Application of a Geographic Information System to Analyze Traffic Accidents Using Nantou County, Taiwan, as an Example View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-01

AUTHORS

Jau-Ming Su, Yu-Ming Wang, Chih-hung Chang, Pei-Ju Wu

ABSTRACT

A geographic information system (GIS) is a commonly used method for analyzing traffic accidents. Through a GIS, data regarding traffic accidents can be presented visually, and traffic accident locations can be analyzed. By identifying locations where traffic accidents frequently occur and highway sections with high accident rates, traffic authorities can adopt preventive measures and enforce traffic regulations to reduce the frequency of traffic accidents, deaths, injuries, and financial losses. The present study analyzed tourist traffic accidents in Nantou County, one of the most popular tourist areas in Taiwan for domestic and international travelers, and tabulated statistical data that were subsequently input into a GIS database to determine dangerous locations and areas where traffic accidents are prone to occur. First, administrative regions in Nantou County were identified and kernel density estimation and repeatability analysis were performed to determine locations with high accident rates. The results showed that in Nantou County, traffic accidents often occur between 12:00 and 18:00 at intersections and on sloped roads and windy roads. The most dangerous locations were Provincial Highway 21 (areas around Sun Moon Lake) and Provincial Highway 14A (areas with access to Qingjing and Hehuanshan). The results of this study could serve as a reference for traffic authorities to develop measures for preventing and regulating traffic accidents. More... »

PAGES

1-11

References to SciGraph publications

  • 2016-06. Identification of Black Spots on Highway with Kernel Density Estimation Method in JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s12524-018-0874-z

    DOI

    http://dx.doi.org/10.1007/s12524-018-0874-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1107967632


    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/2008/0905", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Civil Engineering", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Engineering", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Feng Chia University", 
              "id": "https://www.grid.ac/institutes/grid.411298.7", 
              "name": [
                "Department of Transportation and Logistics, Feng Chia University, No. 100, Wenhwa Road, Seatwen, 40724, Taichung, Taiwan, ROC"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Su", 
            "givenName": "Jau-Ming", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Chung Hua University", 
              "id": "https://www.grid.ac/institutes/grid.411655.2", 
              "name": [
                "Ph.D. Program of Technology Management, Chung Hua University, No. 707, Sec. 2, Wu Fu Rd., 300, Hsin Chu, Taiwan, ROC"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wang", 
            "givenName": "Yu-Ming", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Feng Chia University", 
              "id": "https://www.grid.ac/institutes/grid.411298.7", 
              "name": [
                "Department of Transportation and Logistics, Feng Chia University, No. 100, Wenhwa Road, Seatwen, 40724, Taichung, Taiwan, ROC"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Chang", 
            "givenName": "Chih-hung", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Feng Chia University", 
              "id": "https://www.grid.ac/institutes/grid.411298.7", 
              "name": [
                "Department of Transportation and Logistics, Feng Chia University, No. 100, Wenhwa Road, Seatwen, 40724, Taichung, Taiwan, ROC"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wu", 
            "givenName": "Pei-Ju", 
            "id": "sg:person.013276547461.46", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013276547461.46"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.aap.2015.11.026", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008974464"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1117/12.671387", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012681738"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.aap.2006.02.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024646830"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12524-015-0500-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032768890", 
              "https://doi.org/10.1007/s12524-015-0500-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12524-015-0500-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032768890", 
              "https://doi.org/10.1007/s12524-015-0500-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.trf.2015.07.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033425545"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jtrangeo.2015.01.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034787042"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.aap.2007.05.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035968594"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jtte.2016.01.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038868586"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apacoust.2014.06.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044712477"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/13658810310001629619", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051522659"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.14569/ijacsa.2012.030606", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067338286"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5120/18109-8871", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1072600294"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-01", 
        "datePublishedReg": "2019-01-01", 
        "description": "A geographic information system (GIS) is a commonly used method for analyzing traffic accidents. Through a GIS, data regarding traffic accidents can be presented visually, and traffic accident locations can be analyzed. By identifying locations where traffic accidents frequently occur and highway sections with high accident rates, traffic authorities can adopt preventive measures and enforce traffic regulations to reduce the frequency of traffic accidents, deaths, injuries, and financial losses. The present study analyzed tourist traffic accidents in Nantou County, one of the most popular tourist areas in Taiwan for domestic and international travelers, and tabulated statistical data that were subsequently input into a GIS database to determine dangerous locations and areas where traffic accidents are prone to occur. First, administrative regions in Nantou County were identified and kernel density estimation and repeatability analysis were performed to determine locations with high accident rates. The results showed that in Nantou County, traffic accidents often occur between 12:00 and 18:00 at intersections and on sloped roads and windy roads. The most dangerous locations were Provincial Highway 21 (areas around Sun Moon Lake) and Provincial Highway 14A (areas with access to Qingjing and Hehuanshan). The results of this study could serve as a reference for traffic authorities to develop measures for preventing and regulating traffic accidents.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s12524-018-0874-z", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1136874", 
            "issn": [
              "0255-660X", 
              "0974-3006"
            ], 
            "name": "Journal of the Indian Society of Remote Sensing", 
            "type": "Periodical"
          }
        ], 
        "name": "Application of a Geographic Information System to Analyze Traffic Accidents Using Nantou County, Taiwan, as an Example", 
        "pagination": "1-11", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "8b47ca65208535eb642c60318e1372ffc5fc9e4a36d307f1daa541a0bf678865"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s12524-018-0874-z"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1107967632"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s12524-018-0874-z", 
          "https://app.dimensions.ai/details/publication/pub.1107967632"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T19:18", 
        "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_8678_00000575.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs12524-018-0874-z"
      }
    ]
     

