Modified ALV for selecting the optimal spatial resolution and its scale effect on image classification accuracy
Faced with the prevalence of multi-spatial resolution satellite data sets, selecting data with an appropriate resolution has become a new problem. This paper analyses the significance of scale selection of remote sensing images and discusses a geo-statistics based method for selecting the optimal spatial resolution of a remote sensing image. Breaking through the limitation of traditional average local variance (ALV), the modified ALV method based on variable window size and variable resolution is proposed to quantitatively select the optimal spatial resolution of a remote sensing image. In order to verify the validity of this method and interpret the relationship among spatial resolution, local variance and classification accuracy, this paper gives further image classification experiments with different spatial resolution. The experimental results show that the trend of classification accuracy along spatial resolution is basically accordant with that of modified ALV, which means that the image classification accuracy of the optimal resolution image is basically higher than those of others. Therefore, the modified ALV method for quantitively selecting the optimal spatial resolution of remote sensing image has theoretical and instructional meaning to a certain extent
Remote sensing image Scale Spatial resolution Modified average local variance Image classification
Dongping Ming Jianyu Yang Longxiang Li Zhuoqin Song
School of Information Engineering, China University ofGeosciences (Beijing), Xueyuan Road 29, Haidia College of Information & Electronic Engineering, China Agricultural University, Tsinghua East Road 1 School of Information Engineering, China University ofGeosciences (Beijing), Xueyuan Road 29, Haidia
国际会议
南昌
英文
1061-1068
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）