A Neural Networks Approach for Volcanic Ash Detection in the 2019 Raikoke Eruption Using S3-SLSTR Data

• Published in: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
• Main Authors: Petracca I., De Santis D., Corradini S., Guerrieri L., Picchiani M., Merucci L., Stelitano D., Del Frate F., Prata F., Salvucci G., Schiavon G.
• Other Authors: Petracca, I, De Santis, D, Corradini, S, Guerrieri, L, Picchiani, M, Merucci, L, Stelitano, D, Del Frate, F, Prata, F, Salvucci, G, Schiavon, G
• Format: Conference Object
• Language: English
• Published: IEEE 2022
• Subjects: Ash Detection; Neural Networks; SLSTR; MODIS; Settore ING-INF/02; Settore IINF-02/A - Campi elettromagnetici; Eyjafjallajokull; Iceland
• Online Access: https://hdl.handle.net/2108/389851; https://doi.org/10.1109/IGARSS46834.2022.9883922

In this work the classification of Sentinel-3 Sea and Land Surface Temperature (S3-SLSTR) images with a focus on volcanic cloud detection through a Neural Networks (NNs) approach is presented.Since the hazardous nature of eruptions, a fast and reliable method to monitor the evolution of volcanic clo...