Applications of LiDAR-derived DEMS in geotechnical engineering

Over the past 15 years or so, access to high quality LiDAR-acquired digital elevation models (DEMs) and powerful geographical information system (GIS) software tools to process and display them, has given geoscientists and engineers a wealth of new ways to tackle geoscience problems. For geotechnical engineers and engineering geologists LiDAR DEMs in GIS have, at a basic level, facilitated the production of accurate, professional site plans and maps. However, more advanced applications supported by hillshade rendered DEMs have opened up a wide range of remote mapping possibilities. The potential for hillshade DEMS to be used as a tool for geological mapping in areas with bedded strata has yet to be fully realised. In some cases, freely-available LiDAR data is sufficient to allow geological structural trends to be established from desktop analysis of DEMs, even when they cannot be determined on the ground, in the field. An example of this is provided. LiDAR DEMs have also proven powerful tools for the identification and spatial mapping of landslides, with widespread use in preparing landslide inventories and hazard susceptibility maps. However, detailed LiDAR DEMs can also be used to understand landslide mechanisms and to classify landslide types. Some examples are provided. In a more niche application, 1 m resolution LiDAR DEMs have proven especially useful in hazard mapping for areas subject to coal mining-induced subsidence, with a demonstrated capacity to reliably identify all pothole features in an area, down to a size of less than 1 m. For difficult areas, such as dense forest, this can be done in the safe and convenient environment of the office, and may give more reliable outcomes than ground-based mapping, which if not undertaken with painstaking diligence, can overlook small features. This paper provides a brief review of the background to LiDAR-derived DEMs, the hillshade visualisation technique, and some of the applications in which hillshaded DEMs have been previously used. It proceeds to present examples as to how these can be used to infer geological bedding trends and structures, infer landslide mechanisms and produce inventories of coal mining-induced subsidence features. Consideration is given to the limitations of this application and the potential to adopt more elaborate hillshade techniques to enhance outcomes.