2021 •
Comments on ``Study of Systematic Bias in Measuring Surface Deformation With SAR Interferometry''
Authors:
Claudio De Luca, Francesco Casu, Michele Manunta, Giovanni Onorato, Riccardo Lanari
Abstract:
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 p (...)
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. (Read More)
Claudio De Luca, Francesco Casu, Michele Manunta, Giovanni Onorato, Riccardo Lanari
Ieee Transactions On Geoscience And Remote Sensing ·
2021
Artificial intelligence |
Algorithm |
Information retrieval |
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