Exploring possibilities of including detailed ALS derived biomass information into physically-based slope stability models at regional scale

Abstract

The causes of landslides are manifold and highly influenced by multiple interacting natural and anthropogenic factors. In particular human induced land cover changes, such as deforestation and afforestation are known to strongly influence slope stability. Thus, we investigate the understanding of differences between forested and non-forested conditions of an area is crucial in order to develop sustainable preventive countermeasures. One possibility to evaluate the influence of biomass changes on landslide activity is to apply physically based slope stability models where the dynamic influence of spatially and temporally variable vegetation areas on soil strength and hydrology is explicitly included. Some of these models also require detailed information on biomass related parameters (e.g. wood and crown volume, weight, Leaf Area Index) as well as surface and subsurface conditions. Newly developed algorithms allow deriving biomass parameters from highly resolved multi-temporal 3D Airborne Laser Scanning (ALS). This allows an improved parameterization of hydro-mechanical slope stability models since it accounts for the spatiotemporal variability in vegetation conditions. The BioSLIDE project aims to combine vegetation related parameters derived from ALS data with physically based slope stability modelling to allow a better understanding of geomorphic interdependencies at regional scale. The objective of this paper is to evaluate possibilities and potential limitations of an inclusion of ALS-derived biomass information within dynamic physically based hydro-mechanical slope stability modelling. Hereto both synthetic and real case study data will be used. This interdisciplinary approach is expected to improve spatio-temporal scenarios of anthropogenic effects and environmental changes on landslide activity.