MULTI-SENSOR GEODETIC APPROACH FOR LANDSLIDE DETECTION AND MONITORING
- 1Indian Institute of Technology, Civil Engineering, India
- 2Motilal Nehru National Institute of Technology, GIS Cell, India
Keywords: Landslide monitoring, geodetic techniques, LiDAR, GNSS network adjustment
Abstract. The lesser Himalayan region is mostly affected by landslide events occurring due to rainfall, steep slopes and presence of tectonic activity beneath, causing loss of life and property. Some critical zones in the region have encountered recurring landslides over the past and need careful investigation for better planning and rescue operations. This research work presents a geodetic framework comprising multiple sensors to monitor the Sirobagarh landslide in Uttarakhand, India, which is affected by recurring landslides. Three field visits were made to this site for geodetic data collection using Terrestrial Laser Scanner (TLS), Global Navigation Satellite System (GNSS) and Robotic Total Station (RTS). Co-registration and vegetation removal of the TLS scans corresponding to the three visits resulted in generation of three Digital Elevation Models (DEM), which were differenced to estimate temporal movement of the landslide scarp. DEM differences indicate subsidence of the landslide scarp with vertical displacement values ranging from −0.05 to −5.0 m. Rainfall induced debris flow is one of the prominent reason for large displacement magnitude (∼5 m) in the upper landslide scarp. Horizontal displacement estimates obtained by geodetic network analysis of six GNSS stations installed on the study site show movement towards the Alaknanda river. The maximum horizontal and vertical displacement values for the GNSS stations were 0.1305 m and −2.1315 m respectively. Similar pattern is observed by displacement measurements of RTS target reflectors installed on a retaining wall constructed to arrest the debris flow approaorching the National Highway. The displacement estimates obtained from the sensors applied in this study indicate subsidence of the landslide scarp and surroundings. More time series observations can provide better understanding of the overall deformation process.