基于无人机RGB影像的苗期油菜识别

无人机可见光遥感具有经济成本低、起降方式灵活等优点，在监测苗期油菜缺苗和植株数量方面具有较好的应用前景。采用大疆Phantom 4 Pro V2.0四旋翼无人机获取油菜种植区的可见光影像，设置1个实验区和4个验证区，对比分析土壤、油菜苗、杂草等地物目标红（R）、绿（G）、蓝（B）波段的DN值，根据各波段DN值的正态分布特性和比值关系构建绿蓝红差异指数（green-blue-red difference index， GBRDI）。利用GBRDI对油菜种植区可见光影像进行计算，绘制不同地物的直方图，将其交点作为图像分割阈值对油菜苗植株进行提取，并与常见的过绿指数（excess green， ExG）、差异植被指数（visible-band difference vegetation index， VDVI）、归一化绿蓝差异指数 （normalized green-bule difference index， NGBDI）的提取结果进行对比。结果表明：相较于ExG、VDVI、NGBDI，GBRDI从杂草等背景地物中提取油菜苗效果更好，精度92.93%，完整性83.63%；在4个杂草长势复杂的验证区，GBRDI指数提取油菜苗的精度和完整性均比VDVI、ExG、NGBDI更高；GBRDI能快速准确地提取油菜苗，分离杂草和土壤等背景地物，可为油菜精细化耕作提供技术参考。

Rape Identification at Seedling Stage Based on UAV RGB Image

UAV visible light remote sensing has the advantages of low economic cost and flexible take-off and landing mode， and has good application prospect in monitoring rape seedling shortage and plant quantity calculation. The visible light images of rape planting area were obtained by DJI phantom 4 Pro v2.0 UAV with 4 rotors. 1 experimental area and 4 verification areas were set up to compare and analyze DN values in red（R），green（G），blue（B） bands of soil， rape seedlings， weeds and other ground objects. According to the normal distribution characteristics and ratio relationship of DN values in each band， the green-blue-red difference index （GBRDI） was constructed. the GBRDI was used to calculate the visible light image of rape planting area. The histogram of different ground objects was drawn and the intersection point was as the image segmentation threshold to extract rape seedlings and plants； finally， the extraction results of the GBRDI was compared with those of common excess green index （ExG）， visible band difference vegetation index （VDVI） and normalized green blue difference index （NGBDI）. The results showed that： compared with ExG， VDVI and NGBDI， GBRDI had better effect on extracting rape seedlings from weeds and other background features， with accuracy of 92.93% and integrity of 83.63%； in the 4 verification areas with complex weed growth， the accuracy and integrity of extracting rape seedlings by GBRDI index were higher than those of VDVI， ExG and NGBDI. Above results showed that GBRDI could quickly and accurately extract rape seedlings and separate weeds， soil and other background features， which provided technical reference for rape precision farming.