Analysing GNSS network data for deformation monitoring in multi-scale, multi-temporal civil engineering applications

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Deformation monitoring is a key element to develop strategies of resilience and sustainability in civil engineering infrastructure and measures against geohazards. A network of GNSS stations provides a means to monitor the motions of engineering structures and enables both localised (e.g. single points) and larger scale (e.g. national) structural movements to be detected, over time scales of seconds to years. Most of the strategies in GNSS network data analysis are based on (i) constant GNSS station velocities, (ii) modelling of GNSS data periodic signals and (iii) least squares methods to adjust measurement errors. Such strategies are deterministic approaches, where specific conditions/constraints are applied (e.g. constant velocity) to model the behaviour of the GNSS stations. Furthermore, each GNSS station is analysed individually, without examining the behaviour of other GNSS stations, both nearby and further afield, at which similar behaviour may be occurring. This research project will use to-be-developed techniques, following less deterministic approaches (e.g. artificial intelligence) in the analysis of the GNSS network data and adopting spatial analysis methods which treat the GNSS data as part of a network. It is hypothesised that these approaches could enable the extraction of more information regarding the behaviour of the GNSS data, either related locally to a GNSS-specific station or related to a region of the GNSS network. The aim of this project is to develop a methodology where the GNSS network data will be analysed in both the time and space domains and identify the behaviour of the GNSS data of the stations, as individual GNSS stations and as part of the network. This methodology will be applied to deformation monitoring scenarios from a broad range of engineering projects; (i) multi-scale projects, from small scale civil engineering structures (e.g. bridges) to larger scale including the field of geohazards (e.g. ground motion) and (ii) multi-temporal deformations, from short-term (e.g. bridge vibration) to long-term deformation (e.g. land subsidence).