Synthetic aperture radar interferometry

By P. Rosen, S. Hensley, Ian R. Joughin, Fuk K. Li, S. Madsen, Ernesto Rodríguez, R. Goldstein. Proceedings of the IEEE, 2000

3,709 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Atmospheric Science, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/5176f5207ba955fa9a0927a242bdb7ec3cd319c0

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Citations in the corpus

A tutorial on synthetic aperture radar (2013, background): “…matrix allows to build up a powerful observation space sensitive to shape, orientation and dielectric properties of the scatterers and allows the development of physical models for the identification and/or separation of scattering mechanisms occurring inside the same resolution cell [1].”
Interferometric point target analysis for deformation mapping (2003, background): “Repeat-pass space-borne interferometric SAR is a powerful technique for the observation of land surface deformation [1].”
A Tutorial on Speckle Reduction in Synthetic Aperture Radar Images (2013, methodology): “In fact, coherent processing of data in complex format does not increase the signal-to-noise ratio (SNR), but only the coherence [13] of the interferogram and thus it is used in SAR interferometry [14].”
A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms (2002, background): “As far as the decorrelation phenomena are concerned, we remark that they are significantly mitigated by the complex multilook operation [21] carried out within the DIFSAR”
TanDEM-X: A Satellite Formation for High-Resolution SAR Interferometry (2006, neutral): “The Shuttle Radar Topography Mission (SRTM) [6]–[8] had the challenging goal to meet the requirements for a homogeneous and reliable DEM fulfilling the DTED-2 specification.”
Submillimeter Accuracy of InSAR Time Series: Experimental Validation (2007, background): “A S WELL known, temporal and geometric decorrelation represents the most important limiting factor in synthetic aperture radar interferometry (InSAR) [1].”
Radar Remote Sensing of Urban Areas (2010, methodology): “The potential of radar remote sensing to detect and monitor small magnitude soil movement by Interferometry was investigated quite early (Rosen et al. 2000).”
Spaceborne, UAV and ground-based remote sensing techniques for landslide mapping, monitoring and early warning (2017, background): “A suitable approach to exploit phase variation between two consecutive radar images acquired over the same target is the Differential Interferometric SAR (D-InSAR) (Bamler and Hartl, 1998; Rosen et al., 2000).”
The Shuttle Radar Topography Mission (2007, methodology): “Massonnet, 1997; Madsen and Zebker, 1998; Rosen et al., 2000 ].”
Gravity and magma induced spreading of Mount Etna volcano revealed by satellite radar interferometry (2004, methodology): “[4] Interferometric synthetic aperture radar (InSAR) is a technique for detecting centimeter level surface displacements at 50–100 m sampling over 100 km spatial scales [Rosen et al., 2000].”
Remote sensing methods for power line corridor surveys (2016, methodology): “…different perspectives, and having a geometric baseline (distance between satellites) of tens or hundreds of metres, are used, and the pixel-by-pixel phase differences between the images are converted into elevation differences of the terrain (Massonnet and Feigl, 1998; Rosen et al., 2000).”
Interferometric Processing of Sentinel-1 TOPS Data (2016, background): “The different acquisition geometries for an interferometric pair introduce spectral decorrelation [38].”
A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters (2009, background): “Differential interferometry (DInSAR) calculates the phase difference between SAR images acquired before and after an event or some other period when deformation has occurred (Massonnet and Feigl, 1998; Rosen et al., 2000).”