Near real-time automatic moment magnitude estimation

Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Gallo, A. [verfasserIn] Costa, G. [verfasserIn] Suhadolc, P. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2014

Schlagwörter:	Moment magnitude Seismic moment Source parameters Strong motion

Übergeordnetes Werk:	Enthalten in: Bulletin of earthquake engineering - Dordrecht : Springer Science + Business Media B.V., 2003, 12(2014), 1 vom: 24. Jan., Seite 185-202
Übergeordnetes Werk:	volume:12 ; year:2014 ; number:1 ; day:24 ; month:01 ; pages:185-202

Links:	Volltext

DOI / URN:	10.1007/s10518-013-9565-x

Katalog-ID:	SPR010756566

Internformat


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520			\|a Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\hbox {M}_{\mathrm{W}}\approx 3%$. The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, %$f_{0}%$, derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with %$\hbox {M}_{\mathrm{W}}\ge 3%$. The estimates of %$f_{0}%$ are less reliable. The results show a scatter, principally for small events with %$\hbox {M}_{\mathrm{W}}\le 3%$, probably due to site effects and inaccurate locations.
650		4	\|a Moment magnitude \|7 (dpeaa)DE-He213
650		4	\|a Seismic moment \|7 (dpeaa)DE-He213
650		4	\|a Source parameters \|7 (dpeaa)DE-He213
650		4	\|a Strong motion \|7 (dpeaa)DE-He213
700	1		\|a Costa, G. \|e verfasserin \|4 aut
700	1		\|a Suhadolc, P. \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Bulletin of earthquake engineering \|d Dordrecht : Springer Science + Business Media B.V., 2003 \|g 12(2014), 1 vom: 24. Jan., Seite 185-202 \|w (DE-627)359787797 \|w (DE-600)2098452-2 \|x 1573-1456 \|7 nnns
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912			\|a GBV_ILN_213
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912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
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912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
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912			\|a GBV_ILN_2011
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912			\|a GBV_ILN_2015
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912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
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912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2070
912			\|a GBV_ILN_2086
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912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2107
912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2116
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2119
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912			\|a GBV_ILN_4037
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912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4246
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4336
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912			\|a GBV_ILN_4393
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936	b	k	\|a 38.38 \|q ASE
936	b	k	\|a 56.11 \|q ASE
951			\|a AR
952			\|d 12 \|j 2014 \|e 1 \|b 24 \|c 01 \|h 185-202

