High Density Airborne LIDAR Estimation of Disrupted Trees Induced by landslides

Abstract

Airborne laser scanning (ALS) data has revolutionized the landslide assessment in a rugged vegetated terrain. It enables the parameterization of morphology and vegetation of the instability slopes. Vegetation characteristics are by far less investigated because of the currently available accuracy and density ALS data and paucity of field data validation. We utilized a high density ALS (HDALS) data with 170 points m-2 for characterizing disrupted vegetation induced by landslides by means of a variable window filter and the SkelTre-skeletonisation. Tree analyses in landslide areas resulted in relatively low height, small crown and more irregularities, whereas these peculiarities are not so obvious in the healthy forests. The statistical tests unveiled the clear differences between the extracted parameters in landslide and non-landslide zones and supported the field evidences. We concluded that HDALS is a promising tool to geometrically retrieve disrupted woody vegetation structures and can be good bioindicator to landslide activity.