The authors have proposed a method of the P(X,Y) points identification on a random-generalized terrain surface, where the Z-coordinates are significantly discrepant from the assumed “background” of a particular surface image. The analyzed background consists of average or mean square deviations of the Z-coordinates from local regression surfaces locally fitted to the points of discrete presentation of a terrain. Obtained anomalies stand either for the results of insufficient local density of a surface sampling or confirm the hypothesis assuming that the real terrain surface does not fulfill the criteria determined by mathematical terrain models for the surface z= f(X,Y) with the continuous first derivative (surfaces of the C¹ class).

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