IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i4p534-d94661.html
   My bibliography  Save this article

A Geo-Event-Based Geospatial Information Service: A Case Study of Typhoon Hazard

Author

Listed:
  • Yu Zhang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    School of Geography, Beijing Normal University, Beijing 100875, China)

  • Wenzhou Wu

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Qi Wang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    School of Geography, Beijing Normal University, Beijing 100875, China)

  • Fenzhen Su

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

Abstract

Social media is valuable in propagating information during disasters for its timely and available characteristics nowadays, and assists in making decisions when tagged with locations. Considering the ambiguity and inaccuracy in some social data, additional authoritative data are needed for important verification. However, current works often fail to leverage both social and authoritative data and, on most occasions, the data are used in disaster analysis after the fact. Moreover, current works organize the data from the perspective of the spatial location, but not from the perspective of the disaster, making it difficult to dynamically analyze the disaster. All of the disaster-related data around the affected locations need to be retrieved. To solve these limitations, this study develops a geo-event-based geospatial information service (GEGIS) framework and proceeded as follows: (1) a geo-event-related ontology was constructed to provide a uniform semantic basis for the system; (2) geo-events and attributes were extracted from the web using a natural language process (NLP) and used in the semantic similarity match of the geospatial resources; and (3) a geospatial information service prototype system was designed and implemented for automatically retrieving and organizing geo-event-related geospatial resources. A case study of a typhoon hazard is analyzed here within the GEGIS and shows that the system would be effective when typhoons occur.

Suggested Citation

  • Yu Zhang & Wenzhou Wu & Qi Wang & Fenzhen Su, 2017. "A Geo-Event-Based Geospatial Information Service: A Case Study of Typhoon Hazard," Sustainability, MDPI, vol. 9(4), pages 1-18, March.
  • Handle: RePEc:gam:jsusta:v:9:y:2017:i:4:p:534-:d:94661
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/4/534/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/9/4/534/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Qing Deng & Yi Liu & Hui Zhang & Xiaolong Deng & Yefeng Ma, 2016. "A new crowdsourcing model to assess disaster using microblog data in typhoon Haiyan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(2), pages 1241-1256, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sung Hee Jang & Chang Won Lee, 2018. "The Impact of Location-Based Service Factors on Usage Intentions for Technology Acceptance: The Moderating Effect of Innovativeness," Sustainability, MDPI, vol. 10(6), pages 1-18, June.
    2. Peng Ye & Xueying Zhang & Ge Shi & Shuhui Chen & Zhiwen Huang & Wei Tang, 2020. "TKRM: A Formal Knowledge Representation Method for Typhoon Events," Sustainability, MDPI, vol. 12(5), pages 1-19, March.
    3. Sajjad Ahadzadeh & Mohammad Reza Malek, 2021. "Earthquake Damage Assessment Based on User Generated Data in Social Networks," Sustainability, MDPI, vol. 13(9), pages 1-19, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiaobing Yu & Hong Chen & Chenliang Li, 2019. "Evaluate Typhoon Disasters in 21st Century Maritime Silk Road by Super-Efficiency DEA," IJERPH, MDPI, vol. 16(9), pages 1-10, May.
    2. Turgut Acikara & Bo Xia & Tan Yigitcanlar & Carol Hon, 2023. "Contribution of Social Media Analytics to Disaster Response Effectiveness: A Systematic Review of the Literature," Sustainability, MDPI, vol. 15(11), pages 1-50, May.
    3. Mingjun Ma & Qiang Gao & Zishuang Xiao & Xingshuai Hou & Beibei Hu & Lifei Jia & Wenfang Song, 2023. "Analysis of public emotion on flood disasters in southern China in 2020 based on social media data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(2), pages 1013-1033, September.
    4. Hamed Farahmand & Wanqiu Wang & Ali Mostafavi & Mikel Maron, 2022. "Anomalous human activity fluctuations from digital trace data signal flood inundation status," Environment and Planning B, , vol. 49(7), pages 1893-1911, September.
    5. Faxi Yuan & Rui Liu, 2018. "Crowdsourcing for forensic disaster investigations: Hurricane Harvey case study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(3), pages 1529-1546, September.
    6. Xiaorong He, 2018. "Typhoon disaster assessment based on Dombi hesitant fuzzy information aggregation operators," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 90(3), pages 1153-1175, February.
    7. Lida Huang & Panpan Shi & Haichao Zhu & Tao Chen, 2022. "Early detection of emergency events from social media: a new text clustering approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(1), pages 851-875, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:9:y:2017:i:4:p:534-:d:94661. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.