Kriging算子及其在遥感影像空间分析中的应用

Kriging Algorithm and Its Application to the Spatial Analysis of Remotely Sensed Imagery

由于遥感过程的不确定性及地面状况的复杂性，使得一些像元常常难以判读，甚至出现像元丢失，形成信息“缺口”，因此，如何估测难以识别的像元、内插被丢失的像元，是遥感影像信息提取中面临的一个课题。通过ｋｒｉｇｉｎｇ算子应用于ＴＭ资料空间分析的实验研究，证明了它在这类研究中的作用与精度。

Because of the uncertainty of remote sensing process and the complexity of ground features, some piexls are often obscured,even missed. Thus, it is a important problem how to estimate obscured piexls and interpolate values for missing pixels. We demonstrate the usefulness and accuracy of kriging algorithm to the problem by a case study.