Artikel ; Online: Rapid Mapping of Landslides Induced by Heavy Rainfall in the Emilia-Romagna (Italy) Region in May 2023
Remote Sensing, Vol 16, Iss 1, p
2023 Band 122
Abstract: Heavy rainfall is a major factor for landslide triggering. Here, we present an inventory of 47,523 landslides triggered by two precipitation episodes that occurred in May 2023 in the Emilia-Romagna and conterminous regions (Italy). The landslides are ... ...
Abstract | Heavy rainfall is a major factor for landslide triggering. Here, we present an inventory of 47,523 landslides triggered by two precipitation episodes that occurred in May 2023 in the Emilia-Romagna and conterminous regions (Italy). The landslides are manually mapped from a visual interpretation of satellite images and are mainly triggered by the second rainfall episode (16–17 May 2023); the inventory is entirely original, and the mapping is supplemented with field surveys at a few selected locations. The main goal of this paper is to present the dataset and to investigate the landslide distribution with respect to triggering (precipitation) and predisposing (land use, lithology, slope and distance from roads) factors using a statistical approach. The landslides occurred more frequently on steeper slopes and for the land use categories of “bare rocks and badlands” and woodlands. A weaker positive correlation is found for the lithological classes: silty and flysch-like units are more prone to host slope movements. The inventory presented here provides a comprehensive picture of the slope movements triggered in the study area and represents one of the most numerous rainfall-induced landslide inventories on a global scale. We claim that the inventory can support the validation of automatic products and that our results on triggering and predisposing factors can be used for modeling landslide susceptibility and more broadly for hazard purposes. |
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Schlagwörter | landslide inventory ; heavy rainfall ; spatial distribution ; Emilia-Romagna region ; Science ; Q |
Thema/Rubrik (Code) | 910 |
Sprache | Englisch |
Erscheinungsdatum | 2023-12-01T00:00:00Z |
Verlag | MDPI AG |
Dokumenttyp | Artikel ; Online |
Datenquelle | BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl) |
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