Innovative method for landslide risk assessment
It’s not easy to predict landslides. Risk and hazard assessment hinges on factors marked by uncertainties like geological and geotechnical conditions and human activity. The EU-funded HYBLAND project will develop an innovative, reliable and inclusive method for landslide susceptibility and hazard assessment. Using south-western Cyprus as a test bed area, the project will combine Earth observation technology with classical geotechnical research to investigate the failure mechanisms of landslides and their spatiotemporal spread. HYBLAND will formulate an effective multi-modal deterministic method and an assessment method based on machine learning. The project will combine these methods to develop an innovative methodological approach for more effective management of related uncertainties.
Fields of science
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencesearth and related environmental sciencesphysical geographynatural disasters
- natural sciencesearth and related environmental sciencesgeologyseismology
- social sciencessociologygovernancecrisis management
Funding SchemeMSCA-IF-EF-SE - Society and Enterprise panel
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
2630 Psimolofou Lefkosia