,DVNI,EVI,TVI,NDGI,SAVI,DVI,NDVI,RVI and PVI, significantly negative correlated with the spectral indice values of SATVI, and no significantly correlated with the spectral indice values of B2,B5 and B7. All of the eight spectral indices of TM image selected achieved significant correlation level. However, the linear models on the basis of DVI and DNSIb had the best estimating precision. This study demonstrated that it is feasible to estimate quantitatively the SL of cotton disease using the spectral indices of TM satellite image.

陈兵, 李少昆, 王克如, 苏毅, 陈江鲁, 金秀良, 吕银亮, 刁万英. 基于TM影像光谱指数的棉花病害严重度估测[J]. 红外与毫米波学报, 2011, 30(5): 451. CHEN Bing, LI Shao-Kun, WANG Ke-Ru, SU Yi, CHEN Jiang-Lu, JIN Xiu-Liang, LV Yin-Liang, DIAO Wan-Ying. Estimating severity level of cotton disease based on spcctral indicse of TM image[J]. Journal of Infrared and Millimeter Waves, 2011, 30(5): 451.

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