RELATIVE ADJUSTMENT OF MOBILE LASER SCANNING DATA IN DIFFERENT SCENES

Abstract

Adjustment is a final step in the post-processing of mobile laser scanning (MLS) data. This stage improves the accuracy of point cloud and trajectory registration in the global coordinate system. Cutting-edge software bundled with the corresponding survey complex is capable of performing the majority of MLS data registration steps in an automatic mode for territories with a varied type of development. With the sufficient number of vertical or inclined flat surfaces software algorithms ensure high accuracy of relative adjustment that constitutes calculating and applying corrections to MLS data obtained during multiple passes. The accuracy of automated relative adjustment can be significantly reduced when there are almost no flat surfaces. In this case, pole-like infrastructures can be used. The task of detecting pole-like infrastructures is mainly solved with high accuracy in urban scenes. In out-of-town scenes this task is becoming more complicated due to vegetation along roads. A comprehensive technique for MLS data relative adjustment, which is capable of utilizing the information about pole-like infrastructure location where there are not enough flat surfaces is proposed. The technique allows detecting pole-like infrastructure among vegetation. Analysis of accuracy estimation results demonstrated that only minimum manual correction of tie point locations is required.