关键词: 水稻, 多时相, 植被指数特征, 无人机多光谱影像, 植被覆盖度, 植被指数

Abstract:

In order to accurately and quickly obtain the vegetation index characteristics and vegetation coverage information of rice， the UAV was used to collect the multispectral image data of rice tillering stage， heading stage and seed setting stage， select different types of commonly used vegetation indexes， and extract and explore the vegetation index characteristics of three growth stages of rice at the scale of plot and pixel by using the ideas of sample statistics method and vegetation index intersection method， Then the threshold segmentation method was used to extract and calculate the rice vegetation information and coverage information. The results showed that in the three growth periods of rice， there were obvious phenological characteristics at the pixel and plot scales， which had obvious phenological characteristics， and there were obvious differences between weeds and trees； the extraction accuracy of vegetation coverage of multispectral vegetation index was higher than that of visible vegetation index； （normalized difference vegetation index， NDVI） had the highest accuracy in extracting vegetation coverage in three stages of rice， with extraction errors of 0.40%， 0.43% and 0.81%， R^{2of 0.77， 0.92 and 0.98， and （root mean square error， RMSE） of 9.09%， 2.97% and 0.38%. The extraction accuracy of （visible-band difference vegetation index，VDVI） was higher than that of （excess green-red-blue difference index，EGRBDI） and （excess green-excess red index，ExG-EXR）， the extraction errors were 4.30%， 1.36% and 1.60%， respectively， R2 were 0.53， 0.77 and 0.80， respectively， and RMSE were 14.62%， 3.70% and 5.50%，respectively. It could be seen that the research results can provide technical support for crop growth monitoring and vegetation coverage extraction.}

Key words: rice, multi-phase, remote sensing index features, UAV multispectral imagery, vegetation coverage, vegetation index