Classification of pixels of a satellite image is an important post-processing function in remote sensing applications. Most of the change classification methods focus on classifying the terrain change into different classes of natural objects. The basis of such classifications is statistical distribution and closeness of the spectral signature of the terrain preserved in the pixel. The proposed method makes use of Gaussian and Hessian computations on the intensity profile of the satellite image to classify terrain into 2D or 3D category depending on its curvature. This method is applied to the clusters of pixels which are classified as changes across multi-dated satellite images.

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Change detection Terrain Change Detection Hessian Difference of Gaussian