Resolving Three-Dimensional Surface Motion with InSAR: Constraints from Multi-Geometry Data Fusion

Abstract

Interferometric synthetic aperture radar (InSAR) technology has been widely applied to measure Earth surface motions related to natural and anthropogenic crustal deformation phenomena. With the widespread uptake of data captured by the European Space Agency’s Sentinel-1 mission and other recently launched or planned space-borne SAR missions, the usage of the InSAR technique to detect and monitor Earth surface displacements will increase even more in the coming years. However, InSAR can only measure a one-dimensional motion along the radar line of sight (LOS), which makes interpretation and communication of InSAR measurements challenging, and can add ambiguity to the modelling process. Within this paper, we investigate the implications of the InSAR LOS geometry using simulated and observed deformation phenomena and describe a methodology for multi-geometry data fusion of LOS InSAR measurements from many viewing geometries. We find that projecting LOS measurements to the vertical direction using the incidence angle of the satellite sensor (and implicitly assuming no horizontal motions are present) may result in large errors depending on the magnitude of horizontal motion and on the steepness of the incidence angle. We quantify these errors as the maximum expected error from simulated LOS observations based on a Mogi deformation model. However, we recommend to use LOS observations from several image geometries wherever data are available, in order to solve for vertical and E–W oriented horizontal motion. For an anthropogenic deformation phenomenon observed in seven independent InSAR analyses of Envisat SAR data from the Sydney region, Australia, we find that the strong horizontal motion present could lead to misinterpretation of the actual motion direction when projecting LOS measurements to vertical (uplift instead of subsidence). In this example, the difference between multi-geometry data fusion and vertical projection of LOS measurements (at an incidence angle of 33.8°) reach up to 67% of the maximum vertical displacement rate. Furthermore, the position of maximum vertical motion is displaced horizontally by several hundred metres when the LOS measurements are projected.

Surface Deformation from Sentinel-1A InSAR: Relation to Seasonal Groundwater Extraction and Rainfall in Central Taiwan

“…Such LOS displacement rates have been converted into vertical displacement rates by neglecting horizontal velocities [12]. Fuhrmann and Garthwaite [28] have shown that the error in the vertical velocity, when converting LOS to vertical, depends on the incidence angle and the amount of horizontal motion. From a real-world local displacement phenomenon measured with Envisat data from multiple viewing geometries (four ascending and three descending passes), they found that an error of up to 67% of the maximum vertical motion was introduced into the projected vertical component when neglecting the horizontal component.…”

“…The vertical velocities were mostly over 20 mm/a and the horizontal velocities were mostly less than 5 mm/a. The maximum error resulting from the projection of LOS into the vertical velocity induced by the horizontal velocity component was [28]:…”

The 2018 Lake Muir earthquake sequence, southwest Western Australia: rethinking Australian stable continental region earthquakes

“…Three dimensional displacements of the ground surface are therefore mapped into a one-dimensional geometry. If InSAR data from different viewing geometries (e.g., ascending and descending orbital passes of the SAR satellite) is available, then vertical and horizontal components of displacement can be resolved (Fuhrmann and Garthwaite, 2019). Unfortunately, this is not the case for the Lake Muir earthquake, where only descending-pass Sentinel-1 SAR data is available.…”

Three-dimensional deformation time series of glacier motion from multiple-aperture DInSAR observation

“…The three components of the deformation vector cannot be reconstructed from a single DInSAR measurement, so various techniques were developed to overcome this limitation (Hu et al 2014;Fuhrmann and Garthwaite 2019). In rare cases (e.g., at high latitudes) 3D solution can be derived directly from three independent DInSAR observations (Gray 2011).…”

“…However, ascending and descending DInSAR data are usually acquired at different times and sometimes with different revisit fre-quencies (e.g., 24 days for RADARSAT-2 and 6 days for Sentinel-1). Fuhrmann and Garthwaite (2019) proposed to interpolate the DInSAR measurements to common epochs. The Multidimensional Small Baseline Subset (MSBAS-2D) technique was developed in order to overcome the need for interpolation.…”