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Visualizing and interpreting surface displacement patterns on unstable slopes using multi-geometry satellite SAR interferometry (2D InSAR)

Permanent lenke
https://hdl.handle.net/10037/12096
DOI
https://doi.org/10.1016/j.rse.2016.12.024
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article.pdf (7.631Mb)
Publishers version (PDF)
Dato
2017-02-05
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Forfatter
Eriksen, Harald Øverli; Lauknes, Tom Rune; Larsen, Yngvar; Corner, Geoffrey D.; Bergh, Steffen G; Dehls, John; Kierulf, Halfdan Pascal
Sammendrag
It is well known that satellite radar interferometry (InSAR) is capable of measuring surface displacement with a typical accuracy on the order of millimeters to centimeters. However, when the true deformation vector differs from the satellite line-of-sight (LOS), the sensitivity decreases and interpretation of InSAR deformationmeasurements becomes challenging. By combining displacement data fromextensive ascending and descending TerraSAR-X datasets collected during the summer seasons of 2009–2014, we estimate two-dimensional (2D) InSAR surface displacement. Displacement data are decomposed into vertical and west/east deformation, dip and combined deformation vector, and validated using Global Navigation Satellite System (GNSS) data.We use the decomposed dataset to visualize variations in surface velocity and direction on unstable slopes in a periglacial environmentwith sporadic permafrost in northern Norway. By identifying areas with uplift and subsidence, and detecting velocity changes (downslope acceleration/deceleration) and related areas of extension and compression, we are able to explain driving and controlling mechanisms and geomorphology in two rockslides and one area with solifluction landforms.
Beskrivelse
Source at https://doi.org/10.1016/j.rse.2016.12.024
Forlag
Elsevier
Sitering
Eriksen, H.Ø., Lauknes, T.R.L., Larsen, Y., Corner, G.D., Bergh, S.G., Dehls, J. & Kierulf, H.P. (2017). Visualizing and interpreting surface displacement patterns on unstable slopes using multi-geometry satellite SAR interferometry (2D InSAR). Remote Sensing of Environment,191, 297-312. https://doi.org/10.1016/j.rse.2016.12.024
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