Abstract: The paper analysis the changes of 16 image feature indices through field experiments, as well as the correlation with wheat chlorophyll, and then constructing estimated models of wheat waterlogging based on the attenuation of image feature indices. The results shows that R, normalized redness index （NRI）, green minus red （GMR）, excess red index （EXR）, color index of vegetation extraction （CIVE）, Woebbecke index（WI） were all significantly increased with the time increased of waterlogging, while normalized greenness index （NGI）, normalized green red difference index （NGRDI）, excess green index （EXG）, green-red ratio vegetation index （GRVI） were significantly decreased. And the above 10 image feature indices were significantly correlated with chlorophyll, with the maximum absolute values of 0.98. Moreover, the quadratic polynomial model could be efficiently applied for the modeling of chlorophyll reduction estimation, and the accuracy of the models based on NGRDI、CIVE、EXG、NGI and GRVI exponential deerement was high R² was above 0.99. These results indicated that digital image technology could be applied as an effective method for chlorophyll estimation to monitor wheat waterlogging, and NGRDI、CIVE、EXG、NGI and GRVI can be used as disaster damage image index to reflect the degree of wheat chlorophyll waterlogging.

Key words: waterlogging, chlorophyll, winter wheat, digital image