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 event-based 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.
Highlights
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)
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 al 2008; Schädler et al 2015), or relatively shallower phenomena developed over deep-seated movements (Guida et al 1987; Guerricchio et al 2000; Murillo-García et al 2015), or partial mobilizations of previous landslides in nested structures (Lee et al 2001), or various superimpositions of different landslide types (Stefanini 2004; Guida et al 2006; Valiante et al 2016)
Starting from the overall topic of the definition of the relations between complex arrangements of landslides involving engineering works, this paper aims to (i) define a model, based on the concept of “landslide system”, for the description of associations of landslides and their spatial and temporal relations; (ii) implement such a model in a database structure capable of storing both spatial and temporal information in a single dataset, avoiding physical fragmentation and logic inconsistency of the data and allowing to quickly retrieve information about the number of interacting phenomena, their temporal occurrence, their spatial relations and so on; and (iii) assess its performance in selected case studies
Summary
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). It is adaptable to any natural system and capable to define procedures (called methods or functions) to dynamically access and manipulate classes attributes, reducing the volume of information needed to be stored (Egenhofer and Frank 1987; Worboys et al 1990; Worboys 1994; Kösters et al 1996) This model describes, structures and manage the landslide associations or set, taking into account both their spatial and temporal relations, it is a tool to build up, update and manage landslide inventories using any of the existing classifications for movement types (Varnes 1978; Cruden and Varnes 1996; Hungr et al 2014). The first case refers to a deep-seated, slowmoving and reactivated landslide involving structurally complex formations, while the second one refers to fast-moving, repeated landslides on steep, rocky slopes
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
