An enhanced rainfall-induced landslide catalogue in Italy
Abstract With the increasing use of data-driven landslide prediction models also based on artificial intelligence, the availability of accurate information on the occurrence of landslides and the rigorous reconstruction of their triggering rainfall conditions are crucial. To this end, an enhanced ra...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04551-6 |
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| author | Maria Teresa Brunetti Stefano Luigi Gariano Massimo Melillo Mauro Rossi Silvia Peruccacci |
| author_facet | Maria Teresa Brunetti Stefano Luigi Gariano Massimo Melillo Mauro Rossi Silvia Peruccacci |
| author_sort | Maria Teresa Brunetti |
| collection | DOAJ |
| description | Abstract With the increasing use of data-driven landslide prediction models also based on artificial intelligence, the availability of accurate information on the occurrence of landslides and the rigorous reconstruction of their triggering rainfall conditions are crucial. To this end, an enhanced rainfall-induced landslide catalogue, e-ITALICA, is presented here. e-ITALICA contains spatial and temporal information on 6312 rainfall-induced landslides that occurred in Italy between 1996 and 2021 (already listed in the previous ITALICA catalogue published in 2023), with the addition of their rainfall triggering conditions in terms of rainfall duration D (h) and cumulative event rainfall E (mm). The triggering conditions are calculated using hourly rainfall measurements from 4033 rain gauges and applying a rigorous and reproducible method. In addition, topographic and land cover information is also provided. e-ITALICA can be used to analyse rainfall conditions capable of triggering landslides, to calibrate and validate physically based landslide prediction models, and to define empirical rainfall thresholds from local to national scales in Italy, thus contributing to landslide risk reduction. |
| format | Article |
| id | doaj-art-2e489f4a11f94ca582b22d5a77ffac61 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-2e489f4a11f94ca582b22d5a77ffac612025-02-09T12:11:50ZengNature PortfolioScientific Data2052-44632025-02-0112111010.1038/s41597-025-04551-6An enhanced rainfall-induced landslide catalogue in ItalyMaria Teresa Brunetti0Stefano Luigi Gariano1Massimo Melillo2Mauro Rossi3Silvia Peruccacci4Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle RicercheIstituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle RicercheIstituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle RicercheIstituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle RicercheIstituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle RicercheAbstract With the increasing use of data-driven landslide prediction models also based on artificial intelligence, the availability of accurate information on the occurrence of landslides and the rigorous reconstruction of their triggering rainfall conditions are crucial. To this end, an enhanced rainfall-induced landslide catalogue, e-ITALICA, is presented here. e-ITALICA contains spatial and temporal information on 6312 rainfall-induced landslides that occurred in Italy between 1996 and 2021 (already listed in the previous ITALICA catalogue published in 2023), with the addition of their rainfall triggering conditions in terms of rainfall duration D (h) and cumulative event rainfall E (mm). The triggering conditions are calculated using hourly rainfall measurements from 4033 rain gauges and applying a rigorous and reproducible method. In addition, topographic and land cover information is also provided. e-ITALICA can be used to analyse rainfall conditions capable of triggering landslides, to calibrate and validate physically based landslide prediction models, and to define empirical rainfall thresholds from local to national scales in Italy, thus contributing to landslide risk reduction.https://doi.org/10.1038/s41597-025-04551-6 |
| spellingShingle | Maria Teresa Brunetti Stefano Luigi Gariano Massimo Melillo Mauro Rossi Silvia Peruccacci An enhanced rainfall-induced landslide catalogue in Italy Scientific Data |
| title | An enhanced rainfall-induced landslide catalogue in Italy |
| title_full | An enhanced rainfall-induced landslide catalogue in Italy |
| title_fullStr | An enhanced rainfall-induced landslide catalogue in Italy |
| title_full_unstemmed | An enhanced rainfall-induced landslide catalogue in Italy |
| title_short | An enhanced rainfall-induced landslide catalogue in Italy |
| title_sort | enhanced rainfall induced landslide catalogue in italy |
| url | https://doi.org/10.1038/s41597-025-04551-6 |
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