Indexfelder

author_variant	a g ag g c gc p s ps
matchkey_str	article:15731456:2014----::erelieuoaimmnmgi
hierarchy_sort_str	2014
bklnumber	38.38 56.11
publishDate	2014
allfields	10.1007/s10518-013-9565-x doi (DE-627)SPR010756566 (SPR)s10518-013-9565-x-e DE-627 ger DE-627 rakwb eng 550 ASE 38.38 bkl 56.11 bkl Gallo, A. verfasserin aut Near real-time automatic moment magnitude estimation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\hbox {M}_{\mathrm{W}}\approx 3%$. The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, %$f_{0}%$, derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with %$\hbox {M}_{\mathrm{W}}\ge 3%$. The estimates of %$f_{0}%$ are less reliable. The results show a scatter, principally for small events with %$\hbox {M}_{\mathrm{W}}\le 3%$, probably due to site effects and inaccurate locations. Moment magnitude (dpeaa)DE-He213 Seismic moment (dpeaa)DE-He213 Source parameters (dpeaa)DE-He213 Strong motion (dpeaa)DE-He213 Costa, G. verfasserin aut Suhadolc, P. verfasserin aut Enthalten in Bulletin of earthquake engineering Dordrecht : Springer Science + Business Media B.V., 2003 12(2014), 1 vom: 24. Jan., Seite 185-202 (DE-627)359787797 (DE-600)2098452-2 1573-1456 nnns volume:12 year:2014 number:1 day:24 month:01 pages:185-202 https://dx.doi.org/10.1007/s10518-013-9565-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.38 ASE 56.11 ASE AR 12 2014 1 24 01 185-202
spelling	10.1007/s10518-013-9565-x doi (DE-627)SPR010756566 (SPR)s10518-013-9565-x-e DE-627 ger DE-627 rakwb eng 550 ASE 38.38 bkl 56.11 bkl Gallo, A. verfasserin aut Near real-time automatic moment magnitude estimation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\hbox {M}_{\mathrm{W}}\approx 3%$. The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, %$f_{0}%$, derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with %$\hbox {M}_{\mathrm{W}}\ge 3%$. The estimates of %$f_{0}%$ are less reliable. The results show a scatter, principally for small events with %$\hbox {M}_{\mathrm{W}}\le 3%$, probably due to site effects and inaccurate locations. Moment magnitude (dpeaa)DE-He213 Seismic moment (dpeaa)DE-He213 Source parameters (dpeaa)DE-He213 Strong motion (dpeaa)DE-He213 Costa, G. verfasserin aut Suhadolc, P. verfasserin aut Enthalten in Bulletin of earthquake engineering Dordrecht : Springer Science + Business Media B.V., 2003 12(2014), 1 vom: 24. Jan., Seite 185-202 (DE-627)359787797 (DE-600)2098452-2 1573-1456 nnns volume:12 year:2014 number:1 day:24 month:01 pages:185-202 https://dx.doi.org/10.1007/s10518-013-9565-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.38 ASE 56.11 ASE AR 12 2014 1 24 01 185-202
allfields_unstemmed	10.1007/s10518-013-9565-x doi (DE-627)SPR010756566 (SPR)s10518-013-9565-x-e DE-627 ger DE-627 rakwb eng 550 ASE 38.38 bkl 56.11 bkl Gallo, A. verfasserin aut Near real-time automatic moment magnitude estimation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\hbox {M}_{\mathrm{W}}\approx 3%$. The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, %$f_{0}%$, derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with %$\hbox {M}_{\mathrm{W}}\ge 3%$. The estimates of %$f_{0}%$ are less reliable. The results show a scatter, principally for small events with %$\hbox {M}_{\mathrm{W}}\le 3%$, probably due to site effects and inaccurate locations. Moment magnitude (dpeaa)DE-He213 Seismic moment (dpeaa)DE-He213 Source parameters (dpeaa)DE-He213 Strong motion (dpeaa)DE-He213 Costa, G. verfasserin aut Suhadolc, P. verfasserin aut Enthalten in Bulletin of earthquake engineering Dordrecht : Springer Science + Business Media B.V., 2003 12(2014), 1 vom: 24. Jan., Seite 185-202 (DE-627)359787797 (DE-600)2098452-2 1573-1456 nnns volume:12 year:2014 number:1 day:24 month:01 pages:185-202 https://dx.doi.org/10.1007/s10518-013-9565-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.38 ASE 56.11 ASE AR 12 2014 1 24 01 185-202
allfieldsGer	10.1007/s10518-013-9565-x doi (DE-627)SPR010756566 (SPR)s10518-013-9565-x-e DE-627 ger DE-627 rakwb eng 550 ASE 38.38 bkl 56.11 bkl Gallo, A. verfasserin aut Near real-time automatic moment magnitude estimation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\hbox {M}_{\mathrm{W}}\approx 3%$. The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, %$f_{0}%$, derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with %$\hbox {M}_{\mathrm{W}}\ge 3%$. The estimates of %$f_{0}%$ are less reliable. The results show a scatter, principally for small events with %$\hbox {M}_{\mathrm{W}}\le 3%$, probably due to site effects and inaccurate locations. Moment magnitude (dpeaa)DE-He213 Seismic moment (dpeaa)DE-He213 Source parameters (dpeaa)DE-He213 Strong motion (dpeaa)DE-He213 Costa, G. verfasserin aut Suhadolc, P. verfasserin aut Enthalten in Bulletin of earthquake engineering Dordrecht : Springer Science + Business Media B.V., 2003 12(2014), 1 vom: 24. Jan., Seite 185-202 (DE-627)359787797 (DE-600)2098452-2 1573-1456 nnns volume:12 year:2014 number:1 day:24 month:01 pages:185-202 https://dx.doi.org/10.1007/s10518-013-9565-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.38 ASE 56.11 ASE AR 12 2014 1 24 01 185-202
allfieldsSound	10.1007/s10518-013-9565-x doi (DE-627)SPR010756566 (SPR)s10518-013-9565-x-e DE-627 ger DE-627 rakwb eng 550 ASE 38.38 bkl 56.11 bkl Gallo, A. verfasserin aut Near real-time automatic moment magnitude estimation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\hbox {M}_{\mathrm{W}}\approx 3%$. The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, %$f_{0}%$, derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with %$\hbox {M}_{\mathrm{W}}\ge 3%$. The estimates of %$f_{0}%$ are less reliable. The results show a scatter, principally for small events with %$\hbox {M}_{\mathrm{W}}\le 3%$, probably due to site effects and inaccurate locations. Moment magnitude (dpeaa)DE-He213 Seismic moment (dpeaa)DE-He213 Source parameters (dpeaa)DE-He213 Strong motion (dpeaa)DE-He213 Costa, G. verfasserin aut Suhadolc, P. verfasserin aut Enthalten in Bulletin of earthquake engineering Dordrecht : Springer Science + Business Media B.V., 2003 12(2014), 1 vom: 24. Jan., Seite 185-202 (DE-627)359787797 (DE-600)2098452-2 1573-1456 nnns volume:12 year:2014 number:1 day:24 month:01 pages:185-202 https://dx.doi.org/10.1007/s10518-013-9565-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.38 ASE 56.11 ASE AR 12 2014 1 24 01 185-202
language	English
