Abstract
Abstract. Terrestrial laser scanners generate dense and accurate 3D point clouds with minimal effort, which represent the geometry of real objects, while image data contains texture information of object surfaces. Based on the complementary characteristics of both data sets, a combination is very appealing for many applications, including forest-related tasks. In the scope of our research project, independent data sets of a plain birch stand have been taken by a full-spherical laser scanner and a hemispherical digital camera. Previously, both kinds of data sets have been considered separately: Individual trees were successfully extracted from large 3D point clouds, and so-called forest inventory parameters could be determined. Additionally, a simplified tree topology representation was retrieved. From hemispherical images, leaf area index (LAI) values, as a very relevant parameter for describing a stand, have been computed. The objective of our approach is to merge a 3D point cloud with image data in a way that RGB values are assigned to each 3D point. So far, segmentation and classification of TLS point clouds in forestry applications was mainly based on geometrical aspects of the data set. However, a 3D point cloud with colour information provides valuable cues exceeding simple statistical evaluation of geometrical object features and thus may facilitate the analysis of the scan data significantly.
Highlights
In the last decade, terrestrial laser scanning (TLS) has become a valuable technique to capture complex 3D geometry of real objects as 3D point cloud
A data set taken from the study site of the plain birch stand has been used
The 3D point clouds has been mapped to the 2D image plane exactly as before, but here the assigned RGB colour values are used in the image
Summary
Terrestrial laser scanning (TLS) has become a valuable technique to capture complex 3D geometry of real objects as 3D point cloud. The combination of point clouds and images offers new opportunities for an integrated data analysis in terms of geometry and texture, which will be beneficial for segmentation or classification tasks, for instance. In case of a laser scanning system with an integrated digital camera, captured images can be linked to the 3D point cloud immediately due to the fix relative orientation between scanner and camera. If separate instruments are being used, the combined evaluation requires a co-registration of the collected data sets based on correspondences. Because of differences in data characteristics, resolution, and perspective, determining correspondences between image data and terrestrial laser scans becomes a rather challenging task
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