scholarly journals InSAR processing for the recognition of landslides

2008 ◽  
Vol 14 ◽  
pp. 189-194 ◽  
Author(s):  
B. Riedel ◽  
A. Walther
Keyword(s):  
Synthetic Aperture Radar ◽  
Radar Interferometry ◽  
Sar Interferometry ◽  
Surface Processes ◽  
Synthetic Aperture ◽  
Earth Surface ◽  
Established Method ◽  
Movement Rates ◽  
Synthetic Aperture Radar Interferometry ◽  
Strong Potential

Abstract. Synthetic Aperture Radar Interferometry (InSAR) is an established method for the detection and monitoring of earth surface processes. This approach has been most successful where the observed area fulfills specific requirements, such as sufficient backscattering, flat slope gradients or very slow changes of vegetation. We investigated the capability of two different InSAR techniques and achieved good results for the recognition of landslides in China and Greece that compared well with geodetic derived movement rates. This demonstrates the strong potential of SAR Interferometry for the detection of landslides and earth surface movements.

Deformation information extraction method based on differential synthetic aperture radar interferometry

2020 ◽  
Vol 39 (4) ◽  
pp. 5311-5318
Author(s):  
Zhengquan Hu ◽  
Yu Liu ◽  
Xiaowei Niu ◽  
Guoping Lei
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Adaptive Filtering ◽  
Extraction Method ◽  
Deformation Monitoring ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Filtering Method ◽  
Synthetic Aperture Radar Interferometry ◽  
Aperture Radar

As aerospace technology, computer technology, network communication technology and information technology become more and more perfect, a variety of sensors for measurement and remote sensing are constantly emerging, and the ability to acquire remote sensing data is also continuously enhanced. Synthetic Aperture Radar Interferometry (InSAR) technology greatly expands the function and application field of imaging radar. Differential InSAR (DInSAR) developed based on InSAR technology has the advantages of high precision and all-weather compared with traditional measurement methods. However, DInSAR-based deformation monitoring is susceptible to spatiotemporal coherence, orbital errors, atmospheric delays, and elevation errors. Since phase noise is the main error of InSAR, to determine the appropriate filtering parameters, an iterative adaptive filtering method for interferogram is proposed. For the limitation of conventional DInSAR, to improve the accuracy of deformation monitoring as much as possible, this paper proposes a deformation modeling based on ridge estimation and regularization as a constraint condition, and introduces a variance component estimation to optimize the deformation results. The simulation experiment of the iterative adaptive filtering method and the deformation modeling proposed in this paper shows that the deformation information extraction method based on differential synthetic aperture radar has high precision and feasibility.

Detection of geohazards in the Bailong River Basin using synthetic aperture radar interferometry

Landslides ◽  
2015 ◽  
Vol 13 (5) ◽  
pp. 1273-1284 ◽  
Author(s):  
Yi Zhang ◽  
Xingmin Meng ◽  
Guan Chen ◽  
Liang Qiao ◽  
Runqiang Zeng ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
River Basin ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Interferometry ◽  
Bailong River Basin ◽  
Aperture Radar

scholarly journals Iceberg topography and volume classification using TanDEM-X interferometry

2019 ◽  
Vol 13 (7) ◽  
pp. 1861-1875 ◽  
Author(s):  
Dyre O. Dammann ◽  
Leif E. B. Eriksson ◽  
Son V. Nghiem ◽  
Erin C. Pettit ◽  
Nathan T. Kurtz ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Maximum Height ◽  
Polar Regions ◽  
Classification Approach ◽  
Single Pass ◽  
Synthetic Aperture Radar Interferometry ◽  
Marine Habitats ◽  
Maritime Operations

Abstract. Icebergs in polar regions affect water salinity, alter marine habitats, and impose serious hazards on maritime operations and navigation. These impacts mainly depend on the iceberg volume, which remains an elusive parameter to measure. We investigate the capability of TanDEM-X bistatic single-pass synthetic aperture radar interferometry (InSAR) to derive iceberg subaerial morphology and infer total volume. We cross-verify InSAR results with Operation IceBridge (OIB) data acquired near Wordie Bay, Antarctica, as part of the OIB/TanDEM-X Antarctic Science Campaign (OTASC). While icebergs are typically classified according to size based on length or maximum height, we develop a new volumetric classification approach for applications where iceberg volume is relevant. For icebergs with heights exceeding 5 m, we find iceberg volumes derived from TanDEM-X and OIB data match within 7 %. We also derive a range of possible iceberg keel depths relevant to grounding and potential impacts on subsea installations. These results suggest that TanDEM-X could pave the way for future single-pass interferometric systems for scientific and operational iceberg mapping and classification based on iceberg volume and keel depth.

scholarly journals Radar Interferometry: 20 Years of Development in Time Series Techniques and Future Perspectives

2020 ◽  
Vol 12 (9) ◽  
pp. 1364 ◽  
Author(s):  
Dinh HO TONG MINH ◽  
Ramon Hanssen ◽  
Fabio Rocca
Keyword(s):  
Time Series ◽  
Big Data ◽  
Synthetic Aperture Radar ◽  
Radar Interferometry ◽  
Sar Interferometry ◽  
Synthetic Aperture ◽  
Future Perspectives ◽  
Interferometric Sar ◽  
Deformation Measurements ◽  
Over Time

The research and improvement of methods to be used for deformation measurements from space is a challenge. From the previous 20 years, time series Synthetic Aperture Radar (SAR) interferometry techniques have proved for their ability to provide millimeter-scale deformation measurements over time. This paper aims to provide a review of such techniques developed in the last twenty years. We first recall the background of interferometric SAR (InSAR). We then provide an overview of the InSAR time series methods developed in the literature, describing their principles and advancements. Finally, we highlight challenges and future perspectives of the InSAR in the Big Data era.

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