LAMPRE proposes to execute innovative research and technological developments to increase GMES limited operational capacity to cope with triggered landslide events and their consequences, in Europe and elsewhere. LAMPRE will enhance landslide risk mitigation/preparedness efforts and post-event-landslide recovery and reconstruction activities, in highly vulnerable geographic and geologic regions. The project improves the ability to detect/map landslides, assess/forecast the impact of triggered landslide events on vulnerable elements, and model landscape changes caused by slope failures. These goals are achieved by (i) researching and developing new techniques and products to dynamically integrate satellite/airborne imagery, (ii) designing and using intelligent image processing techniques, (iii) modelling landslide-infrastructure interactions using advanced numerical modelling and ground based thematic information, and (iv) proposing standards for landslide mapping, susceptibility zonation and image processing. Products of LAMPRE, including geo-processing tools, landslide inventory/susceptibility maps, vulnerability/impact assessments, and standards and best practices, will be beneficial to Civil Protection authorities, environmental, agricultural and forestry agencies, organizations managing transportation networks, and Emergency Response and Land Monitoring GMES services. Results of LAMPRE will be relevant to the EU strategy for the prevention, preparedness and response to natural hazards, and the protection of people, property, infrastructures and the environment, to implement the EU Soil Thematic Strategy, and to the design of novel GMES landslide services based on images taken by the ESA Sentinel-2 satellites. To facilitate up take by users and cross boundary cooperation, LAMPRE will test products and services in a range of physiographical and geographical regions, and will use the advice of a specific international stakeholder user group.
Fields of science
Call for proposal
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Funding SchemeCP-FP - Small or medium-scale focused research project