Accuracy Improvement of Airborne Lidar Strip Adjustment by Using Height Data and Surface Feature Strength Information Derived from the Tensor Voting Algorithm

Rey-Jer You,Chao-Liang Lee

doi:10.3390/ijgi9010050

Abstract

Light detection and ranging (Lidar) spatial coordinates, especially height data, and the intensity data of point clouds are often used for strip adjustment in airborne Lidar. However, inconsistency in the intensity data and then intensity gradient data because of the variations in the incidence and reflection angles in the scanning direction and sunlight incident in the same areas of different strips may cause problems in the Lidar strip adjustment process. Instead of the Lidar intensity, a new type of data, termed surface feature strength data derived by using the tensor voting method, were introduced into the strip adjustment process using the partial least squares method in this study. These data are consistent in the same regions of different strips, especially on the roofs of buildings. Our experimental results indicated a significant improvement in the accuracy of strip adjustment results when both height data and surface feature strength data were used.

Highlights

Light detection and ranging (Lidar) systems are widely used for rapidly acquiring various types of three-dimensional (3D) point cloud data to reduce the working time effectively in many fields, especially in surveying, engineering, and 3D smart city construction
The present study focuses on the light detection and ranging (Lidar) strip adjustment by using consistent data, namely height data and the surface feature strength of objects
Because the number of Lidar points and the associated observation equations are large in number and Equations (5) and (6) are nonlinear, a linearization and iteration procedure is necessary for strip adjustment

Summary

Introduction

Light detection and ranging (Lidar) systems are widely used for rapidly acquiring various types of three-dimensional (3D) point cloud data to reduce the working time effectively in many fields, especially in surveying, engineering, and 3D smart city construction. Lidar intensity data may be applied for distinguishing objects according to the reflectivity of different materials and for strip adjustment, these data are affected by laser spreading loss, the incidence angles of sunlight and laser beams, scan angles, atmospheric attenuation, surface roughness, materials of objects, and other factors. The present study focuses on the Lidar strip adjustment by using consistent data, namely height data and the surface feature strength of objects. The feasibility of using height data with surface feature strength data for conducting Lidar strip adjustment computation according to a method proposed in preliminary work studies [36,37] is further discussed and analyzed.

Geometric Feature Information

Geometric Feature Strength

PLS Method

Conclusions