Integration of intensity information and echo distribution in the filtering process of LIDAR data in vegetated areas

Accurate digital terrain models (DTM) are crucial for many applications in coastal management, such as simulation of flood risk scenarios. Airborne LIDAR sensors generate dense height information of large areas for the derivation of suitable DTM in an efficient manner. However, the accuracy and reliability of the LIDAR DTM points suffer if the laser beam interacts with vegetation. Several filter algorithms were developed, which usually apply geometric criteria to eliminate the vegetation points. However, in areas of very dense vegetation and rough terrain, where only few laser pulses are able to penetrate the canopy, such processing often fails resulting in an upward height shift of the derived DTM. In this paper additional features are proposed, which correspond to the reflectance characteristics of the backscattering objects, to support the filtering proccess. The introduced new algorithm uses intensity information and the distribution of multiple echoes for adaptive weight update in an iterative surface fitting procedure. The benefit of the integration of these new features in the filtering method is shown for several areas covered by different types of coastal shrubberies