Observation and Mapping of Complex Landslides Using Field Investigation and Remote Sensed Data

Abstract

Landslide is always not hazard until mankind development in highly potential area. The study not only tries to map deep seated landslide but also monitoring before the initiation of landslide. Study area in central Taiwan is selected and the geological condition is slate. Major direction of bedding in this area is northeast and the dip ranges from 30 degrees to 75 degrees to southeast. Several deep seated landslides were discovered in the same side of bedding from rainfall events. Several methods such as DEM observation, optical image identification, DInSAR, and monitoring instrumentations are adopted in this study. Landslides in study area are easy to observed from DEM observation and previous traditional elevation survey. However, the activity of landslides should be carefully taken into consideration. Thus SAR data utilization is adopted in this case. DInSAR and SBAS sar analysis are used in this research and ALOS/PALSAR from 2006 to 2010 is adopted. DInSAR analysis shows that landslide is possible mapped but the error is not easy to reduce. The error is possibly form several conditions such as vegetation, clouds, vapor, etc. To conquer the problem, time series analysis, SBAS, is adopted in this research. The result of SBAS in this area shows that large deep seated landslides are easy mapped and the accuracy of vertical displacement is reasonable. Moreover, a landslide area is selected to verify landslide activity in study area. Mems accelerometer is designed to monitor both static and dynamic behavior of this study area. Several events have been observed not only from rainfall but also from earthquake.