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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 14, issue 7 | Copyright
Nat. Hazards Earth Syst. Sci., 14, 1749-1759, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 15 Jul 2014

Research article | 15 Jul 2014

Comparison of event landslide inventories: the Pogliaschina catchment test case, Italy

A. C. Mondini1, A. Viero2, M. Cavalli2, L. Marchi2, G. Herrera3, and F. Guzzetti1 A. C. Mondini et al.
  • 1Consiglio Nazionale delle Ricerche, Istituto di Ricerca per la Protezione Idrogeologica, via della Madonna Alta 126, 06128 Perugia, Italy
  • 2Consiglio Nazionale delle Ricerche, Istituto di Ricerca per la Protezione Idrogeologica, Corso Stati Uniti 4, 35127 Padua, Italy
  • 3Instituto Geológico y Minero de España, Ríos Rosas, 23 28003, Madrid, Spain

Abstract. Event landslide inventory maps document the extent of populations of landslides caused by a single natural trigger, such as an earthquake, an intense rainfall event, or a rapid snowmelt event. Event inventory maps are important for landslide susceptibility and hazard modelling, and prove useful to manage residual risk after a landslide-triggering event. Standards for the preparation of event landslide inventory maps are lacking. Traditional methods are based on the visual interpretation of stereoscopic aerial photography, aided by field surveys. New and emerging techniques exploit remotely sensed data and semi-automatic algorithms. We describe the production and comparison of two independent event inventories prepared for the Pogliaschina catchment, Liguria, Northwest Italy. The two inventories show landslides triggered by an intense rainfall event on 25 October 2011, and were prepared through the visual interpretation of digital aerial photographs taken 3 days and 33 days after the event, and by processing a very-high-resolution image taken by the WorldView-2 satellite 4 days after the event. We compare the two inventories qualitatively and quantitatively using established and new metrics, and we discuss reasons for the differences between the two landslide maps. We expect that the results of our work can help in deciding on the most appropriate method to prepare reliable event inventory maps, and outline the advantages and the limitations of the different approaches.

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