    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/s12524-018-0874-z'

    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/s12524-018-0874-z'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12524-018-0874-z'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12524-018-0874-z'


     

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

    113 TRIPLES      21 PREDICATES      37 URIs      17 LITERALS      5 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s12524-018-0874-z schema:about anzsrc-for:09
    2 anzsrc-for:0905
    3 schema:author N7e5f8fc21b964729ba36cf2e77d99980
    4 schema:citation sg:pub.10.1007/s12524-015-0500-2
    5 https://doi.org/10.1016/j.aap.2006.02.012
    6 https://doi.org/10.1016/j.aap.2007.05.004
    7 https://doi.org/10.1016/j.aap.2015.11.026
    8 https://doi.org/10.1016/j.apacoust.2014.06.005
    9 https://doi.org/10.1016/j.jtrangeo.2015.01.007
    10 https://doi.org/10.1016/j.jtte.2016.01.005
    11 https://doi.org/10.1016/j.trf.2015.07.002
    12 https://doi.org/10.1080/13658810310001629619
    13 https://doi.org/10.1117/12.671387
    14 https://doi.org/10.14569/ijacsa.2012.030606
    15 https://doi.org/10.5120/18109-8871
    16 schema:datePublished 2019-01
    17 schema:datePublishedReg 2019-01-01
    18 schema:description A geographic information system (GIS) is a commonly used method for analyzing traffic accidents. Through a GIS, data regarding traffic accidents can be presented visually, and traffic accident locations can be analyzed. By identifying locations where traffic accidents frequently occur and highway sections with high accident rates, traffic authorities can adopt preventive measures and enforce traffic regulations to reduce the frequency of traffic accidents, deaths, injuries, and financial losses. The present study analyzed tourist traffic accidents in Nantou County, one of the most popular tourist areas in Taiwan for domestic and international travelers, and tabulated statistical data that were subsequently input into a GIS database to determine dangerous locations and areas where traffic accidents are prone to occur. First, administrative regions in Nantou County were identified and kernel density estimation and repeatability analysis were performed to determine locations with high accident rates. The results showed that in Nantou County, traffic accidents often occur between 12:00 and 18:00 at intersections and on sloped roads and windy roads. The most dangerous locations were Provincial Highway 21 (areas around Sun Moon Lake) and Provincial Highway 14A (areas with access to Qingjing and Hehuanshan). The results of this study could serve as a reference for traffic authorities to develop measures for preventing and regulating traffic accidents.
    19 schema:genre research_article
    20 schema:inLanguage en
    21 schema:isAccessibleForFree false
    22 schema:isPartOf sg:journal.1136874
    23 schema:name Application of a Geographic Information System to Analyze Traffic Accidents Using Nantou County, Taiwan, as an Example
    24 schema:pagination 1-11
    25 schema:productId N015ec63f0d464ab085cc5a3805d4d657
    26 N2be9b9f0e7ba413dac0c681e1f8f9699
    27 N3eff0cfe0c5e48479331c50ab8128461
    28 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107967632
    29 https://doi.org/10.1007/s12524-018-0874-z
    30 schema:sdDatePublished 2019-04-10T19:18
    31 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    32 schema:sdPublisher N4adb6067f187413bad58a831e6b453ca
    33 schema:url https://link.springer.com/10.1007%2Fs12524-018-0874-z
    34 sgo:license sg:explorer/license/
    35 sgo:sdDataset articles
    36 rdf:type schema:ScholarlyArticle
    37 N015ec63f0d464ab085cc5a3805d4d657 schema:name readcube_id
    38 schema:value 8b47ca65208535eb642c60318e1372ffc5fc9e4a36d307f1daa541a0bf678865
    39 rdf:type schema:PropertyValue
    40 N28b88544560e4033a766e19cbaad75f2 schema:affiliation https://www.grid.ac/institutes/grid.411298.7
    41 schema:familyName Su
    42 schema:givenName Jau-Ming
    43 rdf:type schema:Person
    44 N2be9b9f0e7ba413dac0c681e1f8f9699 schema:name dimensions_id
    45 schema:value pub.1107967632
    46 rdf:type schema:PropertyValue
