基于无人机多光谱NDVI值估测玉米产量

Research of maize yield estimation based on unmanned aerial vehicle multispectral NDVI

【目的】研究基于UAS-8无人机采集数据,运用归一化植被指数(Normalized Difference Vegetation Index)模型估测玉米产量,为大田无人机多光谱预测玉米产量提供理论依据。【方法】以新疆18份春播玉米为研究对象,获取开花期多光谱图像,经过辐射校正、大气校正、建立掩膜、提取NDVI图,计算植被覆盖率,得到区光谱反射率和归一化植被指数实际数值,将NDVI值与田间实测产量值进行模型拟合。【结果】幂函数Y=23411.46-10997.99/X(R^(2)=0.4886),二次函数为Y=39003.00-117963.03X+103130.25X 2(R^(2)=0.562),正反比函数(Inverse Proportional Function)为Y 2=2840.5 X/(1-X)(R^(2)=0.495),利用偏最小二乘回归(Partial Least Squares Regression),其线性函数Y=24458.22X-9620.55(R^(2)=0.521)。【结论】在数值0.5~0.8区间,NDVI与玉米产量具有较高的相关性,线性函数方程NDVI值可预测玉米的产量。

【Objective】To explore the normalized difference vegetation index,an estimation model for maize yield,this study has provided a theoretical basis for the multispectral prediction of maize yield by field UAV.【Methods】Xinjiang eighteen spring-sown maize was taken as the research object,a multispectral image of the flowering period was obtained,and the actual spectral reflectance of the experimental area was obtained after radiometric correction,atmospheric correction,establishment of mask,extraction of NDVI map,and calculation of vegetation coverage,so as to obtain the actual value of normalized vegetation index.In addition to that,the NDVI value was fitted to the measured yield in the field.【Results】The power functions Y=23,411.46-10,997.99/X(R^(2)=0.488,6),polynomial functions Y=39,003.00-117,963.03X+103,130.25X 2(R^(2)=0.562,0),using partial least squares regression.The result was a linear function Y=24,458.22X-9,620.55(R^(2)=0.722,2).【Conclusion】The results show that it has a certain correlation with maize yield,and the linear function model of NDVI value and yield during the critical period of maize growth.