Objectives  Traditional methods for remote sensing interpretation are difficult to identify historical geohazards covered by dense vegetation. For the purpose of interpreting the pre-seismic geohazards in the area of Panda Sea, Jiuzhaigou, and analyze the characteristics and distribution law, we propose a new methodology for geomorphologic identification masks and remote sensing interpretation regarding collapse, landslide and debris flow.

  Methods  Based on high-resolution LiDAR(light detection and ranging) data and data processing method of RRIM(red relief image map). RRIM is formed by the superposition of positive openness, negative openness and slope. RRIM method can supplement the shortcomings of the existing terrain visualization techniques, and apply the influence of environmental light to the terrain display, so that the visual interpretation can clearly identify the differences of landforms, and is more conducive to the identification and accurate interpretation of geohazards in mountainous areas.

  Results  Aiming at the Panda Sea area, which is the most seriously affected by Jiuzhaigou earthquake, the RRIM method is used to interpret the pre-seismic geohazards. A total of 311 pre-earthquake pre-seismic geohazards are interpreted and classified according to their characteristics, then are analyzed for spatial distribution.

  Conclusions  The verified results show that the high-resolution LiDAR data combined with RRIM is of great significance to improve the interpretation of geohazards of mountainous area with dense vegetation coverage, and provide data support for the geohazards prevention and risk assessment of the earthquake area in Jiuzhaigou.