Abstract: Guizhou Province is characterized by a complex geological structure and rugged topography, resulting in frequent geological hazards such as landslides and rockfalls. Traditional methods for identifying geohazards are costly in manpower and resources and limited in spatial coverage. Therefore, the development of high-precision, wide-area surface deformation monitoring technologies is crucial for disaster risk prevention and mitigation. In this study, L-band SAR data from the Lutan-1 satellite were employed using Differential Synthetic Aperture Radar Interferometry (D-InSAR) technique. A total of 124 ascending and descending orbit images covering 36 documented disaster sites in Guizhou from February to September 2024 were selected. By applying a series of precision optimization strategies—including optimal interferometric pair selection, systematic error correction, and atmospheric/ionospheric phase correction—precursory surface deformation signals prior to the hazard events were systematically extracted and identified. The analysis of the 36 sites reveals that the Lutan-1 InSAR technique achieved a pre-disaster deformation identification rate of 55.56%. These findings demonstrate the significant application potential of the Lutan-1 satellite for early identification of geohazards in complex mountainous regions. Its L-band data can effectively penetrate vegetation to capture critical precursory deformation signals, providing key technical support and a practical basis for regional disaster prevention and mitigation.