Forest Disaster and Environmental Research Department
Landslide Division aims to research scientific landslide risk management technology to protect the forest environment and public safety. We also seek to develop the techniques to employ a meteorological big database by creating a network at a national level to address climate change.
Landslide Prediction Research
We are conducting research to analyze landslide risk maps as extreme rainfall events intensify due to recent climate change. Our goal is to identify landslide-prone areasand develop and enhance technologies for producing landslide early-warning information to support residents in their preparedness and evacuation.
- Landslide susceptiblity map
Landslide susceptiblity map
- 48 hour Landslide forecast system
48 hour Landslide forecast system
- Debris flow analysis using UAV LiDAR
Debris flow analysis using UAV LiDAR
Landslide Mitigation Research
We are operating test sites for monitoring sediment discharge in forested areas to reduce the damage caused by landslides. Additionally, we are conducting research on the optimal placement and design of erosion control facilities, including check dams , to effectively mitigate landslide damage.
- Landcreep monitoring system
Landcreep monitoring system
- the analysis of the effect of erosion control facilities
the analysis of the effect of erosion control facilities
- Forest stream geomorphology analysis
Forest stream geomorphology analysis
Forest meteorology → Mountain Weather and Meteorology
We aim to establish basic information for forest disaster prevention and forest management by collecting real-time meteorological data and weather information in mountainous areas. To achieve our goal, we do research developing Automatic Mountain Meteorology Observation Stations (AMOS) and Mountain Meteorology Information Systems (MMIS).
- Mountain weather observation
Mountain weather observation
- Mountain weather observation network
Mountain weather observation network
- Mountain weather information system
Mountain weather information system