Research On Scale Effect Of Remote Sensing Image Based On Structural Nested Analysis

With the rapid development of remote sensing technology, remote sensing detectors provide us a lot of data, in order to extract the data that we need, we must filter and process the data. As a result of the complexity of the surface environment, remote sensing spectral information what there are a lot of mixed messages .And because the sensor correlation between each band, making the establishment of remote signal through the direct and surface parameters Relationship between the extraction of spectral information is difficult to meet the precision requirements. With the spectral characteristics of various types of research and the introduction of geology regularity to analysis remote sensing data ,this statistical model can greatly improve the extraction accuracy.Scale is a key concep t for understanding the comp lexity of earth system. And it is regarded as one of the main challenges of earth observation. Spatial scaling effects are a universal issue for the remote sensing. The appropriate spatial resolution can reveal the spatial structure of specific objects. Scale is an important factor in the application of remote sensing which directly influences the effect of analysis.If we ignore the scale of remote sensing ,we will be diffcult to get the exactly parameters of the earth's surface. The scale of remote sensing has sparked international remote sensing industry high attention.The combination of specific research applications, the scale phenomena from the ground and starting their own, select the optimum scale of remote sensing information and resolution, is very practical significance.Based on analyzing the scale characteristic of remote sensing images, this paper analyses the scale selection and discusses geo-statistics based method of quantificationally selecting the optimal spatial resolution of remote sensing image.And discussed the local variance method based on traditional, local variance and improve the dispersion and other methods in dealing with the problem of scale advantages and disadvantages of remote sensing images. Illustrates the traditional method and the dispersion of local variance method can not get the desired results of the cause. In this regard, this paper, based on structural analysis of variation function select the best spatial resolution, the use of geostatistics in the variation function of the nested structure of the scale effect of remote sensing images to study. ENVI software and will use remote sensing data processing and conversion, and then calculated with the parameters of IDL and image fit. Finally, the experimental results show that this geo-statistics based method of quantificationally selecting the optimal spatial resolution of remote sensing image has theoretical and instructional meanings.