This research idea is built on the assertion that the deterministic approach of determining vertical land motion offers useful information about the status of ground deformation for an area, but it fails to include extreme estimates of VLM. 

In this project, we set out to develop a framework that uses a probability distribution function to estimate the VLM. The aim of developing this framework is to be able to handle the extreme, rare, but important information of subsidence. At the moment, we have the framework ready and have implemented it using InSAR time-series for Louis Armstrong Airport, New York City, the Fiji Islands, and the East Boston area. The results look promising; we are currently trying to add some functionality to this framework to develop a Bayesian inference-based model for recurrently processing InSAR data. This will be useful in areas experiencing shallow vertical motions and also useful in quantifying the drivers in such areas.