    47 N2f944341598443d1ac0d3f06a4d291fb rdf:first sg:person.013276547461.46
    48 rdf:rest rdf:nil
    49 N3e96c4f5cdc04bb687550970ff7f0692 schema:affiliation https://www.grid.ac/institutes/grid.411298.7
    50 schema:familyName Chang
    51 schema:givenName Chih-hung
    52 rdf:type schema:Person
    53 N3eff0cfe0c5e48479331c50ab8128461 schema:name doi
    54 schema:value 10.1007/s12524-018-0874-z
    55 rdf:type schema:PropertyValue
    56 N4adb6067f187413bad58a831e6b453ca schema:name Springer Nature - SN SciGraph project
    57 rdf:type schema:Organization
    58 N7e5f8fc21b964729ba36cf2e77d99980 rdf:first N28b88544560e4033a766e19cbaad75f2
    59 rdf:rest Nf90dd4e8f18740f09f678327646ad282
    60 N855e2ef1d9584ba88f505cbbe9cfa58d schema:affiliation https://www.grid.ac/institutes/grid.411655.2
    61 schema:familyName Wang
    62 schema:givenName Yu-Ming
    63 rdf:type schema:Person
    64 Ncc80b1475f674e39b6b6fe65e2e55868 rdf:first N3e96c4f5cdc04bb687550970ff7f0692
    65 rdf:rest N2f944341598443d1ac0d3f06a4d291fb
    66 Nf90dd4e8f18740f09f678327646ad282 rdf:first N855e2ef1d9584ba88f505cbbe9cfa58d
    67 rdf:rest Ncc80b1475f674e39b6b6fe65e2e55868
    68 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
    69 schema:name Engineering
    70 rdf:type schema:DefinedTerm
    71 anzsrc-for:0905 schema:inDefinedTermSet anzsrc-for:
    72 schema:name Civil Engineering
    73 rdf:type schema:DefinedTerm
    74 sg:journal.1136874 schema:issn 0255-660X
    75 0974-3006
    76 schema:name Journal of the Indian Society of Remote Sensing
    77 rdf:type schema:Periodical
    78 sg:person.013276547461.46 schema:affiliation https://www.grid.ac/institutes/grid.411298.7
    79 schema:familyName Wu
    80 schema:givenName Pei-Ju
    81 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013276547461.46
    82 rdf:type schema:Person
    83 sg:pub.10.1007/s12524-015-0500-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032768890
    84 https://doi.org/10.1007/s12524-015-0500-2
    85 rdf:type schema:CreativeWork
    86 https://doi.org/10.1016/j.aap.2006.02.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024646830
    87 rdf:type schema:CreativeWork
    88 https://doi.org/10.1016/j.aap.2007.05.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035968594
    89 rdf:type schema:CreativeWork
    90 https://doi.org/10.1016/j.aap.2015.11.026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008974464
    91 rdf:type schema:CreativeWork
    92 https://doi.org/10.1016/j.apacoust.2014.06.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044712477
    93 rdf:type schema:CreativeWork
    94 https://doi.org/10.1016/j.jtrangeo.2015.01.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034787042
    95 rdf:type schema:CreativeWork
    96 https://doi.org/10.1016/j.jtte.2016.01.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038868586
    97 rdf:type schema:CreativeWork
    98 https://doi.org/10.1016/j.trf.2015.07.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033425545
    99 rdf:type schema:CreativeWork
    100 https://doi.org/10.1080/13658810310001629619 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051522659
    101 rdf:type schema:CreativeWork
    102 https://doi.org/10.1117/12.671387 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012681738
    103 rdf:type schema:CreativeWork
    104 https://doi.org/10.14569/ijacsa.2012.030606 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067338286
    105 rdf:type schema:CreativeWork
    106 https://doi.org/10.5120/18109-8871 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072600294
    107 rdf:type schema:CreativeWork
    108 https://www.grid.ac/institutes/grid.411298.7 schema:alternateName Feng Chia University
    109 schema:name Department of Transportation and Logistics, Feng Chia University, No. 100, Wenhwa Road, Seatwen, 40724, Taichung, Taiwan, ROC
    110 rdf:type schema:Organization
    111 https://www.grid.ac/institutes/grid.411655.2 schema:alternateName Chung Hua University
    112 schema:name Ph.D. Program of Technology Management, Chung Hua University, No. 707, Sec. 2, Wu Fu Rd., 300, Hsin Chu, Taiwan, ROC
    113 rdf:type schema:Organization
     




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


    ...