INNOVATIVE UAV METHODS FOR INTELLIGENT LANDSLIDE MONITORING

Land Cover Mapping & UAV

Authors

First and Last Name Academic degree E-mail Affiliation
Vincenzo Barrile Ph.D. vincenzo.barrile [at] unirc.it Mediterranea University
Reggio Calabria, Italy
Ernesto Bernardo Ph.D. ernesto.bernardo [at] unirc.it Mediterranea University
Reggio Calabria, Italy
Antonino Fotia Ph.D. antonino.fotia [at] unirc.it Mediterranea University
Reggio Calabria, Italy

I and my co-authors (if any) authorize the use of the Paper in accordance with the Creative Commons CC BY license

First published on this website: 01.11.2020 - 17:00
Abstract 

In Italy every year, the hydrogeological instability causes the destruction of roads, buildings, etc., causing victims and countless economic damage. The monitoring of natural hazards, the evaluation of their impact and the general risk assessment are therefore decisive steps towards the selection and sizing of adequate protection measures. In this paper we intend to present an innovative system that allows us to monitor landslide risk areas and to study landslide phenomena through the use of UAVs. Data are acquired thanks to an automated system of UAVs and wireless charging platforms (capable to acquired, to transmit and to store data); the acquired data are stored automatically in a special platform that allows us to create the point cloud and 3D models of the investigated area (which in turn they are superimposed on the digital models created in previous monitoring), also allowing the creation of the land mass displacement’s sequence in a video. Finally, in relation to early warning, the system allows civil protection to be warned in the event of a landslide risk (start of new landslides or continuation of landslides that have already begun) which in this way will be able to warn the population also through social media.

References 

Barrile, V., Bilotta, G. [2014] Self-localization by laser scanner and GPS in automated surveys. Lecture Notes in Electrical Engineering, 307, 293-311.

Barrile, V., Candela, G., Fotia, A. [2019a] Point cloud segmentation using image processing techniques for structural analysis. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, (2/W11), 187-193.

Barrile, V., Candela, G., Fotia, A., Bernardo, E. [2019b]. UAV Survey of Bridges and Viaduct: Workflow and Application. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11622 LNCS, 269-284.

Barrile, V., Fotia, A., Candela, G., Bernardo, E. [2019c] Integration of 3d model from uav survey in bim environment. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, (2/W11), 195-199.

Barrile, V., Meduri, G.M., Bilotta, G. [2014]. Experimentations and integrated applications laser scanner/GPS for automated surveys. WSEAS Transactions on Signal Processing, 10, (1), 471-480.

Barrile, V., Meduri, G.M., Bilotta, G. [2011]. Laser scanner technology for complex surveying structures. WSEAS Transactions on Signal Processing, 7, (3), 65-74.

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Godone, D.; Allasia, P.; Borrelli, L.; Gullà, G. [2019]. UAV and Structure from Motion Approach to Monitor the Maierato Landslide Evolution. Remote Sens., 12, 1039.

Ma, S., Xu, C., Shao, X., Zhang P., Liang, X. and Tian Y. [2019] Geometric and kinematic features of a landslide in Mabian Sichuan, China, derived from UAV photography. Landslides, 16, 373–381.

Comments

Secretary GeoTerrace
researcher, secretary

Dear authors,

Thank you for your paper submission!

Sincerely,
GeoTerrace Secretary

Tue, 11/03/2020 - 16:33