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Towards A Low-Cost, Real-Time Photogrammetric Landslide Monitoring System Utilising Mobile and Cloud Computing Technology

Lookup NU author(s): Polpreecha Chidburee, Professor Jon Mills, Dr Pauline Miller, Dr Karolina Fieber

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Close-range photogrammetric techniques offer a potentially low-cost approach in terms of implementation and operation for initial assessment and monitoring of landslide processes over small areas. In particular, the Structure-from-Motion (SfM) pipeline is now extensively used to help overcome many constraints of traditional digital photogrammetry, offering increased user-friendliness to nonexperts, as well as lower costs. However, a landslide monitoring approach based on the SfM technique also presents some potential drawbacks due to the difficulty in managing and processing a large volume of data in real-time. This research addresses the aforementioned issues by attempting to combine a mobile device with cloud computing technology to develop a photogrammetric measurement solution as part of a monitoring system for landslide hazard analysis. The research presented here focusses on (i) the development of an Android mobile application; (ii) the implementation of SfM-based open-source software in the Amazon cloud computing web service, and (iii) performance assessment through a simulated environment using data collected at a recognized landslide test site in North Yorkshire, UK. Whilst the landslide monitoring mobile application is under development, this paper describes experiments carried out to ensure effective performance of the system in the future. Investigations presented here describe the initial assessment of a cloud-implemented approach, which is developed around the well-known VisualSFM algorithm. Results are compared to point clouds obtained from alternative SfM 3D reconstruction approaches considering a commercial software solution (Agisoft PhotoScan) and a web-based system (Autodesk 123D Catch). Investigations demonstrate that the cloud-based photogrammetric measurement system is capable of providing results of centimeter-level accuracy, evidencing its potential to provide an effective approach for quantifying and analyzing landslide hazard at a local-scale.


Publication metadata

Author(s): Chidburee P, Mills JP, Miller PE, Fieber KD

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: XXIII ISPRS Congress 2016

Year of Conference: 2016

Pages: 791-797

Print publication date: 11/07/2016

Online publication date: 16/06/2016

Acceptance date: 23/02/2016

ISSN: 2194-9042

Publisher: International Archives of Photogrammetry, Remote Sensing and Spatial Information Science

URL: https://doi.org/10.5194/isprs-archives-XLI-B5-791-2016

DOI: 10.5194/isprs-archives-XLI-B5-791-2016

Series Title: International Archives of Photogrammetry, Remote Sensing and Spatial Information Science


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