A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms

By Riccardo Lanari, Oscar Mora, M. Manunta, Jordi J. Mallorquí, P. Berardino, Eugenio Sansosti. IEEE Transactions on Geoscience and Remote Sensing, 2004

993 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Atmospheric Science, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/f0a799d73e3cbc8224e32c36a46d4074b8d037ea

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Citations in the corpus

On the Extension of the Minimum Cost Flow Algorithm for Phase Unwrapping of Multitemporal Differential SAR Interferograms (2006, methodology): “This clearly indicates the significant impact of the 2π integer correction component within the proposed unwrapping procedure.”
A multi‐temporal InSAR method incorporating both persistent scatterer and small baseline approaches (2008, methodology): “Lanari et al. [2004] have implemented a method that first identifies multi-looked SDFP pixels and then uses these to identify single-look SDFP pixels in a further step.”
Small baseline InSAR time series analysis: Unwrapping error correction and noise reduction (2019, background): “A disconnected network of interferograms with multiple interferogram subsets biases the time-series estimation, especially when there is no overlap in temporal or spatial baseline among interferogram subsets (Lanari et al., 2004; L�opez-Quiroz et al., 2009).”
A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR (2011, background): “Then, for a DS, we are somewhat forced to deal with N (N − 1)/2 interferometric phase values and not simply N , as with PS. Incidentally, this is reason why in the SBAS algorithm, even after successfully phase unwrapping a sub-set of possibly highcoherence interferograms connecting all images within”
Persistent Scatterer Interferometry: A review (2016, background): “This aspect was resolved in an extended SBAS version that works with full-resolution data (Lanari et al., 2004a).”
Spaceborne, UAV and ground-based remote sensing techniques for landslide mapping, monitoring and early warning (2017, methodology): “In the past years, several MIT approaches have been developed such as: the Permanent Scatterers Interferometry, named PSInSAR™ (Ferretti et al., 2011; Colesanti et al., 2003), the SqueeSAR™ (Ferretti et al., 2011), the Stanford Method for Persistent Scatterers StaMPS (Hooper et al., 2004; Hooper et ”
A tutorial on synthetic aperture radar (2013, neutral): “…approaches is the selection of the image pixels with enough quality to be used in the estimation process, being the most commonly approaches the ones based on the amplitude dispersion, i.e., the so-called permanent scatterers (PS) technique [17], [69], or on the interferometric coherence [91]–[93].”