Abstract
Abstract. Road and rail networks are essential components of national infrastructures, underpinning the economy, and facilitating the mobility of goods and the human workforce. Earthwork slopes such as cuttings and embankments are primary components, and their reliability is of fundamental importance. However, instability and failure can occur, through processes such as landslides. Monitoring the condition of earthworks is a costly and continuous process for network operators, and currently, geospatial data is largely underutilised. The research presented here addresses this by combining airborne laser scanning and multispectral aerial imagery to develop a methodology for assessing landslide hazard. This is based on the extraction of key slope stability variables from the remotely sensed data. The methodology is implemented through numerical modelling, which is parameterised with the slope stability information, simulated climate conditions, and geotechnical properties. This allows determination of slope stability (expressed through the factor of safety) for a range of simulated scenarios. Regression analysis is then performed in order to develop a functional model relating slope stability to the input variables. The remotely sensed raster datasets are robustly re-sampled to two-dimensional cross-sections to facilitate meaningful interpretation of slope behaviour and mapping of landslide hazard. Results are stored in a geodatabase for spatial analysis within a GIS environment. For a test site located in England, UK, results have shown the utility of the approach in deriving practical hazard assessment information. Outcomes were compared to the network operator’s hazard grading data, and show general agreement. The utility of the slope information was also assessed with respect to auto-population of slope geometry, and found to deliver significant improvements over the network operator’s existing field-based approaches.
Highlights
Road and rail networks are essential components of national infrastructures, underpinning the economy, and facilitating the mobility of goods and the human workforce
The modelling results indicated that slope gradient exerts the greatest influence on slope stability, with increasing slope gradients strongly correlated to reduced factor of safety (FoS) values
The hazard mapping approach is able to deliver a practical solution for slope stability assessment, which presents the user with the slope factor of safety, a derived risk assessment and a number of additional slope metrics
Summary
Road and rail networks are essential components of national infrastructures, underpinning the economy, and facilitating the mobility of goods and the human workforce. The research presented here addresses some of these shortcomings through the development of a remote methodology for assessing slope failure hazard This approach combines variables derived from remotely sensed data, using these to parameterise a numerical geotechnical model. This allows the simulation of slope behaviour under a range of conditions, and through regression analysis facilitates mapping of slope failure hazard along a test corridor. The results of this approach are compared to those determined by the network operator. The potential of the approach for autopopulation of slope geometry is examined
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