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Project Overview

Project Code: ED 07

Project name:

Deciphering the causes of vertical land motion from GPS using Bayesian inference methods

TUM Department:

ED - Aerospace and Geodesy

TUM Chair / Institute:

Data Science in Earth Observation

Research area:

Bayesian inference, solid Earth geophysics, geodesy

Student background:

Aerospace / GeodesyComputer Science

Further disciplines:

Planned project location:

AI4EO lab,
Lise-Meitner-Str. 9,
85521 Ottobrunn, Munich

Project Supervisor - Contact Details


Title:

Prof

Given name:

Jonathan

Family name:

Bamber

E-mail:

j.bamber@tum.de

Phone:

+44117 445 3945

Additional Project Supervisor - Contact Details


Title:

Dr

Given name:

John

Family name:

Aiken

E-mail:

john@xal.no

Phone:

Additional Project Supervisor - Contact Details


Title:

Given name:

Family name:

E-mail:

Phone:

Project Description


Project description:

Vertical Land Motion (VLM) can be measured by the global network of more than 20,000 permanent GPS stations. For many of these sites, the data cover more than a decade and provide a unique insight into the processes that influence VLM in space and time. The processes include the viscous response of the solid Earth to changes in loading that took place thousands of years ago (called Glacial Isostatic Adjustment), elastic deformation due to instantaneous changes in water or ice load (hydrology), tectonics, human influences such as water extraction or impoundment among others.

Separating out the signal due to each process is a grand challenge in geophysics and would provide valuable information about the structure of the solid Earth but also mass movement at the surface, i.e. the flow of water and the melting of land ice.

We have developed a powerful software package called 4-D Modeller (4DM), which uses Bayesian inference methods to tackle a wide class of problems that have a spatial and temporal component, such as VLM: https://4dmodeller.github.io/fdmr/. We have used the software to investigate hydrological processes in Norway, lakes in Tibet, the spread of Covid in the UK as well as global mass movement (www.globalmass.eu).

The goal of this project would be to take the global network of GPS station measurements of VLM and combine these with prior information about, for example, GIA, urban disturbance, land hydrology to allow us to separate out the signals from each of these processes in the VLM time series. This would, for example, provide information about the rheology of the solid Earth, the accuracy of the models of GIA and hydrology and to find unexplained signals in the GPS data.

Working hours per week planned:

35-40

Prerequisites


Required study level minimum (at time of TUM PREP project start):

3 years of bachelor studies completed

Subject related:

Desirable subjects are:
-Fundamentals of statistics
-Basics of programming in Python
-Some geophysics and/or geodesy background
-Some background in numerical methods

Other:

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