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Earthquake frequency-magnitude distribution and fractal dimension in mainland Southeast Asia

Earth, Planets and Space201466:8

https://doi.org/10.1186/1880-5981-66-8

  • Received: 14 January 2014
  • Accepted: 25 March 2014
  • Published:

Abstract

The 2004 Sumatra and 2011 Tohoku earthquakes highlighted the need for a more accurate understanding of earthquake characteristics in both regions. In this study, both the a and b values of the frequency-magnitude distribution (FMD) and the fractal dimension (D C ) were investigated simultaneously from 13 seismic source zones recognized in mainland Southeast Asia (MLSEA). By using the completeness earthquake dataset, the calculated values of b and D C were found to imply variations in seismotectonic stress. The relationships of D C -b and D C -(a/b) were investigated to categorize the level of earthquake hazards of individual seismic source zones, where the calibration curves illustrate a negative correlation between the D C and b values (D c  = 2.80 - 1.22b) and a positive correlation between the D C and a/b ratios (D c  = 0.27(a/b) - 0.01) with similar regression coefficients (R2 = 0.65 to 0.68) for both regressions. According to the obtained relationships, the Hsenwi-Nanting and Red River fault zones revealed low-stress accumulations. Conversely, the Sumatra-Andaman interplate and intraslab, the Andaman Basin, and the Sumatra fault zone were defined as high-tectonic stress regions that may pose risks of generating large earthquakes in the future.

Keywords

  • Seismicity
  • Frequency-magnitude distribution
  • Fractal dimension
  • Mainland Southeast Asia

Background

Various statistical techniques assessing the seismicity, frequency-magnitude distribution (FMD; Gutenberg and Richter 1944), and fractal dimension (D C ) (Wyss et al. 2004) are regarded as effective approaches used to understand the local seismotectonic activities. Both the b value of the FMD and the D C value are significantly related to, and therefore directly controlled by, the seismicity and tectonic stress levels in that region (Scholz 1968; Öncel et al. 1996). During the past few decades, the relationship between the b and D C values has been successfully calibrated (Hirata 1989; Öncel and Wilson 2002; Wyss et al. 2004), and the D C /b ratio has been used as an indicator of earthquake hazards (Bayrak and Bayrak 2012).

After the devastation caused by the M w -9.0 earthquake on December 26, 2004, the mainland Southeast Asia (MLSEA; Figure 1) has been recognized as one of the most seismically active regions in the world. Both interplate and a number of intraplate regimes are defined as hazardous earthquake sources. More than 45 major earthquake events (M w  ≥ 7.0) have been reported during 1962 to 2013 within the MLSEA. Accordingly, evaluation of the FMD a, b, and D C values of all earthquake sources recognized in the MLSEA is important and is therefore the primary focus of this study. The results of this study may be useful for seismic hazard assessments for countries in the Association of Southeast Asian Nations (ASEAN).
Figure 1
Figure 1

Map of mainland Southeast Asia (MLSEA) and the 13 designated seismic zones (A to M). The map shows epicentral distributions of completeness earthquakes with m b  ≥ 4.0 reported during the period 1974 to 2010 (green circles), earthquakes with m b  ≥ 7.0 (blue circles), and significant earthquakes mentioned in the text (red circles). Red lines depict the fault lines compiled by Pailoplee et al. (2009). Grey polygons indicate the geometry of the individual seismic source zones proposed by Pailoplee and Choowong (2013).

Method

Seismic sources

Present-day activities detected at the Indo-Australian and Eurasian plate collision zone have revealed that various styles of tectonic regimes contribute in various ways to the overall seismic activities occurring within MLSEA's territory. Interplate regimes dominate along the Sumatra-Andaman subduction zone, including central Myanmar, central Sumatra Island, and off the coast of the Andaman Sea, whereas an intraplate regime spreads eastward in the vicinity of eastern Myanmar, Thailand, Laos, and southern China (Pailoplee et al. 2013). To analyze seismic hazards, previous research has defined several seismic source zones in the MLSEA. For example, Nutalaya et al. (1985) and Charusiri et al. (2005) proposed 12 and 21 zones, respectively, according to the various available tectonic, geological, and seismicity information. However, based on the most recent data, Pailoplee and Choowong (2013) modified the seismic source zones of both Nutalaya et al. (1985) and Charusiri et al. (2005) and proposed 13 new zones (A to M), which are used in this study (Figure 1; Table 1). The details of each zone are described briefly as follows.
Table 1

