Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.1007/s35147-022-1008-7 |
| Title (Primary) | Automatized drought impact detection using natural language processing |
| Author | Sodoge, J.; de Brito, M.M.; Kuhlicke, C. |
| Source Titel | WasserWirtschaft |
| Year | 2022 |
| Department | SUSOZ |
| Volume | 112 |
| Issue | S1 |
| Page From | 30 |
| Page To | 31 |
| Language | englisch |
| Topic | T5 Future Landscapes |
| Abstract | Our Team developed a method for the automatized detection of drought impacts based on newspaper articles. The method can extract different classes of drought impacts and their geographic and temporal scope from text data. We generated a multi-sectoral dataset of drought impacts in Germany from 2000 to 2021. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=26210 |
| Sodoge, J., de Brito, M.M., Kuhlicke, C. (2022): Automatized drought impact detection using natural language processing WasserWirtschaft 112 (S1), 30 - 31 10.1007/s35147-022-1008-7 |
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