Remote Sensing and Spatial Analisys for Geohazards And

- Introduction to remote sensing and data acquisition platforms (satellites, UAVs, aircraft). - Optical, multispectral, and hyperspectral sensors. - Synthetic Aperture Radar (SAR) and applications to surface deformation and ground movements. - LiDAR and digital terrain modeling. - UAV and digital photogrammetry: flight planning, data collection, GCPs, SfM processing, DSM/DTM and orthophotos. - Google Earth Engine (GEE): available datasets, spectral indices, time series, change detection, applications. - GIS tools for organization, integration and spatial analysis of environmental data. - Exploratory data analysis for quality check and detection of outliers, missing values and trends of environmental data. - Concepts and algorithms of artificial intelligence and machine learning (supervised/unsupervised learning). - Evaluation of performance, explainability and interpretability of resulting models. - Applications to geohazards: glaciers, landslides, floods, volcanoes. - Applications to georesources: water resources. - Presentation and discussion of real-world case studies. - Development of an applied project based on real datasets.