FMD coefficients ( a and b values) and fractal dimensions ( D C ) of 13 earthquake sources recognized in MLSEA

Name

EQ number

M C

a

b

D C

A: Sumatra-Andaman Interplate

414

4.7

5.98

0.768 ± 0.05

1.91 ± 0.01

B: Sumatra-Andaman Intraslab

560

4.7

6.58

0.877 ± 0.05

2.03 ± 0.02

C: Sagaing Fault Zone

101

4.7

5.8

0.864 ± 0.1

1.61 ± 0.02

D: Andaman Basin

87

4.3

4.51

0.611 ± 0.05

2.17 ± 0.03

E: Sumatra Fault Zone

139

4.8

4.75

0.606 ± 0.06

1.96 ± 0.01

F: Hsenwi-Nanting Fault Zones

48

4.8

6.02

1.01 ± 0.3

1.48 ± 0.01

G: Western Thailand

22

4.4

3.98

0.668 ± 0.2

N/A

H: Southern Thailand

9

N/A

N/A

N/A

N/A

I: Jinghong-Mengxing Fault Zones

84

4.2

4.87

0.712 ± 0.08

1.85 ± 0.01

J: Northern Thailand-Dein Bein Phu

62

4

4.72

0.732 ± 0.09

1.86 ± 0.04

K: Song Da-Song Ma Fault Zones

10

N/A

N/A

N/A

N/A

L: Xianshuihe Fault Zone

197

4.5

6.14

0.915 ± 0.09

1.80 ± 0.02

M: Red River Fault Zone

49

4.4

5.99

1.03 ± 0.1

1.48 ± 0.03

N/A, not applicable.

The Sumatra-Andaman interplate and intraslab, zones A and B, respectively, relate to the plate boundary of the Indo-Australian and Eurasian plate collision zone. The M w -9.0 earthquake of December 26, 2004 (number 1 in Figure 1) nucleated in zone A. In addition, the Sagaing fault zone striking north-south in central Myanmar, zone C, and the Sumatra fault zone striking northwest-southeast in Sumatra Island, zone E, are the major inland strike-slip faults in this region. According to Brown and Leicester (1933), an M w -8.0 earthquake (number 2 in Figure 1) in zone C was created by the Sagaing fault zone on May 23, 1912, as were a number of other major earthquakes (Kundu and Gahalaut 2012). Zone D, the Andaman Basin off the coast of Andaman Sea, is occupied by transform fault systems consisting of the Andaman transform zone and Central Andaman rift in addition to the West Andaman and Seuliman faults (Cattin et al. 2009). Tectonically, zones C, D, and E include the plate boundary between the Burma and Sunda plates (Kundu and Gahalaut 2012).

Along the Thailand-Laos-Myanmar border, two strike-slip fault systems were detected. The northwest-southeast striking faults included in the Moei-Tongyi (Pailoplee et al. 2009) and Sri Sawat (Nuttee et al. 2005) fault zones are grouped into zone G. An earthquake of M w -5.9 (number 3 in Figure 1) occurred in the Moei-Tongyi fault zone on February 17, 1975, whereas an M w -5.6 earthquake (number 4 in Figure 1) occurred at the Sri Sawat fault zone on April 22, 1983 (Klaipongphan et al. 1991). In contrast, the northeast-southeast striking faults, the Ranong and Klong Marui fault zones, respectively, are delineated in the border between southernmost Myanmar and southern Thailand, which form zone H. An M w -5.0 earthquake (number 5 in Figure 1) originated in this zone on October 8, 2006 (Yadav et al. 2012), at the northern end of the Ranong fault zone.

In northern Thailand, approximately north-south-trending grabens and their basin-bounding normal faults, such as the Lampang-Thoen (Charusiri et al. 2004), Phrae (Udchachon et al. 2005), and Mae Tha (Rhodes et al. 2004) fault zones, are classified as zone J in northern Thailand-Dein Bein Phu (Pailoplee and Choowong 2013). Most earthquakes nucleated in this area have been high-frequency, small-to-medium-sized earthquakes.

