Ionospheric temporal variations over the region of Turkey: a study based on long-time TEC observations View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-12

AUTHORS

Erman Şentürk, Murat Selim Çepni

ABSTRACT

In this study, daily mean vertical total electron content (VTEC) and daily mean 2-h VTEC values were obtained from Center for Orbit Determination in Europe–Global Ionosphere Maps (CODE–GIM) data over the region of Turkey between January 1, 2003, and December 31, 2016. The time interval is sufficient to reflect temporal changes of the ionosphere. The daily mean VTEC data was used to analyze the space weather effects on the VTEC variability and daily mean 2-h VTEC data was utilized to see the pattern of the diurnal, monthly, seasonal and yearly variation of VTEC values. The highest correlation was found between VTEC and F10.7 (r = 0.83). Totally, 40 major geomagnetic storms were identified that 45% of the storms are caused a decrease and 55% of the storms are caused an increase in VTEC variation. The maximum VTEC is shown at 13:00 LT and the minimum VTEC is shown at 03:00 LT according to diurnal variation of the 14-year mean 2-h VTEC. The maximum VTEC is shown on April and the minimum VTEC is shown on July according to diurnal variation of monthly mean VTEC. Diurnal variation of seasonal mean VTEC and its standard deviations are higher in equinox than solstices. Diurnal variation of yearly mean VTEC has a significant change from low to high solar activity periods. More... »

PAGES

1-15

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40328-018-0233-0

DOI

http://dx.doi.org/10.1007/s40328-018-0233-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106084755


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/2008/0201", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Astronomical and Space Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/02", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Kocaeli", 
          "id": "https://www.grid.ac/institutes/grid.411105.0", 
          "name": [
            "Department of Surveying Engineering, Kocaeli University, Kocaeli, Turkey"
          ], 
          "type": "Organization"
        }, 
        "familyName": "\u015eent\u00fcrk", 
        "givenName": "Erman", 
        "id": "sg:person.015622263443.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015622263443.81"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Kocaeli", 
          "id": "https://www.grid.ac/institutes/grid.411105.0", 
          "name": [
            "Department of Surveying Engineering, Kocaeli University, Kocaeli, Turkey"
          ], 
          "type": "Organization"
        }, 
        "familyName": "\u00c7epni", 
        "givenName": "Murat Selim", 
        "id": "sg:person.01313575672.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01313575672.48"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1002/2016ja023253", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000458838"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2000gl012551", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001569196"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/jz064i003p00305", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002133024"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0133378", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003620472"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/cjg2.903", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007816886"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2005rs003327", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008384151"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/angeo-27-1047-2009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009282626"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/95ja03343", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015223274"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jastp.2016.10.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016037747"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.asr.2010.07.017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017089662"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0021-9169(69)90081-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018058820"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0021-9169(69)90081-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018058820"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jastp.2006.08.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020279589"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/2014ja020552", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020695613"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/isprsarchives-xl-1-w5-339-2015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025075856"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.asr.2012.12.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025525369"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jastp.2003.09.017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032757783"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/swe.20064", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037557995"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0021-9169(69)90110-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039489246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0021-9169(69)90110-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039489246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10509-011-0973-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044137843", 
          "https://doi.org/10.1007/s10509-011-0973-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.asr.2013.05.032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044484729"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1048098428", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-7091-5126-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048098428", 
          "https://doi.org/10.1007/978-3-7091-5126-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-7091-5126-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048098428", 
          "https://doi.org/10.1007/978-3-7091-5126-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jastp.2005.02.023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050655317"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2006sw000281", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051310798"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jastp.2017.02.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083884309"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10509-017-3043-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084024959", 
          "https://doi.org/10.1007/s10509-017-3043-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10509-017-3043-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084024959", 
          "https://doi.org/10.1007/s10509-017-3043-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00190-017-1026-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084926682", 
          "https://doi.org/10.1007/s00190-017-1026-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00190-017-1026-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084926682", 
          "https://doi.org/10.1007/s00190-017-1026-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2514/4.866388", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099157035"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "In this study, daily mean vertical total electron content (VTEC) and daily mean 2-h VTEC values were obtained from Center for Orbit Determination in Europe\u2013Global Ionosphere Maps (CODE\u2013GIM) data over the region of Turkey between January 1, 2003, and December 31, 2016. The time interval is sufficient to reflect temporal changes of the ionosphere. The daily mean VTEC data was used to analyze the space weather effects on the VTEC variability and daily mean 2-h VTEC data was utilized to see the pattern of the diurnal, monthly, seasonal and yearly variation of VTEC values. The highest correlation was found between VTEC and F10.7 (r = 0.83). Totally, 40 major geomagnetic storms were identified that 45% of the storms are caused a decrease and 55% of the storms are caused an increase in VTEC variation. The maximum VTEC is shown at 13:00 LT and the minimum VTEC is shown at 03:00 LT according to diurnal variation of the 14-year mean 2-h VTEC. The maximum VTEC is shown on April and the minimum VTEC is shown on July according to diurnal variation of monthly mean VTEC. Diurnal variation of seasonal mean VTEC and its standard deviations are higher in equinox than solstices. Diurnal variation of yearly mean VTEC has a significant change from low to high solar activity periods.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s40328-018-0233-0", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136254", 
        "issn": [
          "2213-5812", 
          "2213-5820"
        ], 
        "name": "Acta Geodaetica et Geophysica", 
        "type": "Periodical"
      }
    ], 
    "name": "Ionospheric temporal variations over the region of Turkey: a study based on long-time TEC observations", 
    "pagination": "1-15", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "aa3ad31b3d50df4eaa10192553e695d9dcdab08b4d96d13be5a0f8b101a2976c"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s40328-018-0233-0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1106084755"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s40328-018-0233-0", 
      "https://app.dimensions.ai/details/publication/pub.1106084755"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T00:10", 
    "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_8695_00000485.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/s40328-018-0233-0"
  }
]
 

