4.6 Article

How to avoid false interpretations of Sentinel-1A TOPSAR interferometric data in landslide mapping? A case study: recent landslides in Transdanubia, Hungary

期刊

NATURAL HAZARDS
卷 96, 期 2, 页码 693-712

出版社

SPRINGER
DOI: 10.1007/s11069-018-3564-9

关键词

Sentinel-1A; Persistent scatterer interferometry; High bluffs; Landslide; Atmospheric phase screen

资金

  1. European Union
  2. European Social Fund [EFOP-3.6.1.-16-2016-00004]
  3. [GINOP-2.3.2.-15-2016-00055]

向作者/读者索取更多资源

It is a crucial issue to better understand the usability of Sentinel-1 satellites in geomorphologic applications, since Sentinel-1 and the Copernicus Program are considered to be the workhorse of Earth observation by the European Space Agency during the next decades. Yet, a very limited experience is available on the applicability of Sentinel-1 images in the detection and identification of surface deformations and especially landslide mapping and monitoring in densely vegetated (low-coherence) areas. Few Synthetic Aperture Radar images (not more than 20) are sufficient for a successful run of interferometric stacking algorithms. This number is really low compared to the tremendous data flow of Sentinel-1 images that are available for interferometric analysis nowadays. Despite the availability of acquisitions, only a few papers exist on the accuracy of Sentinel-1 data, signal-to-noise ratio and the value of the acquired imagery for geomorphologic interpretation. Two test sites and a control siteaffected by active surface deformationshave been investigated using 40 Sentinel-1A images and conventional persistent scatterers (PSI) method. PSI results have been combined with the geomorphologic information of the studied sites. We verified that the given number of Sentinel-1A acquisitions provide a unique base for surface deformation recognition and mapping in low-coherence areas. We found that scatterers were corrupted by a strong noise if their line of sight (LOS) velocity was below +/- 6-7mm/year all over the three test sites, although noise can easily be reduced. Noise reduction was achieved by a significant increase of the length of time series, i.e., time range between the first and last image to reduce the effect of atmospheric phase screen (APS).

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