Intelligent Integration of Multi-sensor Data for Risk Assessment in Transport Corridor Environments

Roads and railways are founded on earthwork structures such as embankments, which can be susceptible to slope instability and failure, with serious economic and safety implications. Existing approaches to earthwork condition appraisal are labour-intensive and hazardous. While the increasing availability of high resolution geospatial data offers improved opportunities for remote and efficient slope stability assessment, there remains a gap between the availability of such data, and the subsequent extraction of intelligent information. In this research, high resolution lidar data and multispectral aerial imagery are supporting the extraction of the key stability controls of slope gradient, aspect, soil moisture and vegetation type. The influence of these parameters has been established through numerical modelling under existing and future climate scenarios, enabling stability to be quantified and mapped in a spatially continuous manner. The research has been applied to a test site located at Haltwhistle in northern England. Results highlight the challenges associated with establishing a suitable spatial resolution for parameter extraction and risk assessment in a GIS environment, with degradation in resolution from 20 to 0.5 points / m required in order to overcome micro-topographic effects. A topographic wetness index (TWI), derived from the lidar DTM, was used to characterise soil moisture across the test site. Initial concerns over whether the restricted lidar coverage would be sufficient to capture broader-scale flow routing were allayed following investigations using a larger-scale DTM, which was found to produce results which were in good agreement with the lidar-derived TWI. * Corresponding author.