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/s40328-018-0233-0'

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/s40328-018-0233-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s40328-018-0233-0'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s40328-018-0233-0'


 

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

149 TRIPLES      21 PREDICATES      53 URIs      17 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s40328-018-0233-0 schema:about anzsrc-for:02
2 anzsrc-for:0201
3 schema:author N0f43f51d80574b1cbe609f94fbcac4d6
4 schema:citation sg:pub.10.1007/978-3-7091-5126-6
5 sg:pub.10.1007/s00190-017-1026-x
6 sg:pub.10.1007/s10509-011-0973-6
7 sg:pub.10.1007/s10509-017-3043-x
8 https://app.dimensions.ai/details/publication/pub.1048098428
9 https://doi.org/10.1002/2014ja020552
10 https://doi.org/10.1002/2016ja023253
11 https://doi.org/10.1002/cjg2.903
12 https://doi.org/10.1002/swe.20064
13 https://doi.org/10.1016/0021-9169(69)90081-6
14 https://doi.org/10.1016/0021-9169(69)90110-x
15 https://doi.org/10.1016/j.asr.2010.07.017
16 https://doi.org/10.1016/j.asr.2012.12.005
17 https://doi.org/10.1016/j.asr.2013.05.032
18 https://doi.org/10.1016/j.jastp.2003.09.017
19 https://doi.org/10.1016/j.jastp.2005.02.023
20 https://doi.org/10.1016/j.jastp.2006.08.008
21 https://doi.org/10.1016/j.jastp.2016.10.004
22 https://doi.org/10.1016/j.jastp.2017.02.009
23 https://doi.org/10.1029/2000gl012551
24 https://doi.org/10.1029/2005rs003327
25 https://doi.org/10.1029/2006sw000281
26 https://doi.org/10.1029/95ja03343
27 https://doi.org/10.1029/jz064i003p00305
28 https://doi.org/10.1371/journal.pone.0133378
29 https://doi.org/10.2514/4.866388
30 https://doi.org/10.5194/angeo-27-1047-2009
31 https://doi.org/10.5194/isprsarchives-xl-1-w5-339-2015
32 schema:datePublished 2018-12
33 schema:datePublishedReg 2018-12-01
34 schema:description In this study, daily mean vertical total electron content (VTEC) and daily mean 2-h VTEC values were obtained from Center for Orbit Determination in Europe–Global Ionosphere Maps (CODE–GIM) data over the region of Turkey between January 1, 2003, and December 31, 2016. The time interval is sufficient to reflect temporal changes of the ionosphere. The daily mean VTEC data was used to analyze the space weather effects on the VTEC variability and daily mean 2-h VTEC data was utilized to see the pattern of the diurnal, monthly, seasonal and yearly variation of VTEC values. The highest correlation was found between VTEC and F10.7 (r = 0.83). Totally, 40 major geomagnetic storms were identified that 45% of the storms are caused a decrease and 55% of the storms are caused an increase in VTEC variation. The maximum VTEC is shown at 13:00 LT and the minimum VTEC is shown at 03:00 LT according to diurnal variation of the 14-year mean 2-h VTEC. The maximum VTEC is shown on April and the minimum VTEC is shown on July according to diurnal variation of monthly mean VTEC. Diurnal variation of seasonal mean VTEC and its standard deviations are higher in equinox than solstices. Diurnal variation of yearly mean VTEC has a significant change from low to high solar activity periods.
35 schema:genre research_article
36 schema:inLanguage en
37 schema:isAccessibleForFree false
38 schema:isPartOf sg:journal.1136254
39 schema:name Ionospheric temporal variations over the region of Turkey: a study based on long-time TEC observations
40 schema:pagination 1-15
41 schema:productId N48530c3e237040668a5a172243944182
42 N749d946be5ac41c280af5a301e533ee2
43 N89156a81d1754b1cafcddf13ff922094
44 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106084755
45 https://doi.org/10.1007/s40328-018-0233-0
46 schema:sdDatePublished 2019-04-11T00:10
47 schema:sdLicense https://scigraph.springernature.com/explorer/license/
48 schema:sdPublisher N6465bc5ebc9541bc9be364319e4d9720
49 schema:url http://link.springer.com/10.1007/s40328-018-0233-0
50 sgo:license sg:explorer/license/
51 sgo:sdDataset articles
52 rdf:type schema:ScholarlyArticle
53 N0f43f51d80574b1cbe609f94fbcac4d6 rdf:first sg:person.015622263443.81
54 rdf:rest N7b1c3ac2e5c443a8afeae4ef69264d81
55 N48530c3e237040668a5a172243944182 schema:name readcube_id
56 schema:value aa3ad31b3d50df4eaa10192553e695d9dcdab08b4d96d13be5a0f8b101a2976c
57 rdf:type schema:PropertyValue
58 N6465bc5ebc9541bc9be364319e4d9720 schema:name Springer Nature - SN SciGraph project
59 rdf:type schema:Organization
60 N749d946be5ac41c280af5a301e533ee2 schema:name doi
61 schema:value 10.1007/s40328-018-0233-0
62 rdf:type schema:PropertyValue
63 N7b1c3ac2e5c443a8afeae4ef69264d81 rdf:first sg:person.01313575672.48
64 rdf:rest rdf:nil
65 N89156a81d1754b1cafcddf13ff922094 schema:name dimensions_id
66 schema:value pub.1106084755
67 rdf:type schema:PropertyValue
68 anzsrc-for:02 schema:inDefinedTermSet anzsrc-for:
69 schema:name Physical Sciences
70 rdf:type schema:DefinedTerm
71 anzsrc-for:0201 schema:inDefinedTermSet anzsrc-for:
