scholarly journals Precursory seismicity patterns

1981 ◽  
Author(s):  
Max Wyss
Keyword(s):  
Seismicity Patterns ◽  
Precursory Seismicity

scholarly journals Analysis of precursory seismicity patterns in Zagros (Iran) by CN algorithm

2014 ◽  
Vol 23 ◽  
pp. 91-99 ◽  
Author(s):  
Majid MAYBODIAN ◽  
Mehdi ZARE ◽  
Hosseyn HAMZEHLOO ◽  
Antonella PERESAN ◽  
Anooshiravan ANSARI ◽  
...  
Keyword(s):  
Seismicity Patterns ◽  
Cn Algorithm ◽  
Precursory Seismicity

scholarly journals Seismicity Pattern Changes before theM= 4.8 Aeolian Archipelago (Italy) Earthquake of August 16, 2010

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Salvatore Gambino ◽  
Antonino Laudani ◽  
Salvatore Mangiagli
Keyword(s):  
Spatial Distribution ◽  
Seismic Quiescence ◽  
Seismicity Patterns ◽  
Extensive Area ◽  
Seismicity Pattern ◽  
Precursory Seismicity ◽  
The Village ◽  
Aeolian Archipelago ◽  
Spatial And Temporal Characteristics ◽  
Regional Tectonics

We investigated the seismicity patterns associated with anM=4.8earthquake recorded in the Aeolian Archipelago on 16, August, 2010, by means of the region-time-length (RTL) algorithm. This earthquake triggered landslides at Lipari; a rock fall on the flanks of the Vulcano, Lipari, and Salina islands, and some damages to the village of Lipari. The RTL algorithm is widely used for investigating precursory seismicity changes before large and moderate earthquakes. We examined both the spatial and temporal characteristics of seismicity changes in the Aeolian Archipelago region before theM=4.8earthquake. The results obtained reveal 6-7 months of seismic quiescence which started about 15 months before the earthquake. The spatial distribution shows an extensive area characterized by seismic quiescence that suggests a relationship between quiescence and the Aeolian Archipelago regional tectonics.

scholarly journals Decomposing spatio-temporal seismicity patterns

2001 ◽  
Vol 1 (1/2) ◽  
pp. 83-92 ◽  
Author(s):  
C. Goltz
Keyword(s):  
Spatial And Temporal Variability ◽  
Seismicity Patterns ◽  
Seismicity Rate ◽  
Potential Applications ◽  
Time Series Approach ◽  
Distributed Process ◽  
Sample Application ◽  
Components Analysis ◽  
Spatio Temporal ◽  
Large Earthquakes

Abstract. Seismicity is a distributed process of great spatial and temporal variability and complexity. Efforts to characterise and describe the evolution of seismicity patterns have a long history. Today, the detection of changes in the spatial distribution of seismicity is still regarded as one of the most important approaches in monitoring and understanding seismicity. The problem of how to best describe these spatio-temporal changes remains, also in view of the detection of possible precursors for large earthquakes. In particular, it is difficult to separate the superimposed effects of different origin and to unveil the subtle (precursory) effects in the presence of stronger but irrelevant constituents. I present an approach to the latter two problems which relies on the Principal Components Analysis (PCA), a method based on eigen-structure analysis, by taking a time series approach and separating the seismicity rate patterns into a background component and components of change. I show a sample application to the Southern California area and discuss the promising results in view of their implications, potential applications and with respect to their possible precursory qualities.

scholarly journals On dynamics of seismicity simulated by the models of blocks-and-faults systems

1997 ◽  
Vol 40 (5) ◽  
Author(s):  
A. I. Gorshkov ◽  
V. I. Keilis-Borok ◽  
I. M. Rotwain ◽  
A. A. Soloviev ◽  
I. A. Vorobieva
Keyword(s):  
Numerical Simulation ◽  
Earthquake Prediction ◽  
Driving Forces ◽  
Block Structure ◽  
Seismicity Patterns ◽  
Strong Earthquakes ◽  
Structure Dynamics ◽  
Prediction Algorithms ◽  
The Media

The major results obtained by numerical simulation of block structure dynamics are juxtaposed and analysed: the possibilities to reconstruct tectonic driving forces from territorial distribution of seismicity, clustering of earthquakes in the model, and dependence of the occurrence of strong earthquakes on fragmentation of the media, and on rotation of blocks. These results show that modelling of block structure dynamics is a useful tool to study relations between the geometry of faults and block movements and earthquake flow, including premonitory seismicity patterns, to test the existing earthquake prediction algorithms, and to develop new ones.

Sign in / Sign up

Export Citation Format

Share Document