Analysis on Classified Precision of Land Use Using Remote Sensing Images in Different Temporal

There is an exigent request on remote sensing images in timeliness and season for land use. We choose three packs of SPOT5 remote sensing images in different temporal in this examination of automatic classification by computer. With the annotation on the spot, we statistic the relative square error during classification, fit the regression relationship between classification error and temporal as well, and then gain the logarithm-related regression function. Combining the results with phonological characters in the research area, we synthetically analyze the remote sensing images and present some evaluation of the images which can be used for the investigation of land use. With the result that we can prolong the gaining time of images, thus increase the utilization rate of remote sensing data in the investigation of land use.