小麦生物量及产量与无人机图像特征参数的相关性研究

为了明确无人机图像信息与小麦生物量、产量之间的相关性，该文利用无人机航拍获取田间小麦主要生育时期的RGB图像，通过影像处理获取小麦颜色指数和纹理特征参数值，并通过田间取样获取同时期小麦生物量和最终产量，分析不同颜色指数和纹理特征参数与小麦生物量和产量的关系。结果表明：利用无人机图像可提取归一化差分指数（NDI）、超绿植被指数（ExG）、可见光大气阻抗植被指数（VARI）、超红植被指数（ExR）、绿叶植被指数（GLI）、绿红差值指数（ExGR）、改良绿红植被指数（MGRVI）、红绿蓝植被指数（RGBVI）共8个颜色指数和能量（ASM）、对比度（CON）、相关度（COR）、熵（ENT）共4个纹理特征参数。各颜色指数在小麦拔节期、孕穗期与生物量和产量都有较好的相关性。拔节期所有颜色指数与生物量的相关性均达到极显著水平，其中ExGR与生物量的相关性最高，相关系数r达到0.911，孕穗期除RGBVI未达到显著相关外，其余均达到显著或极显著相关，其中MGRVI相关性最高，相关系数r为0.817。各颜色指数与产量的相关性趋势同生物量一致。越冬前期和开花期各颜色指数与生物量及产量的相关性较拔节期和孕穗期略有下降。而各纹理特征参数中，只有越冬前期的ASM和ENT、拔节期的CON和COR以及孕穗期的CON与生物量的相关性达到显著或极显著水平，其中COR相关性最高（负相关），相关系数r为-0.574。拔节期的CON和COR、孕穗期的CON、COR和ENT与产量的相关性达到显著或极显著水平，其中拔节期COR相关性最高（负相关），相关系数r为-0.530。将颜色指数与纹理特征参数相结合后，其与小麦生物量及产量的相关性均有提高，其中生物量相关性在4个时期分别提高0.27%、0.11%、8.81%和2.65%，产量相关性在4个时期分别提高7.05%、0.72%、0.58%和0.12%。因此，将无人机图像颜色指数与纹理特征参数结合可以提高小麦生物量和产量的估测精度。

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.