ACCURACY ASSESSMENT OF A UAV-BASED LANDSLIDE MONITORING SYSTEM

Peppa, M.V.; Mills, J.P.; Moore, P.; Miller, P.E.; Chambers, J.E.. 2016 ACCURACY ASSESSMENT OF A UAV-BASED LANDSLIDE MONITORING SYSTEM. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B5. 895-902. https://doi.org/10.5194/isprsarchives-XLI-B5-895-2016

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Official URL: http://dx.doi.org/10.5194/isprsarchives-XLI-B5-895...

Abstract/Summary

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.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.5194/isprsarchives-XLI-B5-895-2016
ISSN:	2194-9034
Date made live:	27 Mar 2017 15:30 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/516660

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.5194/isprsarchives-XLI-B5-895-2016

ISSN:

2194-9034

Date made live:

27 Mar 2017 15:30 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/516660