Estimating the validity of the recognition results of earthquake-prone areas using the ArcMap View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-10

AUTHORS

A. Gorshkov, O. Novikova

ABSTRACT

In 1972, V. Keilis-Borok and I. Gelfand introduced the phenomenological approach based on the morphostructural zoning and pattern recognition for identification of earthquake-prone areas. This methodology identifies seismogenic nodes capable of generating strong earthquakes on the basis of geological, morphological, and geophysical data, which do not contain information on past seismicity. In the period 1972–2018, totally, 26 worldwide seismic regions have been studied and maps showing the recognized earthquake-prone areas in each region have been published. After that, 11 of these regions were hit by earthquakes of the relevant sizes. The goal of this work is to analyze the correlation of the post-publication events with seismogenic nodes defined in these 11 regions. The test was performed using the NEIC earthquake catalog because it uniformly defines the location and magnitudes of earthquakes over the globe. The ArcMap facilities were exploited to plot the post-publication events on the maps showing the recognized seismogenic nodes. We found that about 86% of such events fall in the recognized seismogenic nodes. The performed test proved the sufficient validity of the methodology for identifying areas capable of strong earthquakes and confirms the idea on nucleating strong earthquakes at the nodes. More... »

PAGES

843-853

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11600-018-0177-3

DOI

http://dx.doi.org/10.1007/s11600-018-0177-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105642920


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0404", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Geophysics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/04", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Earth Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Institute of Earthquake Prediction Theory and Mathematical Geophysics", 
          "id": "https://www.grid.ac/institutes/grid.425208.9", 
          "name": [
            "Institute of Earthquake Prediction Theory and Mathematical Geophysics, Profsouznaya 84/32, 117997, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gorshkov", 
        "givenName": "A.", 
        "id": "sg:person.016242245266.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016242245266.38"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Earthquake Prediction Theory and Mathematical Geophysics", 
          "id": "https://www.grid.ac/institutes/grid.425208.9", 
          "name": [
            "Institute of Earthquake Prediction Theory and Mathematical Geophysics, Profsouznaya 84/32, 117997, Moscow, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Novikova", 
        "givenName": "O.", 
        "id": "sg:person.013154411064.78", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013154411064.78"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1155/2012/419143", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003463351"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/jb082i036p05658", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008183909"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02893012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011386035", 
          "https://doi.org/10.1007/bf02893012"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02893012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011386035", 
          "https://doi.org/10.1007/bf02893012"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-3121.2009.00879.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021415587"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-3121.2009.00879.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021415587"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s1069351314020116", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021484272", 
          "https://doi.org/10.1134/s1069351314020116"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s1028334x13060159", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030827991", 
          "https://doi.org/10.1134/s1028334x13060159"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/jb084ib11p06140", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034350888"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12210-010-0075-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036556771", 
          "https://doi.org/10.1007/s12210-010-0075-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12210-010-0075-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036556771", 
          "https://doi.org/10.1007/s12210-010-0075-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/cs007p0037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040914492"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-94-011-1614-5_42", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041909100", 
          "https://doi.org/10.1007/978-94-011-1614-5_42"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-94-011-1614-5_42", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041909100", 
          "https://doi.org/10.1007/978-94-011-1614-5_42"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0031-9201(76)90067-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043165267"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0031-9201(76)90067-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043165267"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-662-05298-3_6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046209733", 
          "https://doi.org/10.1007/978-3-662-05298-3_6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0031-9201(80)90135-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046335483"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0031-9201(80)90135-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046335483"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/pl00001101", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047021671", 
          "https://doi.org/10.1007/pl00001101"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0040-1951(72)90031-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048412890"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0040-1951(72)90031-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048412890"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11069-012-0125-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050269837", 
          "https://doi.org/10.1007/s11069-012-0125-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-0-444-88889-1.50009-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051593280"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0040-1951(99)00024-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051898201"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.12681/bgsg.11855", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090974349"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s0742046317060021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101276827", 
          "https://doi.org/10.1134/s0742046317060021"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s0742046317060021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101276827", 
          "https://doi.org/10.1134/s0742046317060021"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s0742046317060021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101276827", 
          "https://doi.org/10.1134/s0742046317060021"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s1028334x1803025x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103606172", 
          "https://doi.org/10.1134/s1028334x1803025x"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-10", 
    "datePublishedReg": "2018-10-01", 
    "description": "In 1972, V. Keilis-Borok and I. Gelfand introduced the phenomenological approach based on the morphostructural zoning and pattern recognition for identification of earthquake-prone areas. This methodology identifies seismogenic nodes capable of generating strong earthquakes on the basis of geological, morphological, and geophysical data, which do not contain information on past seismicity. In the period 1972\u20132018, totally, 26 worldwide seismic regions have been studied and maps showing the recognized earthquake-prone areas in each region have been published. After that, 11 of these regions were hit by earthquakes of the relevant sizes. The goal of this work is to analyze the correlation of the post-publication events with seismogenic nodes defined in these 11 regions. The test was performed using the NEIC earthquake catalog because it uniformly defines the location and magnitudes of earthquakes over the globe. The ArcMap facilities were exploited to plot the post-publication events on the maps showing the recognized seismogenic nodes. We found that about 86% of such events fall in the recognized seismogenic nodes. The performed test proved the sufficient validity of the methodology for identifying areas capable of strong earthquakes and confirms the idea on nucleating strong earthquakes at the nodes.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s11600-018-0177-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.6740940", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1139940", 
        "issn": [
          "1895-6572", 
          "1895-7455"
        ], 
        "name": "Acta Geophysica", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "5", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "66"
      }
    ], 
    "name": "Estimating the validity of the recognition results of earthquake-prone areas using the ArcMap", 
    "pagination": "843-853", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "b80dab4420e0008ce8861ad95f4572c3fb1df8c6202cafacdade37113236f84b"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11600-018-0177-3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1105642920"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11600-018-0177-3", 
      "https://app.dimensions.ai/details/publication/pub.1105642920"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T21:47", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8687_00000568.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs11600-018-0177-3"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11600-018-0177-3'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11600-018-0177-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11600-018-0177-3'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11600-018-0177-3'


