In this study, we developed a program to analyze the time-frequency spectrum of seismology events using MATLAB software. Among all the time-frequency analysis tools, we selected short-time Fourier transform (STFT) owing to its computational simplicity, adequate time and frequency resolution, and absence of undesirable cross terms. One disadvantage of STFT is the tradeoff between window length and time and frequency resolution. In order to determine the optimal window length, we wrote the code according to the sample rate of data records. We collected 82 broadband records, including data of 27 stations, of 5 natural earthquakes and 5 explosion events that occurred in the capital area between 2006 and 2008 having a magnitude in the range of 2.4 to 2.7. For the sake of convenience, we selected five pairs of events, each pair with one natural earthquake and one explosion event at similar epicenter distance, and analyzed the time-frequency spectrum. We plotted the time-frequency spectrum for each record with its original waveform and Fourier spectrum including the three components and their combination. Different time-frequency patterns exist for natural earthquakes and explosion events. In the first place, more peaks can be seen in the natural earthquake time-frequency spectrum, while the explosion events spectrum has fewer peaks. In the second place, the peaks of natural earthquakes are located in a broad frequency band, whereas the peaks of explosion time-frequency spectrum are concentrated in a narrow area. We analyzed all the data, not restricted to the five pairs of events, and the time-frequency spectrum pattern was found to be consistent. However, this pattern may be applicable only in the capital area because the explosion techniques are fairly complicated. The operator can use completely different explosion plans, and different local seismological wave propagation models produce diverse wave fields. When compared with Fourier analysis, the time-frequency spectrum, which is the time domain expansion of Fourier Spectrum, provides more information.