source	Enthalten in Bulletin of earthquake engineering 12(2014), 1 vom: 24. Jan., Seite 185-202 volume:12 year:2014 number:1 day:24 month:01 pages:185-202
sourceStr	Enthalten in Bulletin of earthquake engineering 12(2014), 1 vom: 24. Jan., Seite 185-202 volume:12 year:2014 number:1 day:24 month:01 pages:185-202
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Moment magnitude Seismic moment Source parameters Strong motion
dewey-raw	550
isfreeaccess_bool	false
container_title	Bulletin of earthquake engineering
authorswithroles_txt_mv	Gallo, A. @@aut@@ Costa, G. @@aut@@ Suhadolc, P. @@aut@@
publishDateDaySort_date	2014-01-24T00:00:00Z
hierarchy_top_id	359787797
dewey-sort	3550
id	SPR010756566
language_de	englisch
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author	Gallo, A.
spellingShingle	Gallo, A. ddc 550 bkl 38.38 bkl 56.11 misc Moment magnitude misc Seismic moment misc Source parameters misc Strong motion Near real-time automatic moment magnitude estimation
authorStr	Gallo, A.
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topic_title	550 ASE 38.38 bkl 56.11 bkl Near real-time automatic moment magnitude estimation Moment magnitude (dpeaa)DE-He213 Seismic moment (dpeaa)DE-He213 Source parameters (dpeaa)DE-He213 Strong motion (dpeaa)DE-He213
topic	ddc 550 bkl 38.38 bkl 56.11 misc Moment magnitude misc Seismic moment misc Source parameters misc Strong motion
topic_unstemmed	ddc 550 bkl 38.38 bkl 56.11 misc Moment magnitude misc Seismic moment misc Source parameters misc Strong motion
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title	Near real-time automatic moment magnitude estimation
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title_full	Near real-time automatic moment magnitude estimation
author_sort	Gallo, A.
journal	Bulletin of earthquake engineering
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author_browse	Gallo, A. Costa, G. Suhadolc, P.
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class	550 ASE 38.38 bkl 56.11 bkl
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author-letter	Gallo, A.
doi_str_mv	10.1007/s10518-013-9565-x
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title_sort	near real-time automatic moment magnitude estimation
title_auth	Near real-time automatic moment magnitude estimation
abstract	Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\hbox {M}_{\mathrm{W}}\approx 3%$. The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, %$f_{0}%$, derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with %$\hbox {M}_{\mathrm{W}}\ge 3%$. The estimates of %$f_{0}%$ are less reliable. The results show a scatter, principally for small events with %$\hbox {M}_{\mathrm{W}}\le 3%$, probably due to site effects and inaccurate locations.
abstractGer	Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\hbox {M}_{\mathrm{W}}\approx 3%$. The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, %$f_{0}%$, derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with %$\hbox {M}_{\mathrm{W}}\ge 3%$. The estimates of %$f_{0}%$ are less reliable. The results show a scatter, principally for small events with %$\hbox {M}_{\mathrm{W}}\le 3%$, probably due to site effects and inaccurate locations.
abstract_unstemmed	Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\hbox {M}_{\mathrm{W}}\approx 3%$. The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, %$f_{0}%$, derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with %$\hbox {M}_{\mathrm{W}}\ge 3%$. The estimates of %$f_{0}%$ are less reliable. The results show a scatter, principally for small events with %$\hbox {M}_{\mathrm{W}}\le 3%$, probably due to site effects and inaccurate locations.
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title_short	Near real-time automatic moment magnitude estimation
url	https://dx.doi.org/10.1007/s10518-013-9565-x
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author2	Costa, G. Suhadolc, P.
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doi_str	10.1007/s10518-013-9565-x
up_date	2024-07-03T18:05:58.679Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR010756566</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220110221919.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2014 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10518-013-9565-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR010756566</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10518-013-9565-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">550</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">38.38</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">56.11</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Gallo, A.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Near real-time automatic moment magnitude estimation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2014</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events %$\hbox {M}_{\mathrm{W}}\approx 3%$. The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, %$f_{0}%$, derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with %$\hbox {M}_{\mathrm{W}}\ge 3%$. The estimates of %$f_{0}%$ are less reliable. The results show a scatter, principally for small events with %$\hbox {M}_{\mathrm{W}}\le 3%$, probably due to site effects and inaccurate locations.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Moment magnitude</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Seismic moment</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Source parameters</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Strong motion</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Costa, G.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Suhadolc, P.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Bulletin of earthquake engineering</subfield><subfield code="d">Dordrecht : Springer Science + Business Media B.V., 2003</subfield><subfield code="g">12(2014), 1 vom: 24. Jan., Seite 185-202</subfield><subfield code="w">(DE-627)359787797</subfield><subfield code="w">(DE-600)2098452-2</subfield><subfield code="x">1573-1456</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:12</subfield><subfield code="g">year:2014</subfield><subfield code="g">number:1</subfield><subfield code="g">day:24</subfield><subfield code="g">month:01</subfield><subfield code="g">pages:185-202</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s10518-013-9565-x</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" 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