A long-term landslide on the Huafan University campus in Taiwan, observed since 1990, lacks reliable monitoring data post-2018 due to equipment maintenance issues. This study employs multitemporal interferometry (MTI) using Sentinel-1 SAR images from 2014–2019 to monitor the landslide. MTI reveals consistent slow-moving areas with previous studies, indicating gravity-induced deformation and seasonal surface fluctuations linked to precipitation. This technique compensates for the lack of data and aids in evaluating and monitoring landslides for potential early warnings.
We investigate a slow-moving landslide in southern Taiwan using satellite radar data. By applying a technique called Persistent Scatterer Interferometry (PSI), we can detect very small ground movements over time with millimeter-level precision. Using five years of satellite observations (2018–2023), we find that the slope is moving slowly—only a few millimeters per year in both horizontal and vertical directions. We confirm these results with field measurements. Our study shows that combining satellite monitoring with open-source tools provides an effective and low-cost way to track landslides, helping improve hazard assessment and early warning in mountainous areas.
Satellite-detected land surface temperature (LST) and seismic records are used to study the volcanic activity of Tatun Volcanic Group. Analyzing four decades of LST and three decades of earthquake magnitude data reveals a correlation between LST trends and energy released from volcanic earthquakes, validating the connection between surface temperatures and volcanic activity.
