Potentials and limitations of a landslide inventory based on online news sources: the FraneItalia catalogue

Landslide inventories are critical to support investigations of where and when landslides have happened and may occur in the future. They can be developed using different techniques and data, each bringing intrinsic limitations and potential sources of mapping errors, hence affecting the overall accuracy and reliability of the subsequent analyses.
For more than one decade, the Geotechnical Engineering Group (GEG) of the University of Salerno (Italy) has been carrying out a specific research activity aimed at collecting and organizing, within a national landslide catalogue called “FraneItalia”, information on landslides that occur in Italy from online news sources. To this aim, the news aggregator Google Alerts has been used for screening web pages and news articles published in Italian language. The FraneItalia catalogue is freely accessible at https://zenodo.org/records/7923683. A description of the main features of the catalogue and the procedures adopted to fill it out can be found at https://doi.org/10.1186/s40677-018-0105-5.
FraneItalia, which is being continuously updated, to date contains data on more than 9000 landslide events that occurred in Italy during the period 2010-2024. The catalogue includes both fatal landslide events and events that did not produce physical harm to people. The main peculiarity of the catalogue is the distinction between single landslide events, SLE (i.e., records only reporting one landslide) and areal landslide events, ALE (i.e., records referring to multiple landslides triggered by the same cause in the same geographic area). The structure is organized as a database where each reported landslide event is characterized by 40 unique fields, which are grouped in 9 thematic tables: main info; spatial information; temporal information; landslide characteristics; consequences to people, structures, infrastructures, cars and other elements; and source. Not all fields are mandatory. A set of constraints has been adopted to ensure the correctness and the semantic integrity of the attributes. In addition, a set of confidence descriptors are associated to each landslide record to measure the level of accuracy of the spatial and temporal information. Indeed, the availability of accurate and up-to-date information is essential for improving the accuracy and the quality of the subsequent analyses in landslide research.
Different subsets of the catalogue have been already used to carry out studies on landslide risk in Italy (https://franeitalia.wordpress.com/publications/), including: calibration and validation of models for landslides prediction at territorial scale; detection and mapping of spatio-temporal clusters of landslides; susceptibility, hazard, and risk assessment. Given the rising demand for high-quality data to be used in comprehensive analyses at regional and national scales, this dataset might be very useful for supporting decision-making in landslide risk management in Italy. Moreover, the methodology to define and populate FraneItalia is deemed to be general and can be used to develop similar initiatives in other countries.