72 schema:name Astronomical and Space Sciences
73 rdf:type schema:DefinedTerm
74 sg:journal.1136254 schema:issn 2213-5812
75 2213-5820
76 schema:name Acta Geodaetica et Geophysica
77 rdf:type schema:Periodical
78 sg:person.01313575672.48 schema:affiliation https://www.grid.ac/institutes/grid.411105.0
79 schema:familyName Çepni
80 schema:givenName Murat Selim
81 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01313575672.48
82 rdf:type schema:Person
83 sg:person.015622263443.81 schema:affiliation https://www.grid.ac/institutes/grid.411105.0
84 schema:familyName Şentürk
85 schema:givenName Erman
86 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015622263443.81
87 rdf:type schema:Person
88 sg:pub.10.1007/978-3-7091-5126-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048098428
89 https://doi.org/10.1007/978-3-7091-5126-6
90 rdf:type schema:CreativeWork
91 sg:pub.10.1007/s00190-017-1026-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1084926682
92 https://doi.org/10.1007/s00190-017-1026-x
93 rdf:type schema:CreativeWork
94 sg:pub.10.1007/s10509-011-0973-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044137843
95 https://doi.org/10.1007/s10509-011-0973-6
96 rdf:type schema:CreativeWork
97 sg:pub.10.1007/s10509-017-3043-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1084024959
98 https://doi.org/10.1007/s10509-017-3043-x
99 rdf:type schema:CreativeWork
100 https://app.dimensions.ai/details/publication/pub.1048098428 schema:CreativeWork
101 https://doi.org/10.1002/2014ja020552 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020695613
102 rdf:type schema:CreativeWork
103 https://doi.org/10.1002/2016ja023253 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000458838
104 rdf:type schema:CreativeWork
105 https://doi.org/10.1002/cjg2.903 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007816886
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1002/swe.20064 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037557995
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1016/0021-9169(69)90081-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018058820
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1016/0021-9169(69)90110-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1039489246
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1016/j.asr.2010.07.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017089662
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1016/j.asr.2012.12.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025525369
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1016/j.asr.2013.05.032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044484729
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1016/j.jastp.2003.09.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032757783
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1016/j.jastp.2005.02.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050655317
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1016/j.jastp.2006.08.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020279589
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/j.jastp.2016.10.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016037747
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/j.jastp.2017.02.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083884309
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1029/2000gl012551 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001569196
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1029/2005rs003327 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008384151
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1029/2006sw000281 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051310798
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1029/95ja03343 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015223274
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1029/jz064i003p00305 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002133024
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1371/journal.pone.0133378 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003620472
140 rdf:type schema:CreativeWork
141 https://doi.org/10.2514/4.866388 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099157035
142 rdf:type schema:CreativeWork
143 https://doi.org/10.5194/angeo-27-1047-2009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009282626
144 rdf:type schema:CreativeWork
145 https://doi.org/10.5194/isprsarchives-xl-1-w5-339-2015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025075856
146 rdf:type schema:CreativeWork
147 https://www.grid.ac/institutes/grid.411105.0 schema:alternateName University of Kocaeli
148 schema:name Department of Surveying Engineering, Kocaeli University, Kocaeli, Turkey
149 rdf:type schema:Organization
 




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


...