Effects of errors and biases on the scaling of earthquake spatial pattern: application to the 2004 Sumatra–Andaman sequence

Padhy, Simanchal; Mishra, O. P.; Subhadra, N.; Dimri, V. P.; Singh, O. P.; Chakrabortty, G. K.

doi:10.1007/s11069-013-0978-2

Cited by 6 publications

(12 citation statements)

References 54 publications

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“…The variation in crustal thickness for cratons is well documented based on RF analyses (Fig.4), exhibiting crustal / lithospheric thinning related to magmatism associated with the Gondwana break-up episode, and delamination of lithospheric root below the Singhbhum craton (Saul et al, 2000;Sarkar et al, 2003;Mandal 2017). The crustal thickness obtained by integrating active and passive seismic sources is in agreement with the CRUST1.0 (Laske et al, 2013) throughout the continent except for Tibet and east coast of peninsular India with a difference of as large as 20 km between the two (Singh et al, 2015). There is a good correlation between the 10 s Rayleigh group velocity map and the sediment thickness map of Laske and Masters (1997).…”

Section: Peninsular Indiasupporting

confidence: 77%

“…In a recent study, Padhy et al (2015) theoretically assessed bias due to catalog of finite length, scaling range, effects of location errors and boundary effects, and applied it to the 2004 Sumatra earthquake catalog. They found the lower limit of bias in estimates of fractal dimension from limited data sets.…”

Section: Seismicity Power Laws and Its Implicationsmentioning

confidence: 99%

“…The velocity structures at different scales of the Indian lithosphere are studied by several researchers employing different approaches such as seismic body wave tomography (Ramesh et al, 1990(Ramesh et al, , 1993Kennett and Widiyantoro 1999;Kayal and Mukhopadhyay, 2002;Mishra et al 2003;Mandal and Pujol, 2006;Mishra 2013;Singh et al, 2015;Koulakov et al, 2018Koulakov et al, , 2015Raoof et al, 2017;, surface wave tomography (Bhattacharya, 1981;Acton et al, 2010), receiver functions (RF) (Rai et al, 2003;Gupta et al, 2003;Kiselev et al, 2008;Ravi Kumar et al, 2013;Kumar et al, 2007Kumar et al, , 2013, joint inversion of body and surface wave analyses (Rai et al, 2003;Julia et al, 2009;Saikia et al, 2017), body wave propagation (Krishna et al, 1999;Krishna and Ramesh, 2000), and by magnetotellurics (Gupta et al, 1996;Naganjaneyulu and Santosh, 2012;Pavan Kumar et al, 2017), heat flow (Negi et al, 1986;Roy and Rao, 2000) and xenolith studies (Babu et al, 2009). Lithospheric structures in different tectonic domains are summarized below.…”

Section: Velocity Structuresmentioning

confidence: 99%

“…The cratonic segments in peninsular India are characterized by higher velocity anomalies (~3%) at shallow depths (<300 km), and the upper mantle low-velocity anomalies are closely related to the Deccan volcanisms and reactivation of the rift systems (Singh et al 2015). Recently, Maurya et al (2016) presented a high-resolution 3-D velocity model including anisotropy, and imaged the lithosphere asthenosphere boundary (LAB) and the mid-lithospheric discontinuities of the Indian plate based on surface wave tomography using a massive dataset of 550 seismic broadband stations.…”

Section: Figure 2 Map Showing Various Tectonic Blocks Of India and Amentioning

confidence: 99%

“…There are significant studies on seismic anisotropy in upper mantle for different tectonic units of the Indian continent with varied geological terrains, including the cratons, the continental margins along the west and east coasts, DVP, SGT, Himalayan arc, Indus-Tsangpo suture zone, Tibet and Indian ocean from analysis of direct and core-refracted S-wave phases (SKS, SKKS, PKS, ScS) (Saikia et al 2010;Rao et al, 2013;Roy et al, 2012;Ravi Kumar et al, 2008;Singh et al, 2006Singh et al, , 2007Singh et al, , 2015Vinnik et al, 2007;Heintz et al, 2009;Rao and Kumar, 2014;Pavan Kumar et al, 2015;Rao et al, 2017). The time delay between the split shear waves and their fast polarization direction were used to characterize the nature of anisotropy.…”

Section: Seismic Anisotropymentioning

confidence: 99%

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Seismicity and structure of the Indian subcontin

