In this study, we show that the correct determination of surface morphology using scanning force microscopy (SFM) imaging and power spectral density (PSD) analysis of the surface roughness is an extremely demanding task that is easily affected by experimental parameters such as scan speed and feedback parameters. We present examples were the measured topography data is significantly influenced by the feedback response of the SFM system and the PSD curves calculated from this experimental data do not correspond to that of the true topography. Instead, either features are "lost" due to low pass filtering or features are "created" due to oscillation of the feedback loop. In order to overcome these serious problems we show that the interaction signal (error signal) can be used not only to quantitatively control but also to significantly improve the quality of the topography raw data used for the PSD analysis. In particular, the calibrated error signal image can be used in combination with the topography image in order to obtain a correct representation of surface morphology ("true" topographic image). From this "true" topographic image a faithful determination of the PSD of surface morphology is possible. The corresponding PSD curve is not affected by the fine-tuning of feedback parameters, and allows for much faster image acquisition speeds without loss of information in the PSD curve.

A method to precisely calibrate the oscillation amplitude in dynamic scanning force microscopy is described. It is shown that the typical electronics used to process the dynamic motion of the cantilever can be adjusted to transfer the thermal noise of the cantilever motion from its resonance frequency to a much lower frequency within the typical bandwidth of the corresponding data acquisition electronics of a scanning force microscopy system. Based on this concept, two procedures for the calibration of the oscillation amplitude are proposed. One is based on a simple calculation of the root mean square deviation measured at the outputs of the electronics used to process the dynamic motion of the cantilever, and the second one is based on analysis of the corresponding spectrum and the calculation of the quality factor, the resonance frequency and the signal strength.We show that the proposed scheme for amplitude calibration using thermal noise is experimentally and theoretically robust, with soft as well as with hard cantilevers. Moreover, it is directly related to well-defined quantities such as the force constant and thermal energy, in contrast to the calibration using amplitude versus distance curves, which requires non-trivial a priori assumptions regarding the amplitude versus distance relation.

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