Synthetic aperture radar interferometry

Rosen, P. A.; Hensley, Scott; Joughin, Ian; Li, F.K.; Madsen, S.N.; Rodríguez, Ernesto; Goldstein, Robert S.

doi:10.1109/5.838084

Cited by 2,109 publications

(1,398 citation statements)

References 153 publications

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“…When dealing with sequences of SAR images, the decorrelation effects can be mitigated by selecting, among all the possible interferometric data pairs, only those characterized by small spatial and temporal separations (baselines). In addition, to mitigate decorrelation in the computed interferograms and to reduce the amount of data to be processed, complex multi-look (Rosen et al 2000) and additional noisefiltering Werner 1998, Baran et al 2003) operations are also typically *Corresponding author. Email: lanari.r@irea.cnr.it carried out for each SAR interferogram.…”

Section: Introductionmentioning

confidence: 99%

A simple solution to mitigate noise effects in time-redundant sequences of small baseline multi-look DInSAR interferograms

Yang

Pepe

Manzo

et al. 2013

Remote Sensing Letters

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Letters, 2013 Vol. 4, No. 6, 609-618, http://dx.doi.org/10.1080/2150704X.2013 A simple solution to mitigate noise effects in time-redundant sequences of small baseline multi-look DInSAR interferograms We present a simple and effective filtering algorithm to mitigate noise effects in a time-redundant sequence of multi-look small baseline (SB) differential synthetic aperture radar (SAR) interferograms by exploiting the temporal relationships among the selected interferometric data pairs. The proposed method relies on the estimation of the (wrapped) filtered phase terms associated to each SAR acquisition; this result is achieved via a non-linear minimization procedure which is applied to the phase signal of conventional multi-look interferograms without any pixel selection process, and with no a-priori information on the statistics of the involved complex-valued SAR images. Following their estimation, the phase images are paired to reconstruct a new sequence of filtered SB differential interferograms, which are used to generate surface deformation products, such as deformation velocity maps and displacement time-series. The filtering algorithm effectiveness is demonstrated by analysing a set of SAR images acquired by the ENVISAT sensor from 2003 to 2010 over the city of Shanghai, China.

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Section: Introductionmentioning

confidence: 99%

A simple solution to mitigate noise effects in time-redundant sequences of small baseline multi-look DInSAR interferograms

Yang

Pepe

Manzo

et al. 2013

Remote Sensing Letters

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“…SAR interferometry uses the phase differences between two radar images acquired with a small base-to-height ratio. These phase differences are the photogrammetric equivalent to a "parallax" measurement allowing retrieval of topography (Rosen et al, 2000). We use the SRTM3, V2 without void filling (NASA et al, 2002).…”

Section: Interferometric Srtm Demmentioning

confidence: 99%

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

2011

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Abstract.There are an increasing number of digital elevation models (DEMs) available worldwide for deriving elevation differences over time, including vertical changes on glaciers. Most of these DEMs are heavily post-processed or merged, so that physical error modelling becomes difficult and statistical error modelling is required instead. We propose a three-step methodological framework for assessing and correcting DEMs to quantify glacier elevation changes: (i) remove DEM shifts, (ii) check for elevation-dependent biases, and (iii) check for higher-order, sensor-specific biases. A simple, analytic and robust method to co-register elevation data is presented in regions where stable terrain is either plentiful (case study New Zealand) or limited (case study Svalbard). The method is demonstrated using the three global elevation data sets available to date, SRTM, ICESat and the ASTER GDEM, and with automatically generated DEMs from satellite stereo instruments of ASTER and SPOT5-HRS. After 3-D co-registration, significant biases related to elevation were found in some of the stereoscopic DEMs. Biases related to the satellite acquisition geometry (along/cross track) were detected at two frequencies in the automatically generated ASTER DEMs. The higher frequency bias seems to be related to satellite jitter, most apparent in the backlooking pass of the satellite. The origins of the more significant lower frequency bias is uncertain. ICESat-derived elevations are found to be the most consistent globally available elevation data set available so far. Before performing regional-scale glacier elevation change studies or mosaicking DEMs from multiple individual tiles (e.g. ASTER GDEM), we recommend to co-register all elevation data to ICESat as a global vertical reference system.

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“…The interferograms were generated by computing the phase difference between the co-registered SAR images pairs [58], and by subtracting the relevant topographic phase contributions, as synthesized using the Shuttle Radar Topography Mission (SRTM) DEM (with a spatial sampling of 90 m × 90 m) of the area [59]. To mitigate the effects of the decorrelation noise, we also independently carried out (on each single interferogram) a complex multilook operation [60] (with 30 looks in the azimuth and range directions for the CSK case, and with 20 looks in the azimuth, and 4 looks in the range direction for the ASAR/ENVISAT case, thus resulting, for both SAR datasets, in a radar pixel dimension of about 90 × 90 m). To each interferogram, a noise-filtering operation [61,62] was also applied.…”

Section: Sbas-dinsar Analysismentioning

confidence: 99%

The Use of C-/X-Band Time-Gapped SAR Data and Geotechnical Models for the Study of Shanghai’s Ocean-Reclaimed Lands through the SBAS-DInSAR Technique

et al. 2016

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Abstract:In this work, we investigate the temporal evolution of ground deformation affecting the ocean-reclaimed lands of the Shanghai (China) megacity, from 2007 to 2016, by applying the Differential Synthetic Aperture Radar Interferometry (DInSAR) technique known as the Small BAseline Subset (SBAS) algorithm. For the analysis, we exploited two sets of non-time-overlapped synthetic aperture radar (SAR) data, acquired from 2007 to 2010, by the ASAR/ENVISAT (C-band) instrument, and from 2014 to 2016 by the X-band COSMO-SkyMed (CSK) sensors. The long time gap (of about three years) existing between the available C-and X-band datasets made the generation of unique displacement time-series more difficult. Nonetheless, this problem was successfully solved by benefiting from knowledge of time-dependent geotechnical models, which describe the temporal evolution of the expected deformation affecting Shanghai's ocean-reclaimed platforms. The combined ENVISAT/CSK (vertical) deformation time-series were analyzed to gain insight into the future evolution of displacement signals within the investigated area. As an outcome, we find that ocean-reclaimed lands in Shanghai experienced, between 2007 and 2016, average cumulative (vertical) displacements extending down to 25 centimeters.

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Synthetic aperture radar interferometry

Cited by 2,109 publications

References 153 publications

A simple solution to mitigate noise effects in time-redundant sequences of small baseline multi-look DInSAR interferograms

A simple solution to mitigate noise effects in time-redundant sequences of small baseline multi-look DInSAR interferograms

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

The Use of C-/X-Band Time-Gapped SAR Data and Geotechnical Models for the Study of Shanghai’s Ocean-Reclaimed Lands through the SBAS-DInSAR Technique

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