期刊
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
卷 60, 期 -, 页码 -出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2021.3103037
关键词
Strain; Time series analysis; Synthetic aperture radar; Coherence; Systematics; Orbits; Interferometry; Distributed scatterers (DSs); interferometric synthetic aperture radar (SAR) (InSAR); multilook interferograms; parallel small baseline subset (P-SBAS); phase inconsistencies; phase unwrapping errors; systematic bias; time series analysis
类别
资金
- Presidenza del Consiglio dei Ministri-Dipartimento della Protezione Civile (DPC) (Presidency of the Council of MinistersDepartment of Civil Protection (DPC)) through the Istituto per il Rilevamento Elettromagnetico dell'Ambiente (IREA)-Consiglio Nazional
- European Union [871121]
The authors claim that advanced differential SAR interferometry algorithms are affected by biases in generated InSAR products, recommending strategies to avoid these biases. By processing relevant dataset, they demonstrate that the claim made in the study may not be accurate in certain cases.
In a recent publication, Ansari et al. (2021) claimed (see, in particular, the Discussion and Recommendation Section in their article) that the advanced differential SAR interferometry (InSAR) algorithms for surface deformation retrieval, based on the small baseline approach, are affected by systematic biases in the generated InSAR products. Therefore, to avoid such biases, they recommended a strategy primarily focused on excluding ``the short temporal baseline interferograms and using long baselines to decrease the overall phase errors.'' In particular, among various techniques, Ansari et al. (2021) identified the solution presented by Manunta et al. (2019) as a small baseline advanced InSAR processing approach where the presence of the above-mentioned biases (referred to as a fading signal) compromises the accuracy of the retrieved InSAR deformation products. We show that the claim of Ansari et al. (2021) is not correct (at least) for what concerns the mentioned approach discussed by Manunta et al. (2019). In particular, by processing the Sentinel-1 dataset relevant to the same area in Sicily (southern Italy) investigated by Ansari et al. (2021), we demonstrate that the generated InSAR products do not show any significant bias.
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