Multi-source remote sensing for landslide mapping and monitoring
Department of Earth and Environmental Sciences, University of Milano-Bicocca
Landslides are a widespread hazard in the Alps and mapping and monitoring them is crucial for risk management in this region. This project aims at developing a novel approach for landslide monitoring based on the identification of remote sensing indicators of landslide activity linked to vegetation dynamics.
The project involves:
Development of an automated workflow for downloading and processing the Sentinel 2 data, production of vegetation indices time series from the processed data and data analysis and visualization.
Production and operation of a UAV platform with multispectral sensor to enhance the analysis with higher spatial and/or temporal resolution data.
Employment of machine learning techniques using anomaly and/or object detection in spectral and vegetation indices domain to determine the rules for landslide mapping and monitoring with vegetation dynamics indices. Development and validation of the landslide modelling and mapping algorithm.
This position involves:
i) a secondment of 4 months at SAL engineering, Italy under the supervision of Marco Dubbini. The ESR will take part in the construction of a UAV, equipped with a multispectral sensor configured to match Sentinel 2 bands. The produced UAV platform will be used for field data acquisition on the sites previously exploited for Sentinel 2 data analysis in the ESR’s project to enhance and scale the landslide research according to the project. Upon completing the secondment the ESR is expected to gain knowledge and practice in UAV imaging platforms development, production and operation.
The activity will be supervised by Dr. Micol Rossini.