Along the southern China-Vietnam border, the northeast-southwest and northwest-southeast complex shear zones (Polachan et al. 1991) were grouped into the five zones of F, I, and K to M for the Hsenwi-Nanting, Jinghong-Mengxing, Song Da-Song Ma, Xianshuihe, and Red River fault zones, respectively. Instrumental earthquake records reveal that seismic activities in these zones are not quiescent.

Seismicity

The datasets used for this study are of the instrumentally recorded earthquakes and were provided by (i) the Incorporated Research Institutions for Seismology (IRIS) and (ii) the US National Earthquake Information Center (NEIC) earthquake catalogs. The combined data from these two sources yielded approximately 29,990 recorded earthquake events during the 50-year period of 1962 to 2013. These earthquake magnitudes ranged from 1.0 to 9.0 and were reported mostly in the body-wave magnitude scale (m b ). To homogenize the magnitude scale, earthquake events recorded in moment magnitude (M w ) and surface-wave magnitude (M S ) scales were converted to m b , following the relationships proposed by Pailoplee et al. (2009). Both foreshocks and aftershocks, which are meaningless in seismotectonic investigations, were identified and removed by using the assumption reported by Gardner and Knopoff (1974). As a result, approximately 3,730 unique mainshock events remained in the database.

Thereafter, the Genetic Network Analysis System (GENAS) algorithm (Habermann 1987), implemented in the Z-MAP program (Wiemer 2001), was used to screen for any significant levels of bias from man-made seismicity variations in reporting and seismotectonic activities (Wyss 1991; Zuniga and Wiemer 1999). On the basis of the GENAS algorithm, 2,150 unique mainshock events with magnitudes of ≥4.0 m b reported during the period 1974 to 2010 exhibited a smooth cumulative rate of change and thus formed the completeness catalog used here for the statistical seismicity investigation. The distribution of the completeness earthquakes is shown in Figure 1.

Results and discussions

Frequency-magnitude distribution

According to Gutenberg and Richter (1944), the FMD power law can be expressed as
log N = a - bM
(1)

where N is the cumulative number of earthquakes with a magnitude ≥ M. The a and b coefficient values vary in any specific time and space window. Seismotectonically, the a value indicates the entire seismicity level, and the b value relates to tectonic stress (Mogi 1967; Scholz 1968). Lower b values relate to higher levels of accumulated stress (Manakou and Tsapanos 2000).

Although Pailoplee and Choowong (2013) have previously plotted the FMDs and determined the coefficients for all seismic source zones in the MLSEA, the dataset used was not screened to exclude man-made seismicity artifacts. Therefore, to theoretically achieve more accurate results, the FMD a and b values were redetermined (Figure 2) along with the D C values for these 13 zones of the MLSEA (Table 1).
Figure 2
Figure 2

Frequency-magnitude distribution (FMD) plots of the 13 seismic source zones (A to M). Triangles and squares represent the number and cumulative number of each individual magnitude level of earthquake, respectively. The lines represent the FMD linear regression fitted with the observed data. M C is defined as the magnitude of completeness (Woessner and Wiemer 2005).

Due to the lack of available earthquake data, the FMD plots of zones Hand K are unavailable. However, the calculated b values for the other zones were within the range of 0.61 to 1.03. The lowest b value was observed in zone E, whereas the highest b value was detected in zone M.

According to Bayrak and Bayrak (2012), the obtained b values can be categorized into four groups of b < 0.7, 0.7 ≤ b < 0.8, 0.8 ≤ b < 0.9, and b ≥ 0.9. The variation in the b values in this study region, expressed as the four aforementioned category groups, is represented in Figure 3 by various colors. The highest b value group was observed at zones F, L, and M. With regard to the corresponding high a values of 5.99 to 6.14 (Table 1), this group is interpreted as a low-stress region due to frequent tension release through small earthquakes. The second group of b values (0.8 to 0.9) was detected at zones B and C, whereas b values of 0.7 to 0.8 were observed in zones A, I, and J. The b values of less than 0.7 were detected at zones D, E, and G. Regardless of the a value, these comparatively low b value regions may accumulate high tectonic stress levels.
Figure 3
Figure 3

Map showing distributions of estimated b values for zones A to M proposed in MLSEA.