 

This table displays all metadata directly associated to this object as RDF triples.

143 TRIPLES      21 PREDICATES      48 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11600-018-0177-3 schema:about anzsrc-for:04
2 anzsrc-for:0404
3 schema:author N0cb4f8cfe2fa40d4b8fd2ea6ca43518b
4 schema:citation sg:pub.10.1007/978-3-662-05298-3_6
5 sg:pub.10.1007/978-94-011-1614-5_42
6 sg:pub.10.1007/bf02893012
7 sg:pub.10.1007/pl00001101
8 sg:pub.10.1007/s11069-012-0125-5
9 sg:pub.10.1007/s12210-010-0075-3
10 sg:pub.10.1134/s0742046317060021
11 sg:pub.10.1134/s1028334x13060159
12 sg:pub.10.1134/s1028334x1803025x
13 sg:pub.10.1134/s1069351314020116
14 https://doi.org/10.1016/0031-9201(76)90067-4
15 https://doi.org/10.1016/0031-9201(80)90135-1
16 https://doi.org/10.1016/0040-1951(72)90031-5
17 https://doi.org/10.1016/b978-0-444-88889-1.50009-1
18 https://doi.org/10.1016/s0040-1951(99)00024-4
19 https://doi.org/10.1029/cs007p0037
20 https://doi.org/10.1029/jb082i036p05658
21 https://doi.org/10.1029/jb084ib11p06140
22 https://doi.org/10.1111/j.1365-3121.2009.00879.x
23 https://doi.org/10.1155/2012/419143
24 https://doi.org/10.12681/bgsg.11855
25 schema:datePublished 2018-10
26 schema:datePublishedReg 2018-10-01
27 schema:description In 1972, V. Keilis-Borok and I. Gelfand introduced the phenomenological approach based on the morphostructural zoning and pattern recognition for identification of earthquake-prone areas. This methodology identifies seismogenic nodes capable of generating strong earthquakes on the basis of geological, morphological, and geophysical data, which do not contain information on past seismicity. In the period 1972–2018, totally, 26 worldwide seismic regions have been studied and maps showing the recognized earthquake-prone areas in each region have been published. After that, 11 of these regions were hit by earthquakes of the relevant sizes. The goal of this work is to analyze the correlation of the post-publication events with seismogenic nodes defined in these 11 regions. The test was performed using the NEIC earthquake catalog because it uniformly defines the location and magnitudes of earthquakes over the globe. The ArcMap facilities were exploited to plot the post-publication events on the maps showing the recognized seismogenic nodes. We found that about 86% of such events fall in the recognized seismogenic nodes. The performed test proved the sufficient validity of the methodology for identifying areas capable of strong earthquakes and confirms the idea on nucleating strong earthquakes at the nodes.
28 schema:genre research_article
29 schema:inLanguage en
30 schema:isAccessibleForFree false
31 schema:isPartOf N9189f343e53a49b8a85eb14117d4f9aa
32 Nfcff79a3235b4bf8b75e5eea19840aa7
33 sg:journal.1139940
34 schema:name Estimating the validity of the recognition results of earthquake-prone areas using the ArcMap
35 schema:pagination 843-853
36 schema:productId N97f204af092f46afbb444f0349b5317e
37 Nb6ebe189405d4438b85d34ee704e6894
38 Nf2b5a66a0c9b499792c9f08565c247e6
39 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105642920
40 https://doi.org/10.1007/s11600-018-0177-3
41 schema:sdDatePublished 2019-04-10T21:47
42 schema:sdLicense https://scigraph.springernature.com/explorer/license/
43 schema:sdPublisher Nbc390de18d6a4498b5b7f3eb6854bb4c
44 schema:url https://link.springer.com/10.1007%2Fs11600-018-0177-3
45 sgo:license sg:explorer/license/
46 sgo:sdDataset articles
47 rdf:type schema:ScholarlyArticle
48 N0cb4f8cfe2fa40d4b8fd2ea6ca43518b rdf:first sg:person.016242245266.38
49 rdf:rest Ndd8c8e9441184fc39f3ce9807f3711a3
50 N9189f343e53a49b8a85eb14117d4f9aa schema:volumeNumber 66
51 rdf:type schema:PublicationVolume
52 N97f204af092f46afbb444f0349b5317e schema:name readcube_id
53 schema:value b80dab4420e0008ce8861ad95f4572c3fb1df8c6202cafacdade37113236f84b
54 rdf:type schema:PropertyValue
55 Nb6ebe189405d4438b85d34ee704e6894 schema:name dimensions_id
56 schema:value pub.1105642920
57 rdf:type schema:PropertyValue
58 Nbc390de18d6a4498b5b7f3eb6854bb4c schema:name Springer Nature - SN SciGraph project
59 rdf:type schema:Organization
60 Ndd8c8e9441184fc39f3ce9807f3711a3 rdf:first sg:person.013154411064.78
61 rdf:rest rdf:nil
62 Nf2b5a66a0c9b499792c9f08565c247e6 schema:name doi
63 schema:value 10.1007/s11600-018-0177-3
64 rdf:type schema:PropertyValue
65 Nfcff79a3235b4bf8b75e5eea19840aa7 schema:issueNumber 5
66 rdf:type schema:PublicationIssue
67 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
