There has been abundant data saved in time series three-dimensional fluorescence spectroscopy, which is helpful to the qualitative and quantitative analysis of organic matter. However, redundant information also complicates the analysis and decreases the computation efficiency. Based on time-frequency of time series three-dimensional fluorescence spectroscopy, three-dimensional fluorescence spectroscopy is compressed with cluster analysis and 2-D wavelet transform. Some key factors, such as sample distance, inter-calss distance, composite correlation coefficient and R-square stastic, are discussed. The introductions of correlation coefficient and R-square statistic not only improve the precision of cluster analysis but also reduce the data for 2-D wavelet transform. Experiment results show that the important information in the original data is still kept in the compressed time series three-dimensional fluorescence spectroscopy.