Gintaris Maknavicius
Gintaris Maknavicius has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Andrea Bartoli
Worldsensing, 08014 Barcelona, Spain
1 shared publication - Denis Guilhot
WorldSensing, Barcelona, Spain
1 shared publication - Gijs Leemans
SkyGeo, Inc., San Francisco, CA 94107, USA
1 shared publication - Jacqueline Salzer
SkyGeo, Inc., San Francisco, CA 94107, USA
1 shared publication - John S. Metzger
SkyGeo, Inc., San Francisco, CA 94107, USA
1 shared publication - Martijn Houtepen
SkyGeo, Inc., San Francisco, CA 94107, USA
1 shared publication
Latest Publications
- Open Access
- 14 July 2021
- Published by MDPI AG in Remote Sensing
- Vol. 13 (14) , 2757
Internet-of-Things-Based Geotechnical Monitoring Boosted by Satellite InSAR Data
Landslides, often a side effect of mining activities, pose a significant risk to humans and infrastructures such as urban areas, power lines, and dams. Operational ground motion monitoring can help detect the spatial pattern of surface changes and their evolution over time. In this technical note, a commercial, cost-effective method combining a network of geotechnical surface sensors with the InSAR data was reported for the first time to accurately monitor surface displacement. The correlation of both data sets is demonstrated in the Gediminas Castle testbed, where slope failure events were detected. Two specific events were analyzed, and possible causes proposed. The combination of techniques allows one to detect the precursors of the events and characterize the consequences of the failures in different areas in proximity to the castle walls, since the solution allows for the confirmation of long-term drifts and sudden movements in real time. The data from the in situ sensors were also used to refine the satellite data analysis. The results demonstrate that not all events pose a direct threat to the safety of the structure monitored.
- 14 July 2021
- Published by MDPI AG in Remote Sensing
- Vol. 13 (14) , 2757
Open AccessInternet-of-Things-Based Geotechnical Monitoring Boosted by Satellite InSAR Data
Landslides, often a side effect of mining activities, pose a significant risk to humans and infrastructures such as urban areas, power lines, and dams. Operational ground motion monitoring can help detect the spatial pattern of surface changes and their evolution over time. In this technical note, a commercial, cost-effective method combining a network of geotechnical surface sensors with the InSAR data was reported for the first time to accurately monitor surface displacement. The correlation of both data sets is demonstrated in the Gediminas Castle testbed, where slope failure events were detected. Two specific events were analyzed, and possible causes proposed. The combination of techniques allows one to detect the precursors of the events and characterize the consequences of the failures in different areas in proximity to the castle walls, since the solution allows for the confirmation of long-term drifts and sudden movements in real time. The data from the in situ sensors were also used to refine the satellite data analysis. The results demonstrate that not all events pose a direct threat to the safety of the structure monitored.