The rate of vertical land subsidence in the Samoan Islands has increased since the 2009 Samoa-Tonga earthquake (Han et al. 2019), relative to the pre-earthquake rate. Land subsidence strongly exacerbates the effects of sea level rise and has led to increased flooding that disrupts everyday life and threatens critical infrastructure in the Samoan islands. However, developing effective mitigation policies requires a more detailed picture of both local and broad-scale patterns of subsidence that is difficult to measure. Geographic and atmospheric characteristics of the Samoan Islands present challenges to remote sensing modalities: the archipelago consists of small, isolated landmasses with heavily vegetated and rugged topography, and the region experiences dense cloud cover year-round and moderate ionospheric activity.

We present a processing workflow that incorporates three disparate data sources and yields a promising look into vertical land motion (VLM) over the islands. Using data from GNSS, tide gauge stations, and InSAR, we are able to broadly constrain patterns of VLM over Tutuila Island, American Samoa and Upolu, Samoa. We identify relative deformation using InSAR time-series analysis of Sentinel-1 data from 2016 to the present with both persistent scatterer (PS) and small baseline subset (SBAS) methods, and tie the results to a global reference frame using the deformation signals from local permanent GPS stations. Furthermore, we use measurements from each local tide gauge station available on Upolu and Tutuila Islands as a local validation point and to identify inconsistencies in the InSAR results due to atmospheric noise, unwrapping, and non-zero phase closure. Finally, we discuss outline next steps for a more comprehensive understanding of future flood hazards.