Importance of detailed geomorphic interpretation in the landslide characterisation component of landslide risk assessment

Inventories are foundational to landslide hazard characterisation, and thus risk assessment, but commonly suffer from inadequate landslide detection and interpretation. Bare-earth LiDAR models offer excellent opportunities to identify and understand diverse slope failures from their landscape signatures. However, LiDAR’s utility is rarely fully leveraged because of unfamiliarity with its datasets and underappreciation of the geomorphic subtleties they record. We illustrate challenges – and some solutions – to interpreting and documenting landslide features with wide-ranging geomorphic distinctiveness using LiDAR through the worked example of a hilly 2.8-km² site in Tasmania. Its size and undulating slopes are representative of typical residential subdivisions and development-pressured land fringing many Australian cities. Previous high-level, reconnaissance mapping did not identify any landslides at this site. However, iterative, site-focused landform mapping using publicly available LiDAR data and complementary open-access datasets reveal diverse slope movements. They range from fresh-looking, indisputable landslides to very subdued features suggesting much older movements, all of which should be further considered during site visits. Improved landslide hazard characterisation in this example highlights key factors influencing landslide inventorying: LiDAR’s utility in conveying diverse geomorphic indicators; complementarity of geospatial techniques for interrogating elevation data; contributions from supplemental information sources; inverse proportionality between land extent and mapping detail; value of mappers’ previous experience; and benefits of discussion-based landscape interpretation. Expanding site inventories into adjacent terrain and to consider evidence of additional geohazards enhances both identification and likelihood-consequence estimation of hazard scenarios. Robust landslide inventories such as this improve the entire risk assessment process and enable better risk management.