Scale-Invariance in the Spatial Development of Landslides in the Umbria Region (Italy)

Liucci, Luisa; Melelli, Laura; Suteanu, Cristian

doi:10.1007/s00024-014-0877-9

Cited by 10 publications

(9 citation statements)

References 41 publications

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“…Massive strata of limestone and marly-limestone lithotypes characterize the carbonate reliefs. The topographic profiles commonly follow the structural setting of the area, with wide and flat mountain tops corresponding to the tops of the anticlines and convex-straight slopes corresponding to the fold sides (Liucci et al, 2015). The drainage density is overall low, and diffusive processes related to slope wash (i.e., splash and sheet erosion) operate at small wavelengths (Chase, 1992) near the tops of mountains.…”

Section: Discussionmentioning

confidence: 99%

“…During its evolution, the topographic relief advances toward a dynamical steady state (Bonnet and Crave, ; Lague et al ., ). Space–time scale‐invariant dynamics could characterize this process (Reinhardt and Ellis, ; Singh et al ., ), thus explaining the scale invariance observed for the landscape, as well as for many processes modeling the Earth's surface and their resulting landforms, like river networks (Tokunaga, ; Turcotte, ; Donadio et al ., ), landslides (Liucci et al ., ), fracture systems (Bonnet et al ., ; Le Garzic et al ., ), coastlines (Xiaohua et al ., ; D'Alessandro et al ., ) and erosion triangular facets (Paliaga, ).…”

Section: Introductionmentioning

confidence: 99%

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The fractal properties of topography as controlled by the interactions of tectonic, lithological, and geomorphological processes

Liucci

Melelli

2017

Earth Surf Processes Landf

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Landscape topography widely exhibits fractal structure. Because of the complexity of relief geometry this structure is not homogeneous in space, and the study of its spatial characteristics represents a powerful method for investigating the interrelationships between landforms and underlying processes. We explore these interrelationships using the digital elevation model (DEM) of an area located in central Italy, where landscape topography is strongly linked to its geological evolution, being characterized by alternating intermountain basins and mountain ranges trending NW–SE. A modified version of the method based on the standard deviation of relief elevations is used to evaluate the fractal parameters of relief after tiling the DEM in spatial units characterized by homogeneous fractal geometry, and statistical methods in conjunction with spatial analysis techniques are applied to the resulting terrain datasets. Both the lowest and (to a lesser extent) the highest values of fractal dimension are found to follow the ridge‐and‐valley trend. Low fractal dimension is observed in the mountain ranges characterized by massive strata of limestone, and along the fault scarps defining the contact between the intermountain basins and the surrounding slopes, where sediment deposition prevails. High fractal dimension is observed in regions characterized by highly erodible terrigenous lithology, and in areas where tectonic activity favors erosional processes mainly by rivers. The analysis of the (fractal) power law parameters also suggests that each major lithological complex has its own characteristic fractal signature. These results provide new insights into the link between the fractal properties of topography and the tectonic, lithological, and geomorphological features of the area, and show that the analysis approach proposed is useful to depict key aspects about the geomorphological and geological setting of an area, using only a DEM. Copyright © 2017 John Wiley & Sons, Ltd.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The fractal properties of topography as controlled by the interactions of tectonic, lithological, and geomorphological processes

Liucci

Melelli

2017

Earth Surf Processes Landf

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“…The periodical moving traces of these GPS monitoring points are seldom considered. In addition, fractal theory provides an efficient way to explore the characteristics behind the data, but in landslide research field, this theory are always popularly used in landslide frequency analysis and size characteristic analysis (Malamud et al 2004;Liucci et al 2014;Ma et al 2014;Pourghasemi et al 2014). The study on exploring the fractal characteristic behind landslide deformation data is rare.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, fractal theory has also been adopted in landslide research field. For example, it has been used to analyze the frequencyÀmagnitude relationship on a large number of landslides using power law statistics (Guzzetti et al 2002;Iwahashi et al 2003;Malamud et al 2004;Liucci et al 2014), to identify fractal structures and scale invariance in numerous subaerial environments based on topographic data (Pelletier 1999;Southgate & M€ oller 2000;Micallef et al 2008;Pourghasemi et al 2014), and to extrapolate and explain the fractal behaviour in the deformation and mechanisms of landslides (Katz & Aharonov 2006;Li et al 2011;Hu et al 2011;Ma et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Landslide displacement analysis based on fractal theory, in Wanzhou District, Three Gorges Reservoir, China

Gui

Yin

Glade

2016

Geomatics, Natural Hazards and Risk

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Slow moving landslide is a major disaster in the Three Gorges Reservoir area. It is difficult to compare the deformation among different parts of this kind of landslide through GPS measurements when the displacement of different monitoring points is similar in values. So far, studies have been seldom carried out to find out the information hidden behind those GPS monitoring data to solve this problem. Therefore, in this study, three landslides were chosen to perform landslide displacement analysis based on fractal theory. The major advantage of this study is that it has not only considered the values of the displacement of those GPS monitoring points, but also considered the moving traces of them. This allows to reveal more information from GPS measurements and to obtain a broader understanding of the deformation history on different parts of a unique landslide, especially for slow moving landslides. The results proved that using the fractal dimension as an indicator is reliable to estimate the deformation of each landslide and to represent landslide deformation on both spatial and temporal scales. The results of this study could make sense to those working on landslide hazard and risk assessment and land use planning.

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“…Spatial patterns of landslide locations have been found to exhibit power scaling properties (Goltz, 1996;Guthrie & Evans, 2004b;Liucci et al, 2015;Qiu et al, 2019). Guthrie and Evans (2004b) and Qiu et al (2019), using nearest neighbor analysis and density contour methods, found that the spatial distribution of landslides cluster and that intraday rainfall magnitudes and earthquake occurrences correlate with the clustering of landslides within the study areas.…”

Section: Spatial Scaling and Patternsmentioning

confidence: 99%

Landslide Scaling: A Review

Tebbens

2020

Earth and Space Science

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Scale-Invariance in the Spatial Development of Landslides in the Umbria Region (Italy)

Cited by 10 publications

References 41 publications

The fractal properties of topography as controlled by the interactions of tectonic, lithological, and geomorphological processes

The fractal properties of topography as controlled by the interactions of tectonic, lithological, and geomorphological processes

Landslide displacement analysis based on fractal theory, in Wanzhou District, Three Gorges Reservoir, China

Landslide Scaling: A Review

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