Estimating Severity Level of Cotton Infected Verticillium Wilt Based on Spectral Indices of TM Image
In this paper, we present a new method for monitoring severity level (SL) of cotton infected Verti-cillium wilt. Using eight groups multi-temporal TM images and field-investigating data in the cotton field infected Verticillium wilt, we analyzed the correlation between spectral indices of TM image and SL of disease, and established the estimation models for SL of cotton disease. The results indi-cated that the SLs of disease were highly significantly positive correlation with the spectral indices values of B1, B3 and Rl, highly significantly negative correlation with 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 correlation with SATVI, and no significantly correlation with B2, B5 and B7. Excluded the model of TSAVI, others models based on thirteen spectral indices which were selected out were all achieved higher estimating precision. Compare with the others the models, the linear models of DVI and DNSIb had the highest decision coefficients (0.836 and 0.820), the lowest root mean square errors (0.606 and 0.506) and lower relative error (0.154 and 0.008), and their the slop and intercept approached 1 and 0. So they were commended as best models to estimate SL of cotton disease by spectral indices of satellite image. This study shows that it is feasible to estimate the SL of cotton disease by the spectral indices of satellite image, quantitatively.
Cotton Verticillium Wilt Disease Severity TM Image Spectral Indices Estimation Models
Bing Chen Keru Wang Shaokun Li Chunhua Xiao Jianglu Chen Xiulinag Jin
Key Laboratory of Oasis Ecology Agriculture of Xinjiang Corps, Shihezi University, Shihezi, Xinjiang Key Laboratory of Oasis Ecology Agriculture of Xinjiang Corps, Shihezi University, Shihezi, Xinjiang Key Laboratory of Oasis Ecology Agriculture of Xinjiang Corps, Shihezi University, Shihezi, Xinjiang
国际会议
南昌
英文
1157-1163
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）