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Landslide modeling based on seismic signal characteristics is an effective method to study landslide evolution. The scientific challenge lies in how to systematically characterize and reconstruct the entire landslide evolution process using the recorded seismic data. We selected the 2017 "6.24" Xinmo landslide as a case study. Empirical mode decomposition (EMD) is used to analyze the seismic signals from 14 seismic stations near the landslide area. Numerical simulations using two-dimensional discrete element methods (DEM) are performed to simulate landslide dynamics using the calculated kinetic energy profile. After analyzing the short-time Fourier transform (STFT) and fast Fourier transform (FFT) characteristics of the signal, the landslide process is reconstructed and compared with the DEM simulation. The landslide process is observed to consist of a stationary stage, slipping stage, transition stage, entrainment-transportation stage, and a deposition stage. This is the first study that uses seismic signals to identify a transition stage, which is a feature that is difficult to constrain from field survey and analysis alone. Landslide development and movement in the transition stage are discussed considering the sedimentology of the study area. This study provides improved theoretical guidance for the reconstruction and characterization of landslide processes by seismic signals. • Seismic signals generated by the Xinmo landslide (Sichuan - China) were analyzed. • 5 stages of landslide were recognized from spectral variations of seismic recording. • One transition stage was identified between first slipping and entrainment stage. • Discrete element simulations supported the landslide process reconstruction. [ABSTRACT FROM AUTHOR]