Landslide Detection Using Multi-temporal Sentinel-1 C-band SAR Imagery in Northern Taiwan
Abstract
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. In this study, multi-temporal SAR images were analyzed to identify the backscattering changes over landslide surfaces and incorporated into a supervised image classifier. Landslides induced by Typhoon Soudelor (2015) in Northern Taiwan were collected to perform the analysis. The Sentinel-1 C-band SAR images from different observing modes (ascending and descending) were fused to reduce effects from shadow and layover in the mountainous region. Further details and preliminary results will be presented in the meeting. This study suggests that an effective and useful landslide detection method, based on SAR data, is expected to serve as a part of rapid response system of landslide monitoring, when optical data is not timely available.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFMNH14A..07C
- Keywords:
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- 9805 Instruments useful in three or more fields;
- GENERAL OR MISCELLANEOUS;
- 1920 Emerging informatics technologies;
- INFORMATICS;
- 4314 Mathematical and computer modeling;
- NATURAL HAZARDS;
- 4333 Disaster risk analysis and assessment;
- NATURAL HAZARDS