Kayal

2020

Episodes

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Instrumentally recorded tectonic earthquakes The 1897 great Shillong plateau earthquake (M w 8.1) in NE India region is the first instrumentally recorded Indian earthquake that was registered outside India by a few global seismic stations. After this great event, the first Indian seismological observatory was established in Alipore (Kolkata) in 1899 under auspices of the India Meteorological Department (IMD) (Kayal, 2008). Since then the national seismological network is developed; today it consists of some 115 broadband seismic observatories including some cluster-networks in NE India and in different segments of the Himalayas. In addition to these, a cluster of some 21 broadband stations is in operation in Koyna-Warna region and a cluster of some 50 broadband and 50 strong-motion stations is in operation in Gujarat state under the auspices of the Institute of Seismological Research (ISR), a newly established Institute in 2006. With the upgraded national network, earthquakes down to magnitude M w 3.5 are fairly well located, and down to M w 2.0 by the cluster networks. Recently, the Ministry of Earth Sciences (MoES) established the National Centre for

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Section: Peninsular Indiasupporting

confidence: 77%

Section: Seismicity Power Laws and Its Implicationsmentioning

confidence: 99%

Section: Velocity Structuresmentioning

confidence: 99%

Section: Figure 2 Map Showing Various Tectonic Blocks Of India and Amentioning

confidence: 99%

Section: Seismic Anisotropymentioning

confidence: 99%

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Seismicity and structure of the Indian subcontin

Kayal

2020

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Fractal dimension analysis for seismicity spatial and temporal distribution in the circum-Pacific seismic belt

Yin

Zheng

et al. 2019

J Earth Syst Sci

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In this study, we present the fractal characteristics of the spatio-temporal sequence for seismic activity in the circum-Pacific seismic belt and vicinity regions, which is one of the most active seismic zones worldwide. We select the seismic dataset with magnitude M ≥ 4.4 in the circum-Pacific seismic belt region and its vicinity from 1900-2015 as the objects. Based on the methods of capacity dimension and information dimension, using ln(1/δ)-ln N (δ) of the relationship to evaluate and explain, the results show that (1) in the circum-Pacific seismic belt and the surrounding areas, for the seismic activity with magnitude M ≥ 4.4, the time series dimension is 0.63, the spatial distribution dimension is 0.52 and they have fractal structure. (2) For the earthquakes with M ≥ 7.0, the time series dimension increases greatly, which indicates that the cluster characteristics in time is greatly reduced. And the earthquakes with magnitude 7.0 ≥ M ≥ 4.4 have significant impact on the characterized by clustering in time in the study region. (3) There is significant fractal structure at spatio-temporal distribution of earthquakes in the circum-Pacific seismic belt. It reveals the tectonic movements keep continuous, obvious anisotropism characteristic of geological structure and the distribution of surface stress field is spatio-temporal heterogeneity in the study area.

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Fractal Theory and its Implication for Acquisition, Processing and Interpretation (API) of Geophysical Investigation: A Review

Dimri

Ganguli

2019

Journal of the Geological Society of India

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It has been observed that the sources of geophysical anomalies, such as density, susceptibility, conductivity, reflectivity, etc. may be conveniently defined according to a scaling/fractal distribution. Acquisition, processing and interpretation (collectively known as API) are the three main steps in any geophysical investigation. The proper design of acquisition of data can enhance the signal to noise ratio of geophysical response. Fractal theory has been applied and found to be worthwhile in deciding a geophysical survey network. Similarly, the second step, geophysical data processing for interpolation of missing data is key to reduce spurious anomaly due to aliased-interpolated data, and fractal or multi-fractal concepts have been applied to improve data processing significantly. Finally, interpretation is the main step which depends on the nature of the source. This lead to the development of new interpretation methods such as scaling spectral method and modified centroid method to accommodate scaling/fractal distribution of source for scaling geology for improved results. In the present paper, in-depth review of the application of fractal/multi-fractal approach in geophysical API for better geophysical understanding, is presented. Also, the advancement in geophysical API for filling the gaps in our understanding of sub-surface source characterization with recent examples in seismology and heat flow is highlighted, which can be further helpful in conducting future research of scaling geology.

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Effects of errors and biases on the scaling of earthquake spatial pattern: application to the 2004 Sumatra–Andaman sequence

Cited by 6 publications

References 54 publications

Seismicity and structure of the Indian subcontin

Seismicity and structure of the Indian subcontin

Fractal dimension analysis for seismicity spatial and temporal distribution in the circum-Pacific seismic belt

Fractal Theory and its Implication for Acquisition, Processing and Interpretation (API) of Geophysical Investigation: A Review

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