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Piontek, Dennis (2022) A novel machine learning-based satellite retrieval of volcanic ash for Meteosat covering the petrological variability. Dissertation, Ludwig-Maximilians-Universität München. doi: 10.5282/edoc.29799.
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Official URL: https://edoc.ub.uni-muenchen.de/29799/
| Item URL in elib: | https://elib.dlr.de/186372/ | ||||||||
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| Document Type: | Thesis (Dissertation) | ||||||||
| Title: | A novel machine learning-based satellite retrieval of volcanic ash for Meteosat covering the petrological variability | ||||||||
| Authors: |
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| Date: | 2022 | ||||||||
| Journal or Publication Title: | Universitätsbibliothek der Ludwig-Maximilians-Universität München | ||||||||
| Refereed publication: | No | ||||||||
| Open Access: | Yes | ||||||||
| DOI: | 10.5282/edoc.29799 | ||||||||
| Number of Pages: | 176 | ||||||||
| Status: | Published | ||||||||
| Keywords: | Vulkanasche, Satellitenretrieval, Eyjafjallajökull, Puyehue-Cordón Caulle | ||||||||
| Institution: | Ludwig-Maximilians-Universität München | ||||||||
| Department: | Fakultät für Physik | ||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||
| HGF - Program: | Space | ||||||||
| HGF - Program Themes: | Earth Observation | ||||||||
| DLR - Research area: | Raumfahrt | ||||||||
| DLR - Program: | R EO - Earth Observation | ||||||||
| DLR - Research theme (Project): | R - Atmospheric and climate research | ||||||||
| Location: | Oberpfaffenhofen | ||||||||
| Institutes and Institutions: | Institute of Atmospheric Physics > Cloud Physics | ||||||||
| Deposited By: | Piontek, Dennis | ||||||||
| Deposited On: | 13 May 2022 09:00 | ||||||||
| Last Modified: | 13 May 2022 09:00 |
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