Abstract
Natural hazards like earthquakes, volcanic eruptions, landslides, droughts, floods, cyclones and fires threaten people and properties. These events can happen in any moment and need to be studied and monitored. In particular, the number of landslide events, as well as the direct and indirect damage caused by slope failures are largely increasing over the last years, calling for the development of more adequate methods for landslide monitoring and prevention.
This LEMONADE research project (http://lemonade.mountainresearch.at) focused on mass movements and particularly on landslides with the aim to evaluate the abilities, potentialities and limitations of remote and proximal sensing methods for monitoring ground deformations. In particular, the project considered and integrated different earth observation platforms (satellite, unmanned aerial vehicle, land-based), sensors (imaging, ranging, radar, etc.), techniques (photogrammetry, scanning, etc.) and algorithms to deliver an innovative fusion methodology applicable also to other application fields and hazard scenarios. Sensor fusion and (multi-temporal, multi-modal) data integration techniques were used to improve the results of single methods in order to assess the capabilities of a combination of monitoring approaches.
The LEMONADE project was coordinated by FBK Trento (3D Optical Metrology unit - http://3dom.fbk.eu) and run in collaboration with Eurac Research Bolzano/Bozen (Institute for Earth Observation - www.eurac.edu/en/research/mountains/remsen/Pages/default.aspx) and the Austrian Academy of Sciences (AAS) in Innsbruck (Institute of Interdisciplinary Mountain Research - www.mountainresearch.at/).
The most important outcome of the project, beside monitoring in 3D three different landslide scenarios (Schmirn valley – Tyrol, Corvara – Bolzano/Bozen, Fortebuso – Trento) in collaboration and support with regional authorities, was the development of an innovative data fusion methodology, validated in three test sites. The data fusion approach considered the intrinsic advantages of each dataset and sensor and provided interesting results for better monitoring and prevention policies. In particular, the large and active landslide in Corvara was analyzed in close collaboration among all three project partnerships. The LEMONADE project was coordinated by FBK Trento (3D Optical Metrology unit - http://3dom.fbk.eu) and run in collaboration with Eurac Research Bolzano/Bozen (Institute for Earth Observation - www.eurac.edu/en/research/mountains/remsen/Pages/default.aspx) and the Austrian Academy of Sciences (AAS) in Innsbruck (Institute of Interdisciplinary Mountain Research - www.mountainresearch.at/).
The most important outcome of the project, beside monitoring in 3D three different landslide scenarios (Schmirn valley – Tyrol, Corvara – Bolzano/Bozen, Fortebuso – Trento) in collaboration and support with regional authorities, was the development of an innovative data fusion methodology, validated in three test sites. The data fusion approach considered the intrinsic advantages of each dataset and sensor and provided interesting results for better monitoring and prevention policies. In particular, the large and active landslide in Corvara was analyzed in close collaboration among all three project partnerships.