The application of particle image velocimetry to turbulence measurement is described. An analysis of physically necessary spatial resolution is presented by using a model spectrum function. A comparison is made with hot-wire anemometry. Some aspects of spatial filtering and two-dimensional sampling are presented with a comparison to large-eddy simulation. The estimation of time mean turbulence quantities from the measured vector fields in a laboratory mixer is used as an example. The measurement results for two different image sizes at the same position in the flow field are compared with different interrogation area sizes. The assumed dependence of the velocity field on the interrogation area size could not be confirmed. The image size seems to produce dependence in all estimated quantities. The measurement errors are critical for the achieved results.

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A new method to apply spatial two-dimensional power spectral density (2D PSD) analysis to the data measured with Particle Image Velocimetry (PIV) has been introduced. Applying the method to a set of the velocity vector fields characteristic turbulence length scales can be estimated. In this method the computation of 2D PSD has been performed to two kinds of pre-processed data. In the first set, the local average has been spatially subtracted (Spatial decomposition) and in the second set the time-average has been subtracted (Reynolds decomposition). In the computation of 2D PSD the 2D FFT with the variance scaling has been used.Besides 2D spectral analysis this paper uses the distribution analysis of the various turbulence quantities and a structure analysis method to estimate the dimensions of coherent structures in the flow. Another method to analyse turbulence length scales is the estimation of the spatial 2D Auto Correlation Coefficient Function (2D ACCF). All these methods applied side by side to the PIV data increase the understanding ofthe turbulence, its scales and the nature of the coherent structures.

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