Landslide monitoring with interferometric SAR in Liugui, a vegetated area

Tian-Yuan Shih*, Huijung Wang, Kuo-Wei Li, Jyh-Jong Liao, Yii-Wen Pan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Interferometric SAR analysis with a time series of images obtained from satellite has been proven to be a useful monitoring scheme for geomorphological changes, particularly related to the vertical dimension. The success of this technique relies on the coherence between the images. This imposes severe challenges for applications in vegetated areas. In this study, the landslide process of a site located in Liugui, southern Taiwan, is investigated by a time series of SAR images collected from ALOS PALSAR and Sentinel 1A. This landslide monitoring site is heavily vegetated. From the Persistent Scattering (PS) analysis, ALOS PALSAR presented more extracted points. The wavelength of the band may be a decisive factor. The time series of ALOS images spans across the deadliest typhoon impacted Taiwan in recorded history, Typhoon Morakot on 8 August 2009. It is clear that there are more PS points extracted from the time series after the event as compared to before Typhoon Morakot. This is largely explained by the increase in the amount of bare earth after the disaster. From the interferometric SAR analysis, the development of headward erosion could be observed. Although the number of PS points is limited, the understanding of erosion and landslide progress in the area could still be improved while integrating with the digital elevation model collected with airborne lidar, historic aerial photos, and images collected with UAS (Unmanned Aviation Systems). Together with the in situ measurements, the colluvium depth ranges from 2 - 40 m in the area. The surface instability is expected to persist.

Original languageAmerican English
Pages (from-to)521-530
Number of pages10
JournalTerrestrial, Atmospheric and Oceanic Sciences
Volume30
Issue number4
DOIs
StatePublished - Aug 2019

Keywords

  • Geomorphological features
  • Persistent scatterer
  • Remote sensing

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