Inhaltszusammenfassung

Geodetic monitoring measurements (e.g., of terrain surfaces) are used to detect deformations. Terrestrial laser scanning (TLS) or unmanned aircraft systems (UAS) equipped with lightweight cameras are often utilized for land surveying, resulting in point clouds that represent the surface of the captured object. For image-based acquisition of the area of interest, point clouds must frst be generated from overlapping images, for which the Structure-from-Motion (SfM) method is commonly used. To p...Geodetic monitoring measurements (e.g., of terrain surfaces) are used to detect deformations. Terrestrial laser scanning (TLS) or unmanned aircraft systems (UAS) equipped with lightweight cameras are often utilized for land surveying, resulting in point clouds that represent the surface of the captured object. For image-based acquisition of the area of interest, point clouds must frst be generated from overlapping images, for which the Structure-from-Motion (SfM) method is commonly used. To perform deformation analyses and derive changes from them, at least two temporally diferent measurement epochs of the same area are required. In this article, we present both point cloud- and feature-based models from TLS and SfMbased UAS point clouds. In addition, an image-based 2D approach using optical fow is applied as an example for landslide simulation to detect changes on object surfaces. To eliminate erroneous results in the analyses due to vegetation areas, the 3D data is fltered using the CANUPO algorithm. The results of this research study show, that the task of deformation detection has some challenges, depending on the use case and the methodology. The point cloud-based methods are suitable to detect pure changes between two point clouds. Also, the direction of these changes can be determined to distinguish between material uplift and downlift. In contrast, the feature-based descriptor (Fast Point Feature Histogram, FPFH) assigns pairs of points between two epochs based on similar geometry in both point clouds therewith individual movements can be detected. However, areas that have changed signifcantly cannot be assigned. Optical fow shows point changes in similar dimensions to the target deformations and allows deformation analysis with much less computational efort than with 3D point clouds. Considering these fndings, point cloud-based method are suitable for determining surface-based information, while the feature-based and image-based methods are capable of extracting local changes.» weiterlesen» einklappen

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DDC Sachgruppe:
Ingenieurwissenschaften