Relationship between tree height and landslide characteristics obtained by GIS assessment

Abstract

AbstractLandslides in forested landscapes have far‐reaching implications, beyond that of just destroying the forest itself, sometimes initiating large‐scale sediment disasters. Although vegetation increases slope stability through its root network, it is hard to evaluate its contribution to slope stability over a wide area. In this study, the relationship between tree height and landslide characteristics in the Ikawa catchment, central Japan, was investigated to develop a method for evaluating the effects of forest cover on slope stability over a regional extent. Catchment‐wide tree height was obtained using airborne LiDAR point cloud data and used in conjunction with the root depth profile, measured for trees of various height by digging trenches. Root tensile strength per unit area of soil was calculated from individual root diameters and empirical power law equations on the relationship between root diameter and root tensile force in order to better understand the effect that tree height has on slope stability. Landslide density in the Ikawa catchment shows that landslides occur more frequently in forests with shorter trees, with occurrence decreasing as tree height increases. This is likely due to the stabilizing features of larger trees having a greater network of roots, which is supported by the general increase in total root area and the deeper penetration of root biomass into the soil as the height of trees surveyed increases. Landslide density was not solely affected by tree height, but also by slope gradient and plane curvature. Decreasing landslide occurrence and landslide area as tree height increases suggests that slope stability increases with tree height, while the random distribution of results when comparing landslide depth to tree height suggests that while tree height has an impact on relative slope stability, the landslide failure depth is independent of tree height, and thus controlled by other factors. © 2020 John Wiley & Sons, Ltd.