Accuracy Assessment of Thematic Classification Based on Point and Cluster Sample
遥感图像分类精度的点、群样本检验与评估

In order to assure the application of thematic classification,it is very important and necessary to make a rigorous accuracy assessment.In this paper,we use sampling-methods of point and cluster sample to assess the accuracy of the same region's land-use/land-cover thematic maps,which are derived from different resolution remote sensing data.Here,Sampling designs are consisted of simple random,systematic and stratified sampling.The results are as following.Firstly,the sampling design has great impact on the accuracy of remote sensing classification.There exists great randomicity on the result of points and cluster sample verification on the different Sampling design.On the same sampling design,the stability of point sample verification is higher than that of Cluster sample verification.Secondly,the average accuracy of different sampling designs of multi-point and multi-cluster sample verification can reflect the accuracy characteristic.During the course of point sample verification,stratified sampling's error is lower than others'.During the course of cluster sample verification,systematic sampling and stratified sampling's accuracy are prior to simple random sampling's.