Digital Terrain Model on Vegetated Areas: Joint Use of Airborne Lidar Data and Optical Images

Airborne Lidar system provides the Earth’s topography as 3D point clouds. Many algorithms have been implemented to sort out the automatic classification problem as well as the Digital Terrain Model generation (DTM). This is mainly due to the various aspects of landscapes within a global survey which can include urban, forested or mountainous areas. This paper is focused on the generation of DTM over rural areas that are composed of open fields and forests. The methodology we propose is based on the joint use of optical images and Lidar data. It aims at adapting the window size of a morphological-based filtering algorithm to the presence of vegetated areas. In this context, Lidar intensity and optical images are combined to generate a Hybrid Normalized Difference Vegetation Index (HNDVI). A vegetation mask is then calculated with HNDVI and Lidar variance information. The window size continuously varies from a predefined minimum distance to an automatically processed upper boundary. We show with conclusive results the potentiality of a full combination of Lidar data and RGB optical images for improving the generation of fine DTMs on rural environments.