Fractal dimension (D C )

In this study, the D C value was evaluated according to the correlation integral technique (Grassberger and Procaccia 1983) expressed as
C r = 2 N N - 1 N R < r
(2)
where N is the number of earthquakes analyzed, and N(R < r) is the number of event pairs separated by a distance R < r. If the distribution is fractal, the relation obtained will be the same as that in Equation 3 (Kagan and Knopoff 1980), which can be expressed as
C r ~ r D C .
(3)
Unlike the b value, the D C value has not been reported previously for the MLSEA. Therefore, the D C graphs of the 13 seismic source zones in the MLSEA were established (Figure 4). The slopes of the linear fit of graphs log(C(r))-log(r) were the estimated D C values (Table 1). Because of the statistical insufficiency of the available earthquake data, the D C values for zones G, H, and K could not be evaluated.
Figure 4
Figure 4

Graphs showing relationship between log( C ( r )) and log( r ) of earthquake data for 13 seismic source zones (A to M). The slopes of linear fit (solid black lines) are the fractal dimension (D C ).

The calculated D C values varied between 1.48 and 2.17, with the lowest D C values found at zones F and M. The highest D C value, 2.17, was observed at zone D. From the definition of Tosi (1998), which states that the D C value of seismogenically active sources ranges between 0 and 2, most of the MLSEA zones were interpreted as being seismically active.

The D C values were divided into four groups of D C  < 1.5, 1.5 ≤ D C  < 1.7, 1.7 ≤ D C  < 1.9, and D C  ≥ 1.9 (Bayrak and Bayrak 2012) and are mapped in Figure 5 by various colors. The highest D C values were detected in zones A, B, D, and E. Second-level D C values (1.7 to 1.9) were detected in zones I, J, and L; D C values between 1.5 and 1.7 were observed only in zone C.
Figure 5
Figure 5

Map showing distributions of estimated D C values for zones A to M proposed in MLSEA.

Empirically, a D C value close to 1 or 2 signifies that the earthquake epicenters are homogeneously distributed over a line and two-dimensional (2-D) fault plane, respectively (Yadav et al. 2011). Therefore, most zones mentioned exhibit the near-plane characteristics of the seismogenic structures. Moreover, the lowest D C values (<1.5), indicating an active linear fault system, were observed in zones F and M.

D C /b relationship

The D C /b ratio has been suggested as an effective indicator of seismic hazards (Bayrak and Bayrak 2011, 2012). Accordingly, in this study, the correlation between the D C and b values was investigated according to that reported in previous works (Legrand 2002; Wyss et al. 2004; Mandal and Rastogi 2005; Bayrak and Bayrak 2012). On the basis of the obtained D C and b values (Table 1), the empirical D C /b relationship was calibrated as shown in Figure 6a and can be expressed as
D c = 2.80 - 1.22 b
(4)
Figure 6
Figure 6

Empirical relationships. (a) Between the b and D C values and (b) between the a/b ratios and D C values for the 13 seismic source zones (A to M). The straight lines represent the linear regressions fitted with the observed data.

Empirically, the D C /b correlation can be either a positive or a negative regression. For example, positive regression was reported for the San Andreas fault in the USA, in addition to faults in India (Wyss et al. 2004; Yadav et al. 2012), whereas negative correlation was reported for fault zones in Japan, Turkey, and Iran (Hirata 1989; Öncel et al. 1996; Barton et al.1999; Öncel and Wilson 2002; Poroohan and Teimournegad 2010).

For the MLSEA, the D C /b relationship showed a distinct negative linear regression (Figure 6a), which implies increased accumulated stress and decreased earthquake clustering (Barton et al. 1999; Öncel and Wilson 2002). Therefore, in the MLSEA, zones D and E were defined as the highest stress regions, whereas zones F and M exhibited low-stress accumulations. Moreover, zones A, B, C, I, J, and L cluster in the middle of the graph with b values of approximately 0.71 to 0.92 and D C values of approximately 1.61 to 2.03.

In addition, the relation between the D C values and a/b ratios were investigated as per Bayrak and Bayrak (2012). The calibration (Figure 6b) revealed a positive correlation as
D c = 0.27 a / b - 0.01
(5)

A comparison of Figure 6a,b reveals that the distributions of both the D C /b and D C -(a/b) correlations were not significantly variant in terms of the data scatter. However, the D C -(a/b) correlation showed a positive regression, whereas the D C -b correlation showed a negative regression. Zones A and B of the interplate regime were moved from the middle group to the first group, which are of high a/b and D C values. According to the entire seismicity rate, the a value for both zones was higher than that in the other zones. Although Bayrak and Bayrak (2012) mentioned that the D C -(a/b) relationship was more reliable and effective than that of the D C -b for indicating seismic hazards, both relationships in this study depicted an identical accuracy based on the R2 values of 0.65 to 0.68. Therefore, both relationships between D C -b and D C -(a/b) could potentially reflect local seismicity and earthquake risk and can thus be useful in hazard studies, particularly in the MLSEA.

