Choosing the optimal spatial scale is one of the crucial issues in the field of remote sensing.In this paper

an approach

which is based on texture frequency analysis is proposed to determine the optimal spatial scale for high resolution imagery.Firstly

four typical geo-objects are used to analyze their frequency properties of the response to the Fourier transform domain.Secondly

the original image is up-scaled to different spatial resolutions using point spread function.The adequate spatial scale is chosen according to the change patterns in the radius distribution and angle distribution curves of geo-object texture with up-scaling.Finally

the separability among four types of geo-objects at six scales is analyzed based on the texture feature to approve the feasibility of the new method.The object-based classification of the QuickBird panchromatic image by means of SVM is implemented

and results of experiment demonstrate that the higher accuracy can be obtained at the optimal spatial scale.