基于新型植被指数的冬小麦覆盖度遥感估算

为提高冬小麦覆盖度估测精度,从增强近红外与红光差别的数学变换原理出发,构建了一种新型植被指数(NDVIn),再基于2013、2014年冬小麦冠层高光谱和模拟的资源三号卫星宽波段多光谱数据,分别构建基于常规植被指数(NDVI)与NDVIn的冬小麦覆盖度估算模型,然后利用留一交叉验证法对模型精度进行评价。结果表明,当n=6时,新生成的植被指数NDVI6对冬小麦农田覆盖度具有最好的估算性能,利用其基于小麦冠层高光谱及卫星多光谱数据建立的冬小麦覆盖度估算模型的决定系数r2分别为0.84、0.85,RMSE分别为0.092、0.091,模型精度均好于常规指数NDVI的估算结果。说明NDVI6用于估测冬小麦覆盖度具有可行性。

Estimating Vegetation Coverage of Winter Wheat Based on New Vegetation Index

In order to improve the precision of fractional canopy cover estimations of winter wheat,a new index,NDVI_n ,was derived by enhancing the difference between red and near-infrared reflectance. By using of canopy hyperspectral data and simulated wide band multi-spectral data of ZY-3 in 2013 and 2014,estimation models were built based on typical NDVI and the new NDVI_n . Then,leave one-out cross validation evaluated model.The results showed that NDVI_n achieved the best performance with an n value of 6.The model precision of estimating winter wheat coverage based on the new index NDVI₆ was better than typical NDVI built by using of canopy hyperspectral data and simulated ZY-3 wide band multi-spectral data with r being 0.84,0.85,RMSE being 0.092,0.091. Likewise,NDVI_n can feasibly be used to estimate fractional cover of winter wheat.