Conclusions

In this study, instrumental earthquake data recorded within the MLSEA were analyzed simultaneously in terms of the FMD b and the D C values from 13 seismic source zones. The results revealed that regional variations in both the b and D C values could imply local tectonic stress and hazard levels. According to the obtained D C values, nearly all of the zones in the MLSEA are seismically active, and earthquakes are homogeneously distributed within the aerial fault plane. In addition, among the 13 seismic sources, zones A, B, D, and E showed comparatively low b and high D C values. Conversely, zones F and M exhibited prominently high b and low D C values.

Both the D C -b and D C -(a/b) relationships were calibrated in this study for the MLSEA region. Although the D C /b correlation showed a negative regression, that for the D C -(a/b) correlation was positive. In contrast to that reported by Bayrak and Bayrak (2012), which states that the D C -(a/b) correlation represents seismotectonics more accurately than that of the D C -b, in the present study of the MLSEA, both showed essentially similar correlations with R2 values of 0.65 to 0.68. Therefore, both relationships can be used as an effective indicator of seismic hazards in the MLSEA region.

On the basis of both D C /b and D C -(a/b) relationships, it is interpreted tectonically that zones F and M are the low-stress zones that maybe safer against seismic hazards than other regions. Moreover, the interplate regimes of zones A, B, D, and E accumulated high levels of tectonic stress, which poses risks for generating large earthquakes in the future. Therefore, it is reasonable to suggest the introduction of seismic hazard warnings and the development of mitigation plans for the ASEAN community.

Declarations

Acknowledgments

This research was jointly sponsored by the Ratchadapiseksomphot Endowment Fund of Chulalongkorn University (RES560530028CC) and the Thailand Research Fund (TRF) Grant for New Researchers. Additional thanks are extended to T. Pailoplee for the preparation of the draft manuscript. We thank the Publication Counseling Unit (PCU), Faculty of Science, and Chulalongkorn University for critical reviews and suggestions for improving the English. We also acknowledge the thoughtful comments and suggestions by Y. Ogawa (Editor in Chief), T. Okada, and anonymous reviewers, which significantly enhanced the quality of this manuscript.

Authors’ Affiliations

(1)
Earthquake and Tectonic Geology Research Unit (EATGRU), Department of Geology, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand

