Bridging Insar Coherence Losses Using Contextual Data Driven Processing

We present a methodology which enables InSAR observations of ground motion in regions of low coherence and periodic decorrelation events which makes use of spatial and temporal contextual data to increase the information available to the processing algorithms. While this study is focused on observations of cultivated peatlands, the approach is generic and can be applied to other types of regions where coherence loss may be a concern. Neighbouring regions are grouped together by their contextual attributes such that when one region decorrelates, other observations from similarly behaving regions can still be used to derive a kinematic displacement model, thereby spanning the incoherent gap.