One of the limitations of deformation measurements made with interferometric synthetic aperture radar (InSAR) is that an interferogram only measures one component of the surface deformation — in the satellite's line of sight. We investigate strategies for mapping surface deformation in three dimensions by using multiple interferograms, with different imaging geometries. Geometries for both current and future missions are evaluated, and their abilities to resolve the displacement vector are compared. The north component is always the most difficult to determine using data from near‐polar orbiting satellites. However, a satellite with an inclination of about 60°/120° would enable all three components to be well resolved. We attempt to resolve the 3D displacements for the 23 October 2002 Nenana Mountain (Alaska) Earthquake. The north component's error is much larger than the signal, but proxies for eastward and vertical motion can be determined if the north component is assumed negligible. Inversions of hypothetical coseismic interferograms demonstrate that earthquake model parameters can be well recovered from two interferograms, acquired on ascending and descending tracks.

Summary: Studies of interseismic strain accumulation are crucial to our understanding of continental deformation, the earthquake cycle and seismic hazard. By mapping small amounts of ground deformation over large spatial areas, InSAR has the potential to produce continental-scale maps of strain accumulation on active faults. However, most InSAR studies to date have focused on areas where the coherence is relatively good (e.g. California, Tibet and Turkey) and most analysis techniques (stacking, small baseline subset algorithm, permanent scatterers, etc.) only include information from pixels which are coherent throughout the time-span of the study. In some areas, such as Alaska, where the deformation rate is small and coherence very variable, it is necessary to include information from pixels which are coherent in some but not all interferograms. We use a three-stage iterative algorithm based on distributed scatterer interferometry. We validate our method using synthetic data created using realistic parameters from a test site on the Denali Fault, Alaska, and present a preliminary result of 10.5 ± 5.0 mm yr−1 for the slip rate on the Denali Fault based on a single track of radar data from ERS1/2.

Triggered by earthquakes, rainfall, or anthropogenic activities, landslides represent widespread and problematic geohazards worldwide. In recent years, multiple remote sensing techniques, including synthetic aperture radar, optical, and light detection and ranging measurements from spaceborne, airborne, and ground-based platforms, have been widely applied for the analysis of landslide processes. Current techniques include landslide detection, inventory mapping, surface deformation monitoring, trigger factor analysis and mechanism inversion. In addition, landslide susceptibility modelling, hazard assessment, and risk evaluation can be further analyzed using a synergic fusion of multiple remote sensing data and other factors affecting landslides. We summarize the 19 articles collected in this special issue of Remote Sensing of Landslide, in the terms of data, methods and applications used in the papers.