Verticillium wilt of cotton is one of the diseases of cotton with extensive occurrence and maximal harming in our country even in the world. Hyper spectrum remote sensing with the fine spectrum information has becoming the efficient method to monitor the Verticillium wilt of cotton. The research was conducted in Xinjiang, the largest cotton plant region of China. The paper used data which was collected both canopy spectrum infected with verticillium wilt nearand SL (severity level) in the year 2005 -2006, the quantitative correlation were analyzed between SL and canopy reflectance spectrum, derivative spectrum. The tested results indicated that spectrum characteristics of cotton canopy infected with verticillium wilt had better regularity with the increase of SL in different periods and varieties. Spectrum reflectance increased in visible light region (620 -700 nm) with the increase of the SL, which inverted in nearand SL (severity level) in the year 2005 -2006, the quantitative correlation infrared region, and extreme signification in 780 - 1300 nm. When SL got 25%, cotton canopy infected with verticillium wilt could be used as a watershed and diagnosed index in an early time. The tested results also indicated there were evident characteristics of first derivative spectrum in these SL, it changed significantly in red edge ranges (680 - 760 nm) with different SL, red edge swing decreased, and red edge position equal moved to the blue. The results indicated that 1001-1110 nm and 1205-1320 nm were selected out as sensitive band regions to SL of canopy. These some inversion models for estimating cotton canopy infected with verticillium wilt all reached the most significantly level. At last, the results suggested that different spectrum characteristics of cotton canopy infected with verticillium wilt were obvious, the first derivative spectrum (FD 731 nm -FD 1317 nm) will invert the cotton canopy SL accurately, and it may be used to forecast the position of cotton canopy infected with verticillium wilt in quantitatively.