References

  1. Barton DJ, Foulger GR, Henderson JR, Julian BR: Frequency-magnitude statistics and spatial correlation dimensions of earthquakes at Long Valley Caldera, California. Geophys J Int 1999, 138: 563–570. 10.1046/j.1365-246X.1999.00898.xView ArticleGoogle Scholar
  2. Bayrak Y, Bayrak E: An evaluation of earthquake hazard potential for different regions in Western Anatolia using the historical and instrumental earthquake data. Pure Appl Geophys 2011, 169: 1859–1873.View ArticleGoogle Scholar
  3. Bayrak Y, Bayrak E: Regional variations and correlations of Gutenberg–Richter parameters and fractal dimension for the different seismogenic zones in Western Anatolia. J Asian Earth Sci 2012, 58: 98–107.View ArticleGoogle Scholar
  4. Brown JC, Leicester P: The Pyu earthquake of 3rd and 4th December, 1930 and subsequent Burma earthquakes up to January 1932. Memoirs Geolog Survey India 1933, 42(1):1–140.Google Scholar
  5. Cattin R, Chamot-Rooke N, Pubellier M, Rabaute A, Delescluse M, Vigny C, Fleitout L, Dubernet P: Stress change and effective friction coefficient along the Sumatra-Andaman-Sagaing fault system after the 26 December 2004 (Mw = 9.2) and the 28 March 2005 (Mw = 8.7) earthquakes. Geochem Geophys Geosyst 2009, 10: Q03011.View ArticleGoogle Scholar
  6. Charusiri P, Daorerk V, Choowong M, Muangnoicharoen N, Won-in K, Lumjuan A, Kosuwan S, Saithong P, Thonnarat P: The study on the investigations of active faults in Changwat Kanchanaburi area, western Thailand. Technical report: Department of Geology, Faculty of Science, Chulalongkorn University, Bangkok, Thailand; 2004:119. in Thai with English abstract in Thai with English abstractGoogle Scholar
  7. Charusiri P, Choowong M, Charoentitirat T, Jankaew K, Chutakositkanon V, Kanjanapayont P: Geological and physical effect evaluation in the tsunami damage area for restoration and warning system. Technical report: Department of Geology, Faculty of Science, Chulalongkorn University, Bangkok, Thailand; 2005:412. in Thai with English abstract in Thai with English abstractGoogle Scholar
  8. Gardner JK, Knopoff L: Is the sequence of earthquakes in Southern California, with aftershocks removed, Poissonian? Bull Seismol Soc Am 1974, 64(1):363–367.Google Scholar
  9. Grassberger P, Procaccia I: Measuring the strangeness of strange attractors. Physica 1983, D9: 189–208.Google Scholar
  10. Gutenberg B, Richter CF: Frequency of earthquakes in California. Bull Seismol Soc Am 1944, 34: 185–188.Google Scholar
  11. Habermann RE: Man-made changes of seismicity rates. Bull Seismol Soc Am 1987, 77: 141–159.Google Scholar
  12. Hirata T: Fractal dimension of fault system in Japan: fractal structure in rock fracture geometry at various scales. Pure Appl Geophys 1989, 131(1/2):157–170.View ArticleGoogle Scholar
  13. Kagan YY, Knopoff L: Spatial distribution of earthquakes: the two-point correlation function. Geophys J Roy Astron Soc 1980, 62: 303–320. 10.1111/j.1365-246X.1980.tb04857.xView ArticleGoogle Scholar
  14. Klaipongphan S, Chakramanont V, Pinrode J, Chittrakarn P: Geological and seismicity evaluation. St. Louis, Missouri: Proceedings of the Second International Conference on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics; 1991:1357–1363.Google Scholar
  15. Kundu B, Gahalaut VK: Earthquake occurrence processes in the Indo-Burmese wedge and Sagaing fault regions. Tectonophysics 2012, 524–525: 135–146.View ArticleGoogle Scholar
  16. Legrand D: Fractal dimensions of small, intermediate, and large earthquakes. Bull Seismol Soc Am 2002, 92: 3318–3320. 10.1785/0120020025View ArticleGoogle Scholar
  17. Manakou MV, Tsapanos TM: Seismicity and seismic hazard parameters evaluation in the island of Crete and the surrounding area inferred from mixed data files. Tectonophysics 2000, 321: 157–178. 10.1016/S0040-1951(00)00075-5View ArticleGoogle Scholar
  18. Mandal P, Rastogi BK: Self-organized fractal seismicity and bvalue of aftershocks of the 2001 Bhuj earthquake in Kutch (India). Pure Appl Geophys 2005, 162: 53–72. 10.1007/s00024-004-2579-1View ArticleGoogle Scholar
  19. Mogi K: Earthquakes and fractures. Tectonophysics 1967, 5(35–55):2005.Google Scholar
  20. Nutalaya P, Sodsri S, Arnold EP: Series on seismology-volume II-Thailand. In Technical report, Southeast Asia Association of Seismology and Earthquake Engineering Edited by: Arnold EP. 1985, 402.Google Scholar
