Simona Reale

By analyzing several case studies, the effectiveness of SAR and optical data in combination with machine learning and deep learning technologies in monitoring railway infrastructure demonstrates how they can significantly contribute to preventive maintenance and resource optimization. Starting from the initial work of my master thesis, an in-depth analysis is conducted using additional data such as WorldView-3, Landsat 8, and COSMO-SkyMed. Comparisons are made between various multispectral and hyperspectral data. Subsequently, machine learning and deep learning techniques are explored and implemented on satellite data to find better solutions. Beyond monitoring railway infrastructure alone, the study aims to extend its scope to the sourrounding the infrastructures, including terrains, their slopes, landslides, presence of buildings, etc.