Time-dependent volcano source monitoring using interferometric synthetic aperture radar time series: A combined genetic algorithm and Kalman filter approach

2010 ◽  
Vol 115 (B10) ◽  
Author(s):  
M. Shirzaei ◽  
T. R. Walter
Keyword(s):  
Genetic Algorithm ◽  
Time Series ◽  
Kalman Filter ◽  
Synthetic Aperture Radar ◽  
Source Monitoring ◽  
Time Dependent ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Filter Approach ◽  
Aperture Radar

scholarly journals Removal of systematic seasonal atmospheric signal from interferometric synthetic aperture radar ground deformation time series

2014 ◽  
Vol 41 (17) ◽  
pp. 6123-6130 ◽  
Author(s):  
Sergey V. Samsonov ◽  
Alexander P. Trishchenko ◽  
Kristy Tiampo ◽  
Pablo J. González ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Synthetic Aperture Radar ◽  
Ground Deformation ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Aperture Radar

scholarly journals Landslide Deformation Monitoring by Adaptive Distributed Scatterer Interferometric Synthetic Aperture Radar

2019 ◽  
Vol 11 (19) ◽  
pp. 2273 ◽  
Author(s):  
Hongguo Jia ◽  
Hao Zhang ◽  
Luyao Liu ◽  
Guoxiang Liu
Keyword(s):  
Time Series ◽  
Synthetic Aperture Radar ◽  
Deformation Monitoring ◽  
Synthetic Aperture ◽  
Economic Losses ◽  
Interferometric Synthetic Aperture Radar ◽  
Mountainous Areas ◽  
Landslide Area ◽  
Landslide Deformation ◽  
Aperture Radar

Landslide is the second most frequent geological disaster after earthquake, which causes a large number of casualties and economic losses every year. China frequently experiences devastating landslides in mountainous areas. Interferometric Synthetic Aperture Radar (InSAR) technology has great potential for detecting potentially unstable landslides across wide areas and can monitor surface displacement of a single landslide. However traditional time series InSAR technology such as persistent scatterer interferometry (PSI) and small-baseline subset (SBAS) cannot identify enough points in mountainous areas because of dense vegetation and steep terrain. In order to improve the accuracy of landslide hazard detection and the reliability of landslide deformation monitoring in areas lacking high coherence stability point targets, this study proposes an adaptive distributed scatterer interferometric synthetic aperture radar (ADS-InSAR) method based on the spatiotemporal coherence of the distributed scatterer (DS), which automatically adjusts its detection threshold to improve the spatial distribution density and reliability of DS detection in the landslide area. After time series network modeling and deformation calculation of the ADS target, the displacement deformation of the landslide area can be accurately extracted. Shuibuya Town in Enshi Prefecture, Hubei Province, China, was used as a case study, along with 18 Sentinal-1A images acquired from March 2016 to April 2017. The ADS-InSAR method was used to obtain regional deformation data. The deformation time series was combined with hydrometeorological and related data to analyze landslide deformation. The results show that the ADS-InSAR method can effectively improve the density of DS distribution, successfully detect existing ancient landslide groups and determine multiple potential landslide areas, enabling early warning for landslide hazards. This study verifies the reliability and accuracy of ADS-InSAR for landslide disaster prevention and mitigation.

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