Yang Jun, Ding Feng, Chen Chen, Liu Tao, Sun Chengming, Ding Dawei, Huo Zhongyang. Study on correlation of wheat biomass and yield with UAV image characteristic parameters[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(23): 104-110. DOI: 10.11975/j.issn.1002-6819.2019.23.013
    Citation: Yang Jun, Ding Feng, Chen Chen, Liu Tao, Sun Chengming, Ding Dawei, Huo Zhongyang. Study on correlation of wheat biomass and yield with UAV image characteristic parameters[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(23): 104-110. DOI: 10.11975/j.issn.1002-6819.2019.23.013

    Study on correlation of wheat biomass and yield with UAV image characteristic parameters

    • In order to determine the correlation between UAV image information and wheat biomass and yield, based on the field experiments of different planting densities, different nitrogen fertilizer levels and different varieties, the RGB images of field wheat at main growth stages were obtained by using UAV aerial photography in this study. The color and texture characteristic parameter values of the wheat images were obtained by image processing, and the wheat biomass and final yield were obtained by field sampling, and then the relationship between the wheat biomass, yield and different index of color and texture feature parameters was analyzed. The results showed that the 8 color indexes such as normalized difference index (NDI), Extra green vegetation index(ExG), visible light atmospherical resistant vegetation index (VARI), extra red vegetation index (ExR), green leaf vegetation index (GLI), extra green-red difference index (ExGR), modified green-red vegetation index (MGRVI), red, green and blue vegetation index (RGBVI) and 4 texture feature parameters such as angular second moment (ASM), gontrast (CON), correlation (COR) and entropy (ENT) could be extracted from UAV images. The correlation between the biomass, yield and various color index at wheat jointing stage and booting stage was high. The correlation between all color indexes and biomass at the jointing stage reached an extremely significant level, and the correlation coefficient between ExGR and biomass was the highest, the correlation coefficient was 0.911. Except for RGBVI, all the other indexes reached a significant or extremely significant correlation at booting stage, among which MGRVI had the highest correlation and the correlation coefficient was 0.817. The correlation trend between color indexes and yield were consistent with that of biomass. The correlation between the color index and biomass and yield at early wintering stage and flowering stage were slightly lower than that at jointing stage and booting stage. Among the wheat texture parameters, only ASM and ENT at early wintering stage and CON and COR at jointing stage and CON at booting stage had a significant or extremely significant correlation with biomass, among which COR had the highest correlation(negative correlation) and the correlation coefficient was -0.574. CON and COR at jointing stage and CON, COR and ENT at booting stage had a significant or extremely significant correlation with yield, among which COR at jointing stage had the highest correlation(negative correlation) with the correlation coefficient of -0.530. After combining color index and the texture feature parameters, the correlation of these parameters with wheat biomass and yield were all improved. Among them, the biomass correlation increased by 0.27%, 0.11%, 8.81% and 2.65% respectively in the 4 stages, and the yield correlation increased by 7.05%, 0.72%, 0.58% and 0.12% respectively in the 4 stages. Therefore, combining the color index of UAV image with the texture feature parameters can improve the estimation accuracy of wheat biomass and yield.
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