Filtering of point clouds acquired by mobile laser scanner for digital terrain model generation in densely vegetated green architectures

Abstract Protection and maintenance of green architecture such as parks, countryside villas, and historic gardens are a duty of our communities. Recently, hand‐held or portable mobile laser scanner (MLS) systems exploiting simultaneous localization and mapping (SLAM) are becoming a promising alternative to terrestrial laser scanner (TLS) in densely vegetated areas to efficiently collect information for site maintenance. The main goal for such surveys stands normally in tree parameter estimation, but getting a high‐resolution, high‐quality digital terrain model (DTM) is an objective worth pursuing as it is useful in later processing. This work presents a novel algorithm for terrain filtering of TLS point clouds and compares its performance with existing packages. To this aim, it compares and evaluates the accuracy of DTM produced by three well‐established open‐source packages and an in‐house development on the test case of an ancient garden survey, where nine scans were executed using a ZEB‐HORIZON scanner. The algorithm we developed is specifically designed for creating digital terrain models (DTMs) from TLS point clouds. In contrast, two of the three software packages we analysed were originally developed for processing airborne laser scanning (ALS) data. As parameter setting significantly influenced the quality of the DTM generation we describe in detail this process for all three algorithms. Since the unavailability of ground truth data, we used the terrain points generated by all four algorithms to perform a cross‐validation.