Three-dimensional data quality assessment: Unmanned aerial vehicle photogrammetry and mobile laser scanner

With significantly rapid in acquiring data and sufficient data quality, unmanned aerial vehicle (UAV) photogrammetry and land based mobile laser scanner are actively implemented in three-dimensional (3D) data acquisition that involve with large area. Considering the final data provided by both measurement approaches are point clouds, accuracy assessment using several well-distributed control points are less significant. With intention to robustly evaluate the accuracies of both measurement approaches using point clouds, this study has established reference point clouds using terrestrial laser scanner (TLS) and tacheometry techniques. At the similar test site, fourteen (14) images were captured using UAV photogrammetry approach and georeferenced point clouds were directly acquired from MLS measurement. To produce quality point clouds from photogrammetry approach, six (6) ground control points (GCP) have been well-distributed at the test area to aid geometry correction in image processing phase. Obtained point clouds from both measurement approaches were deviated with the reference point clouds to determine values of mean deviations with the precisions. Based on law of propagation of variance (LOPOV) algorithm, final accuracy of the tested UAV photogrammetry and MLS were computed by propagating the accuracy of reference point clouds and yielded mean deviations of both approaches. Consider the theories and constraints for both approaches, it is found that the yielded accuracies are meet the measurement principles

Quality assessment of terrestrial laser scanner surface deviation analysis in vegetation slope monitoring

Mechanised with ability to rapidly acquire three-dimensional (3D) data using non-contact measurement, terrestrial laser scanner (TLS) has become an option in landslide monitoring. Dense 3D point clouds provided from TLS has enable surface deviation analysis to rigidly examine the displacement that occurred on the monitored object. However, the existence of vegetation on land slope has become uncertainty in TLS measurement for landslide monitoring. To concretely measure the effect of vegetation, this study has performed two epoch landslide monitoring using tacheometry (for benchmarking) and TLS (Topcon GLS-2000) at Kulim Techno City, Kedah, Malaysia. Sixteen (16) artificial targets were well-distributed on the slope to determine the accuracy of the employed TLS, evaluate the capability of TLS to determine the stability of the slope and scrutinise the significant of vegetation uncertainties in TLS measurement. Results obtained revealed that Topcon GLS-2000 manage to obtained results that are statistically similar to tacheometry and provides 0.006m of accuracy. However, the presence of high incidence angles in TLS measurement has limited the capability to identify the significant displacement of the targets. With the aid of F-variance ratio test, the study has statistically proved that vegetation uncertainty is able to decrease the quality of TLS data.Landslide monitoring, Quality assessmen