基于地质统计学的NDVI图像估值技术

将疏采样后的NDVI图像作为未受云层影响的已知数据,分别用普通克里格、泛克里格、指示克里格和序贯指示模拟对NDVI图像进行恢复并比较其效果。研究发现,各种克里格法对NDVI图像的估值效果由高到低依次为泛克里格、普通克里格、指示克里格,通常计算方便的普通克里格法就能够满足图像恢复所要求的精度;普通克里格方差和泛克里格方差只能反映数据的构型,不能很好地衡量估值图像的不确定性,指示克里格的条件方差的分布和实际误差的分布基本一致,能够较好地衡量估值图像的不确定性,并且其大小与NDVI影像数据的不确定性大小的分布一致。序贯指示模拟得到的多个等概率实现表现出很大的空间变异性,多个实现的均值图像光滑效应明显,估值精度不高,但是多个实现的方差分布可以很好地表征空间数据的不确定性分布。

Geostatistics-based technique for NDVI image estimation

The objective of this paper is to examine the effect of estimation of NDVI images by four geostatistical approaches, Ordinary Kriging (OK), Universal Kriging (UK), Indicator Kriging (IK) and Sequential Indicator Simulation(SIS).Using the undersampled data of NDVI from NOAA/AVHRR image of the Hetian River Watershed, both estimates and variances from OK, UK and IK are obtained. After comparison, we found that the images of OK and UK estimates can both successfully restore the overall trend of the original image, but the image of IK estimates is not good enough. We also found that the images of OK and UK variances only reflect the sampling configuration because OK and UK variances are independent of the data values locally, however, owing to the fact that IK variances are conditional on the data values, they show the errors of estimates perfectly, and the magnitudes of IK variances are consistent with the uncertainty of remotely sensed data.Using the undersampled data of NDVI, the multiple realizations from SIS exhibit strong variability, and the mean image from multiple realizations has a clear smoothing effect, with a low exactness. However, the image of variances from multiple realizations can successfully show the distribution of data uncertainty.