2007
DOI: 10.1007/s00024-007-0192-9
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An Overview of the Small BAseline Subset Algorithm: a DInSAR Technique for Surface Deformation Analysis

Abstract: We present an overview of the Differential SAR Interferometry algorithm referred to as Small BAseline Subset (SBAS) technique, that allows us to detect surface deformation and to analyze their space-time characteristics. Following the description of the main theoretical aspects of the algorithm, we present several results obtained by applying the SBAS approach in selected case studies relevant to phenomena affecting volcanic areas (Campi Flegrei caldera and Somma-Vesuvio complex, Italy), aquifers (Santa Clara … Show more

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Cited by 283 publications
(153 citation statements)
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“…The presented DInSAR analysis exploits a sequence of SB time-redundant differential interferograms, selected by limiting the maximum perpendicular baseline and the relevant time span of the SAR data pairs to 400 m and 2000 days, respectively. Note that these threshold values have been derived through extensive experimental analyses carried out in several geophysical contexts by exploiting the SBAS approach (Lanari et al 2007 and references therein, Manzo et al 2012 and references therein). As a result, we retrieved a network of 664 differential SAR interferograms (see figure 1), which were computed by performing a complex multi-look operation with 4 looks in the range direction and 20 looks in the azimuth one (Bamler and Hartl 1998, Rosen et 2000, Lanari et al 2007), leading to a resulting pixel dimension of about 100 m × 100 m. For the interferogram generation (Gabriel et al 1989), the topographic phase contributions were removed by using precise satellite orbit information and a threearcsecond shuttle radar topography mission (SRTM) digital elevation model (DEM) of the region.…”
Section: Resultsmentioning
confidence: 99%
See 3 more Smart Citations
“…The presented DInSAR analysis exploits a sequence of SB time-redundant differential interferograms, selected by limiting the maximum perpendicular baseline and the relevant time span of the SAR data pairs to 400 m and 2000 days, respectively. Note that these threshold values have been derived through extensive experimental analyses carried out in several geophysical contexts by exploiting the SBAS approach (Lanari et al 2007 and references therein, Manzo et al 2012 and references therein). As a result, we retrieved a network of 664 differential SAR interferograms (see figure 1), which were computed by performing a complex multi-look operation with 4 looks in the range direction and 20 looks in the azimuth one (Bamler and Hartl 1998, Rosen et 2000, Lanari et al 2007), leading to a resulting pixel dimension of about 100 m × 100 m. For the interferogram generation (Gabriel et al 1989), the topographic phase contributions were removed by using precise satellite orbit information and a threearcsecond shuttle radar topography mission (SRTM) digital elevation model (DEM) of the region.…”
Section: Resultsmentioning
confidence: 99%
“…Note that these threshold values have been derived through extensive experimental analyses carried out in several geophysical contexts by exploiting the SBAS approach (Lanari et al 2007 and references therein, Manzo et al 2012 and references therein). As a result, we retrieved a network of 664 differential SAR interferograms (see figure 1), which were computed by performing a complex multi-look operation with 4 looks in the range direction and 20 looks in the azimuth one (Bamler and Hartl 1998, Rosen et 2000, Lanari et al 2007), leading to a resulting pixel dimension of about 100 m × 100 m. For the interferogram generation (Gabriel et al 1989), the topographic phase contributions were removed by using precise satellite orbit information and a threearcsecond shuttle radar topography mission (SRTM) digital elevation model (DEM) of the region. The multi-look interferograms were also pre-filtered by applying the well-known approach described in Goldstein and Werner (1998), and subsequently processed by following the lines of the filtering approach described in the previous section.…”
Section: Resultsmentioning
confidence: 99%
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“…The Small Baseline Subset (SBAS) method (Berardino et al, 2002;Lanari et al, 2007) is a small baseline technique that uses stacks of differential interferometric synthetic aperture radar (DInSAR) observations of the same location to estimate slow linear and non-linear motion of the land surface to millimetric precision. The method, especially when using multilooked, low-pass interferograms, is relatively easy to implement and is excellent for the investigation of large spatial scale distortions.…”
Section: Introductionmentioning
confidence: 99%