Enabling the public sector to save money, innovate and make more effective policy decisions by using space technology and data

Case Study: CGG Services (UK) Ltd - Soil moisture estimation to support asset management within the rail sector

General Information

  • Provider: CGG Services (UK) Ltd
  • Technology utilised: Earth Observation (EO) Position Navigation & Timing (PNT)
  • Thematic area: Infrastructure
  • End user(s): Network Rail
  • Website: www.cgg.com/npa

Year

  • 2018

This grant funded, feasibility study was undertaken in 2018, in response to SSGP's 2017-18 Open Call Competition.  

Soil moisture can have significant impacts on asset management within the rail sector. The occurrence of earthwork failures have been shown to correspond with ground (soil) saturation and weather conditions reported at the time of failure. The key aim was to improve the understanding of soil moisture evaluation from Earth Observation (EO) Sentinel-1 SAR data and to develop algorithms to facilitate the remote estimation of soil moisture at a greater spatial resolution than currently available to the rail sector.

The project generated a simple but effective method of calculating soil moisture values derived from Sentinel-1 data and demonstrated outputs at three sites across the UK.  It has been successful in terms of building an algorithm to prototype EO-derived soil moisture estimation and has shown the following:

  • EO radar data can be used to generate an estimation of soil moisture at specified locations across the UK.
  • A relative method for soil moisture estimation is preferred to an absolute calculation and can be tailored to a specific site.
  • A moderate correlation between alternative soil moisture data (COSMOS-UK and Soil Moisture Deficit) and EO Sentinel-1 radar derived soil moisture was achieved. 

The method provides an initial relative soil moisture evaluation to offer complementary information to that currently used within the rail sector.  Further development is required across additional test sites in the UK.

High resolution, timely information on soil moisture is of value to a number of companies/organisations. This project has focussed upon Network Rail, but the commercial application of this can be applied in multiple areas. CGG will continue to develop the algorithms to complement established InSAR services and improve access to EO-derived soil moisture information.

Next Steps

Further work is required at more test sites across the UK to address variability / repeatability of results and to enable a more detailed and robust set of case studies to be established for soil moisture estimation from Sentinel-1 data.