## 1 Introduction  
Ground movement is the soil-related geohazard most damaging to infrastructure in the UK [1]. As such, the ability to measure the impact of soil movement on infrastructure networks in a cost-effective manner offers great value to utilities, insurance companies, and governments. Infrastructure resilience can be compromised by infrastructure pressures (ageing assets, embrittlement, thinning, increasing demand and loading), environmental pressures (changing climate, soil movement), and financial pressures. However, a fully functioning and fault-resistant system of infrastructure is important for the critical operation of healthcare, transport, trade, and commerce. The UK government is set to invest \(\ell\)100 billion in infrastructure by 2021 to ensure that the UK's infrastructure needs are met for future generations [2]. Monitoring the structural condition of infrastructure networks is essential to ensure its long-term resilience. Developing suitable methods to monitor infrastructure networks at the regional to national scale is also a key challenge [2]. Several in situ techniques are available for the local monitoring of infrastructure assets, including manual visual inspection, levelling, total station surveying, and GPS technologies [3]. These approaches provide highly accurate measurements of deformation at a single point, yet they require significant investment of human resources and equipment to obtain a high density of measurements suitable for wide-scale infrastructure monitoring. On this premise, satellite remote sensing--particularly with the onset of new generation high resolution Synthetic Aperture Radar (SAR) sensors--can measure deformation over areas several tens of kilometres wide while retaining high precision and accuracy. This allows the cost-effective monitoring of surface deformation [4]. Advanced Differential Interferometry (D-InSAR) techniques, such as Persistent Scatterers Interferometry (PSI), offer promise for the monitoring of large scale soil movement and long-term deformation of infrastructure networks. PSI requires at least 20 SAR images to measure surface deformation over months or years, removing the effects of atmosphere, topography, and signal noise [5; 6]. Several applications of PSI have previously been investigated. Some examples include monitoring either natural or anthropogenic urban subsidence [3; 7; 8], measuring the inter-annual variability of soil related ground movement [3; 9; 10], the detection of natural hazards such as landslides [11; 12], as well as observing the structural condition of infrastructure [13; 14]. This technique is of great potential value to utility companies wishing to monitor assets in near real-time, and could ultimately lead to observations of an entire infrastructure network with a high spatial and temporal resolution. In a recent study of Mexico City, a density of 575 PS targets per km\({}^{2}\) was achieved using the European Space Agency's Sentinel 1 data [15]. With the advent of very high resolution SAR data, such as TerraSAR-X, a PS density of up to 5201 targets per km\({}^{2}\) have been recorded [16]. Lower resolution datasets such as the ERS, and the ENVISAT satellite constellations have an archive of data extending back to 1992, enabling historical evaluations of surface deformation if required [17]. However, new satellite missions such as the Sentinel 1 offer an increased spatial resolution with a quicker revisit period of 6 days drawing on a combination of Sentinel 1a and 1b, making it a promising new tool for environmental monitoring. On this basis, PSI applied to Sentinel 1 data could provide high density measurements of ground movement on a regional scale and over a range of different land cover types [3]. Furthermore, PSI outputs can be integrated into a Geographical Information System (GIS) which allows for a greater understanding of the relationships between surface deformation and the natural environment [18; 19].