Abstract
Abstract. Landslides are hazardous events with often disastrous consequences. Monitoring landslides with observations of high spatio-temporal resolution can help mitigate such hazards. Mini unmanned aerial vehicles (UAVs) complemented by structure-from-motion (SfM) photogrammetry and modern per-pixel image matching algorithms can deliver a time-series of landslide elevation models in an automated and inexpensive way. This research investigates the potential of a mini UAV, equipped with a Panasonic Lumix DMC-LX5 compact camera, to provide surface deformations at acceptable levels of accuracy for landslide assessment. The study adopts a self-calibrating bundle adjustment-SfM pipeline using ground control points (GCPs). It evaluates misalignment biases and unresolved systematic errors that are transferred through the SfM process into the derived elevation models. To cross-validate the research outputs, results are compared to benchmark observations obtained by standard surveying techniques. The data is collected with 6 cm ground sample distance (GSD) and is shown to achieve planimetric and vertical accuracy of a few centimetres at independent check points (ICPs). The co-registration error of the generated elevation models is also examined in areas of stable terrain. Through this error assessment, the study estimates that the vertical sensitivity to real terrain change of the tested landslide is equal to 9 cm.
Highlights
1.1 BackgroundLandslides represent complex and dynamic phenomena that have the potential to impact disastrously on society
Mini unmanned aerial vehicles (UAVs) fitted with off-the-shelf compact cameras have recently become attractive for many photogrammetric applications because they offer time-efficient and cost-effective solutions compared to traditional aerial photogrammetric surveys, thereby enabling capture at high spatio-temporal resolution
During the fieldwork the following tasks were performed: (1) Global Navigation Satellite System (GNSS) base station was established on stable terrain in an adjacent field and observed in GNSS static mode for at least six hours, which delivered 1 cm planimetric and 2 cm vertical absolute accuracy; (2) circular targets of 0.40 m diameter were evenly distributed over the landslide and were surveyed in GNSS rapid static mode, which delivered 3D accuracy at mm-level relative to the GNSS base station; (3) visible UAV imagery was collected at the specification described below; and (4) spot heights of characteristic concave/convex landslide features were topographically surveyed using total station and/or rapid static GNSS for validation purposes
Summary
Landslides represent complex and dynamic phenomena that have the potential to impact disastrously on society. Some geophysical methods offer higher resolution, providing transect based observations (e.g. Electrical Resistivity Tomography). These methods often provide indirect information (e.g. physical property information) that requires cross-validation from benchmark observations obtained by other techniques (Chambers et al, 2011; Merritt et al, 2014). Airborne laser scanning (ALS) and terrestrial laser scanning (TLS) provide high density point clouds enabling generation of high quality digital elevation models (DEMs) (Ackermann, 1999; Pirotti et al, 2013). Both techniques are relatively costly and, in the case of TLS, occlusions can occur due to oblique incidence angles (Eisenbeiß, 2009). UAV-derived multi-temporal observations based on a SfM workflow can complement contemporary ground-based investigations and enhance the interpretation of landslide activity
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