In Taiwan, three quarters of the island comprises hilly and mountainous areas, with small drainage basins and steep stream gradients. Affected by active tectonics, frequent typhoons and storms, and human activities over mountainous ranges, landslides are frequently induced during typhoon seasons. To detect landslide hazards for a wide region, remotely sensed data has been applied due to its efficiency and low cost. However, the cloudy condition during a typhoon may limit the application of optical data. For an emergent monitoring task, Synthetic Aperture Radar (SAR) is therefore a suitable tool for detecting landslides in cloudy and rainy weather. This three-year project aims to develop a automatic landslide monitoring system, by analyzing the texture of SAR images and the spatial autocorrelation property to identify the clustering of new landslides. In this study freely available Sentinel-1A SAR imagery will be collected to construct the monitoring system.
|Effective start/end date||1/08/18 → 31/07/19|
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):