Testing fractal coefficients sensitivity on real and simulated earthquake data

Understanding the mechanisms behind human mobility patterns is crucial to improve our ability to optimize and predict traffic flows. Two representative mobility models, i.e., radiation and gravity models, have been extensively compared to each other against various empirical data sets, while their fundamental relation is far from being fully understood. In order to study such a relation, we first model the heterogeneous population landscape by generating a fractal geometry of sites and then by assigning to each site a population independently drawn from a power-law distribution. Then the radiation model on this population landscape, which we call the radiation-on-landscape (RoL) model, is compared to the gravity model to derive the distance exponent in the gravity model in terms of the properties of the population landscape, which is confirmed by the numerical simulations. Consequently, we provide a possible explanation for the origin of the distance exponent in terms of the properties of the heterogeneous population landscape, enabling us to better understand mobility patterns constrained by the travel distance.

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“…Here L denotes the number of layers. In our work, we consider the set of sites only in the last layer to find its fractal dimension as [49]…”

Section: Modeling Heterogeneous Population Landscapesmentioning

confidence: 99%

Gravity model explained by the radiation model on a population landscape

Hong

Jung

2019

PLoS ONE

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“…The fractal approach has introduced a new statistical tool to quantify the scale invariant distribution of seismicity and, with that, the properties of randomness and clusterization. Time variations of the spatial fractal dimension of seismic events have been found for different areas in the world allowing a quantitative characterisation over time of scale invariant failure processes acting in seismogenic volumes/fault zones (Lomnitz-Adler 1992, De Rubeis et al 1993, Öncel et al 1996, Tosi 1998, Xu and Burton 1999, Gospodinov et al 2012). The method often preferred for calculating the fractal dimension D on timespatial earthquake sequences is the correlation integral method (Grassberger and Procaccia 1983).…”

Section: Previous Studies On Spatial Clustering Of Earthquakesmentioning

confidence: 99%

Magma intrusion as a driving mechanism for the seismic clustering following the 9 May 1989 earthquake swarms at the Canary Islands

Vinciguerra

Day

2013

Acta Geophys.

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A b s t r a c t On 9 May 1989 a M L = 5.2 earthquake struck a region between the islands of Tenerife and Gran Canaria. We investigated the time-spatial evolution of seismic patterns affecting the Canary Islands region during 1989-1995, using a quantitative spatial fractal analysis method. This method allows quantitative investigation of subtle trends in seismicity distribution through time. The fractal analysis indicates that epicenters clustered around a large zone during the May 1989 sequence affected narrow zones during 1991-1993, but then larger zones during 1993-1995 with an overall trend to shallower focal depths. The spatial localisation of seismic data and its time evolution appear to be related to magmatic rather than tectonic activity. Spatial clustering properties of seismicity are consistent with a major intrusive episode in 1989, followed by a period of quiescence and renewed deep intrusive activity from 1993 onwards. This interpretation suggests an increasing probability of future volcanic hazard in the region investigated.

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Testing fractal coefficients sensitivity on real and simulated earthquake data

Cited by 2 publications

References 21 publications

Gravity model explained by the radiation model on a population landscape

Gravity model explained by the radiation model on a population landscape

Magma intrusion as a driving mechanism for the seismic clustering following the 9 May 1989 earthquake swarms at the Canary Islands

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