68 schema:name Earth Sciences
69 rdf:type schema:DefinedTerm
70 anzsrc-for:0404 schema:inDefinedTermSet anzsrc-for:
71 schema:name Geophysics
72 rdf:type schema:DefinedTerm
73 sg:grant.6740940 http://pending.schema.org/fundedItem sg:pub.10.1007/s11600-018-0177-3
74 rdf:type schema:MonetaryGrant
75 sg:journal.1139940 schema:issn 1895-6572
76 1895-7455
77 schema:name Acta Geophysica
78 rdf:type schema:Periodical
79 sg:person.013154411064.78 schema:affiliation https://www.grid.ac/institutes/grid.425208.9
80 schema:familyName Novikova
81 schema:givenName O.
82 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013154411064.78
83 rdf:type schema:Person
84 sg:person.016242245266.38 schema:affiliation https://www.grid.ac/institutes/grid.425208.9
85 schema:familyName Gorshkov
86 schema:givenName A.
87 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016242245266.38
88 rdf:type schema:Person
89 sg:pub.10.1007/978-3-662-05298-3_6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046209733
90 https://doi.org/10.1007/978-3-662-05298-3_6
91 rdf:type schema:CreativeWork
92 sg:pub.10.1007/978-94-011-1614-5_42 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041909100
93 https://doi.org/10.1007/978-94-011-1614-5_42
94 rdf:type schema:CreativeWork
95 sg:pub.10.1007/bf02893012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011386035
96 https://doi.org/10.1007/bf02893012
97 rdf:type schema:CreativeWork
98 sg:pub.10.1007/pl00001101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047021671
99 https://doi.org/10.1007/pl00001101
100 rdf:type schema:CreativeWork
101 sg:pub.10.1007/s11069-012-0125-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050269837
102 https://doi.org/10.1007/s11069-012-0125-5
103 rdf:type schema:CreativeWork
104 sg:pub.10.1007/s12210-010-0075-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036556771
105 https://doi.org/10.1007/s12210-010-0075-3
106 rdf:type schema:CreativeWork
107 sg:pub.10.1134/s0742046317060021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101276827
108 https://doi.org/10.1134/s0742046317060021
109 rdf:type schema:CreativeWork
110 sg:pub.10.1134/s1028334x13060159 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030827991
111 https://doi.org/10.1134/s1028334x13060159
112 rdf:type schema:CreativeWork
113 sg:pub.10.1134/s1028334x1803025x schema:sameAs https://app.dimensions.ai/details/publication/pub.1103606172
114 https://doi.org/10.1134/s1028334x1803025x
115 rdf:type schema:CreativeWork
116 sg:pub.10.1134/s1069351314020116 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021484272
117 https://doi.org/10.1134/s1069351314020116
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1016/0031-9201(76)90067-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043165267
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1016/0031-9201(80)90135-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046335483
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1016/0040-1951(72)90031-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048412890
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/b978-0-444-88889-1.50009-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051593280
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/s0040-1951(99)00024-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051898201
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1029/cs007p0037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040914492
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1029/jb082i036p05658 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008183909
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1029/jb084ib11p06140 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034350888
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1111/j.1365-3121.2009.00879.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1021415587
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1155/2012/419143 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003463351
138 rdf:type schema:CreativeWork
139 https://doi.org/10.12681/bgsg.11855 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090974349
140 rdf:type schema:CreativeWork
141 https://www.grid.ac/institutes/grid.425208.9 schema:alternateName Institute of Earthquake Prediction Theory and Mathematical Geophysics
142 schema:name Institute of Earthquake Prediction Theory and Mathematical Geophysics, Profsouznaya 84/32, 117997, Moscow, Russia
143 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...