Detection of seismic events at or below the noise level is enabled by the use of dense arrays of receivers and corresponding advances in data analysis methods. It is not only important to detect tectonic events, but also events from man-made, non-earthquake sources and events that originate from coupling between the solid Earth and the atmosphere. In urban environments with high ambient noise levels the effectiveness of event detection methods is unclear, particularly when deployment restrictions result in an irregular receiver array geometry. Here, we deploy a dense nodal array for 1 month in the highly populated city state of Singapore. We develop a new detection method based on image processing that we call spectrogram stacking, which detects anomalous, coherent spectral energy across the array. It simultaneously detects multiple classes of signal with differing spectral content and aids event classification, so it is particularly useful for signal exploration when signal characteristics are unknown. Our approach detects more local events compared to the traditional short-term average over long-term average and waveform similarity methods, while all methods detect similar numbers of teleseismic and regional earthquakes. Local events are principally man-made non-earthquake sources, with several events from the same location exhibiting repeating waveforms. The closest earthquake occurs in peninsular Malaysia, in an area where no earthquakes have previously been detected. We also detect ground motion over a wide frequency range from discrete thunder events that show complex coupling between acoustic and elastic wavefield propagation. We suggest that care should be taken deciphering local high-frequency tectonic events in areas prone to thunder storms.
Image processing, Induced seismicity, Seismicity and tectonics, Time-series analysis