  21. Nuttee R, Charusiri P, Takashima I, Kosuwan S Proceedings of the International Conference on Geology, Geotechnology and Mineral Resources of Indochina, Khon Kaen, Thailand. Paleo-earthquakes along the southern segment of the Sri Sawat Fault, Kanchanaburi, Western Thailand: morphotectonic and TL-dating evidences 2005. 28–30 November 2005, pp 542–554Google Scholar
  22. Öncel AO, Wilson T: Space-time correlations of seismotectonic parameters and examples from Japan and Turkey preceding the Izmit earthquake. Bull Seismol Soc Am 2002, 92: 339–350. 10.1785/0120000844View ArticleGoogle Scholar
  23. Öncel AO, Main I, Alptekin Ö, Cowie P: Temporal variations in the fractal properties of seismicity in the north Anatolian fault zone between 31°E and 41°E. Pure Appl Geophys 1996, 147: 147–159. 10.1007/BF00876441View ArticleGoogle Scholar
  24. Pailoplee S, Choowong M: Probabilities of earthquake occurrences in Mainland Southeast Asia. Arabian J Geosci 2013, 6: 4993–5006. 10.1007/s12517-012-0749-5View ArticleGoogle Scholar
  25. Pailoplee S, Sugiyama Y, Charusiri P: Deterministic and probabilistic seismic hazard analyses in Thailand and adjacent areas using active fault data. Earth Planets Space 2009, 61: 1313–1325.View ArticleGoogle Scholar
  26. Pailoplee S, Channarong P, Chutakositkanon V: Earthquake activities in the Thailand-Laos-Myanmar border region: a statistical approach. Terr Atmos Ocean Sci 2013, 24(Part II):721–730.View ArticleGoogle Scholar
  27. Polachan S, Pradidtan S, Tongtaow C, Janmaha S, Intrawijitr K, Sangsuwan C: Development of Cenozoic basins in Thailand. Mar Petrol Geol 1991, 8: 84–97. 10.1016/0264-8172(91)90047-5View ArticleGoogle Scholar
  28. Poroohan N, Teimournegad K: An analysis of correlations of seismotectonic parameter and fractal dimension preceding Roudbar-Tarom earthquake (northwest of Iran). Int Conf Geology Seismology 2010, 148–154.Google Scholar
  29. Rhodes BP, Perez R, Lamjuan A, Kosuwan S: Kinematics and tectonic implications of the Mae Kuang Fault, northern Thailand. J Asian Earth Sci 2004, 24(1):79–89. 10.1016/j.jseaes.2003.09.008View ArticleGoogle Scholar
  30. Scholz CH: The frequency–magnitude relation of microfracturing in rock and its relation to earthquakes. Bull Seismol Soc Am 1968, 58: 399–415.Google Scholar
  31. Tosi P: Seismogenic structure behavior revealed by spatial clustering of seismicity in the Umbria-Marche Region (central Italy). Ann Geophys 1998, 41: 215–224.Google Scholar
  32. Udchachon M, Charusiri P, Daorerk V, Won-in K, Takashima I Proceedings of the International Conference on Geology, Geotechnology and Mineral Resources of Indochina, Khon Kaen, Thailand. Paleo-seismic studies along the southeastern portion of the Phrae Basin, Northern Thailand 2005. 28–30 November 2005, pp 511–519 28–30 November 2005, pp 511–519Google Scholar
  33. Wiemer S: A software package to analyze seismicity: ZMAP. Seismol Res 2001, 72: 373–382. 10.1785/gssrl.72.3.373View ArticleGoogle Scholar
  34. Woessner J, Wiemer S: Assessing the quality of earthquake catalogues: estimating the magnitude of completeness and its uncertainty. Bull Seismol Soc Am 2005, 95(2):684–698. 10.1785/0120040007View ArticleGoogle Scholar
  35. Wyss M: Reporting history of the central Aleutians seismograph network and the quiescence preceding the 1986 Andreanof Island earthquake. Bull Seismol Soc Am 1991, 81: 1231–1254.Google Scholar
  36. Wyss M, Sammis CG, Nadeau RM, Wiemer S: Fractal dimension and b-value on creeping and locked patches of the San Andreas fault near Parkfield, California. Bull Seismol Soc Am 2004, 94: 410–421. 10.1785/0120030054View ArticleGoogle Scholar
  37. Yadav RBS, Papadimitriou EE, Karakostas VG, Rastogi BK, Shanker D, Chopra S, Singh AP, Kumar S: The 2007 Talala, Saurashtra, western India earthquake sequence. Tectonic implications and seismicity triggering. J Asian Earth Sci 2011, 40(1):303–314. 10.1016/j.jseaes.2010.07.001View ArticleGoogle Scholar
  38. Yadav RBS, Gahalaut VK, Chopra S, Shan B: Tectonic implications and seismicity triggering during the 2008 Baluchistan, Pakistan earthquake sequence. J Asian Earth Sci 2012, 45(2):167–178.View ArticleGoogle Scholar
  39. Zuniga FR, Wiemer S: Seismicity patterns: are they always related to natural causes? Pageoph 1999, 155: 713–726. 10.1007/s000240050285View ArticleGoogle Scholar

Copyright

© Pailoplee and Choowong; licensee Springer. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

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