A spatiotemporal object-oriented data model for landslides (LOOM)
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Mario Valiante I Domenico Guida I Marta Della Seta I Francesca Bozzano
A spatiotemporal object-oriented data model for landslides (LOOM)
Abstract LOOM (landslide object-oriented model) is here presented as a data structure for landslide inventories based on the object-oriented paradigm. It aims at the effective storage, in a single dataset, of the complex spatial and temporal relations between landslides recorded and mapped in an area and at their manipulation. Spatial relations are handled through a hierarchical classification based on topological rules and two levels of aggregation are defined: (i) landslide complexes, grouping spatially connected landslides of the same type, and (ii) landslide systems, merging landslides of any type sharing a spatial connection. For the aggregation procedure, a minimal functional interaction between landslide objects has been defined as a spatial overlap between objects. Temporal characterization of landslides is achieved by assigning to each object an exact date or a time range for its occurrence, integrating both the time frame and the eventbased approaches. The sum of spatial integrity and temporal characterization ensures the storage of vertical relations between landslides, so that the superimposition of events can be easily retrieved querying the temporal dataset. The here proposed methodology for landslides inventorying has been tested on selected case studies in the Cilento UNESCO Global Geopark (Italy). We demonstrate that the proposed LOOM model avoids data fragmentation or redundancy and topological inconsistency between the digital data and the real-world features. This application revealed to be powerful for the reconstruction of the gravity-induced deformation history of hillslopes, thus for the prediction of their evolution. Keywords Object-oriented . Landslide system . Landslide complex . Landslide object Introduction In the field of natural hazards, landslides are one of the most widespread and frequent phenomena, related both to natural and anthropogenetic causes and triggers, sometimes with catastrophic outcomes such as casualties (Cascini et al. 2008; Petley 2012; Barla and Paronuzzi 2013). Landslides often also interfere with human activities, impacting on urban areas, infrastructures such as roads, tunnels, bridges, pipelines and areas related to other socioeconomic activities causing significant economic losses (Crosta et al. 2004; Evans and Bent 2004; Pankow et al. 2014; Bozzano et al. 2017; Marinos et al. 2019). In this framework, sometimes structures or infrastructures are faced with complex arrangements of landslides rather than a single movement (Barredo et al. 2000; Schädler et al. 2015; Uzielli et al. 2015; Bozzano et al. 2016). Such complexity can be related to different spatiotemporal arrangements of landslides: there can be a frequent occurrence of phenomena in a relatively small area (Corbi et al. 1996; Crozier 2010; Berti et al. 2013), or the spatial overlap of successive landslide occurrences, like converging flow-like movements (Cascini et a
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