Based on the actual damage data of 7 routes (total length of about 70km) around the Aso area damaged by the 2016 Kumamoto earthquake, an attempt was made to develop a damage estimation method that combines the degree of risk and the degree of impact. The probability of collapse occurrence by risk and seismic intensity was evaluated based on the topographical and geological conditions along the road. In addition, the degree of impact based on the amount of collapsed sediment and the sediment removal time was considered. Then, using Monte Carlo simulation, a model was constructed to probabilistically calculate the location of the collapse, the scale of the collapse, and the sediment removal time (road recovery time). As a result of the verification, the actual damage situation was almost simulated, and it was shown that it is possible to quantitatively evaluate the deterioration of the road network function caused by the slope failure during the earthquake.

  Rockfall disasters have occurred frequently in recent years, and efforts to prevent rockfall are of urgent necessity. On the other hand, many sites where rockfall surveys are conducted on steep slopes, and it has been pointed out that the survey accuracy and safety issues may be reduced.

  In recent years, considerable progress has been made in the field of laser surveying, and several models of mobile laser scanners have been introduced. As of 2020, smartphones equipped with LiDAR functions, such as the Apple iPhone 12 Pro, have also become available. Accordingly, we conducted a rockfall survey utilizing such mobile laser scanners, and will provide a report of an investigation of their usability.