IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v70y2014i3p1735-1748.html
   My bibliography  Save this article

Study on spatial prediction and time forecast of landslide

Author

Listed:
  • Gao Hua-xi
  • Yin Kun-long

Abstract

Landslide is one of natural hazards in mountainous regions, which has resulted in a large quantity of casualties and property losses and also has absorbed high attention of the researchers and government. A considerable amount of research has been carried out in the past 30 years in the landslide field. In this paper, the contribution and existing problems on landslide are analyzed and summarized in the previous studies. Spatial prediction and zonation of the regional landslide are developed by using information content model that is a new method, with the example of landslide in Xincheng District of Badong County. On the other hand, by learning from the forecast theories and methods of earthquake forecast, probability of excess for landslide that will take place in the studied area is calculated quantitatively in next 5 and 10 years. All the calculated results are mainly accordant with the regional fact. Therefore, it may provide scientific data for landslide prevention and reduction as well as landslide management. Based on the achievement obtained in this study, it was found that 29.11% of the total area was prone to landslide due to the adverse effects of topography, reservoir water in the leading edge of bank, and improper land use. At the same time, the theory of spatial prediction and probability of excess will be example and reference for the other region of China or the world. Copyright Springer Science+Business Media B.V. 2014

Suggested Citation

  • Gao Hua-xi & Yin Kun-long, 2014. "Study on spatial prediction and time forecast of landslide," 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. 70(3), pages 1735-1748, February.
  • Handle: RePEc:spr:nathaz:v:70:y:2014:i:3:p:1735-1748
    DOI: 10.1007/s11069-011-9756-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-011-9756-1
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11069-011-9756-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yang Hong & Robert Adler & George Huffman, 2007. "Use of satellite remote sensing data in the mapping of global landslide susceptibility," 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. 43(2), pages 245-256, November.
    2. C. van Westen & N. Rengers & R. Soeters, 2003. "Use of Geomorphological Information in Indirect Landslide Susceptibility Assessment," 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. 30(3), pages 399-419, November.
    3. Jordi Corominas & Ramon Copons & Joan Vilaplana & Joan Altimir & Jordi Amigó, 2003. "Integrated Landslide Susceptibility Analysis and Hazard Assessment in the Principality of Andorra," 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. 30(3), pages 421-435, November.
    4. Zhaohua Chen & Jinfei Wang, 2007. "Landslide hazard mapping using logistic regression model in Mackenzie Valley, Canada," 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. 42(1), pages 75-89, July.
    Full references (including those not matched with items on IDEAS)

    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. Chong Xu & Xiwei Xu & Fuchu Dai & Zhide Wu & Honglin He & Feng Shi & Xiyan Wu & Suning Xu, 2013. "Application of an incomplete landslide inventory, logistic regression model and its validation for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China," 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. 68(2), pages 883-900, September.
    2. Paolo Magliulo & Antonio Di Lisio & Filippo Russo & Antonio Zelano, 2008. "Geomorphology and landslide susceptibility assessment using GIS and bivariate statistics: a case study in southern Italy," 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. 47(3), pages 411-435, December.
    3. Netra Bhandary & Ranjan Dahal & Manita Timilsina & Ryuichi Yatabe, 2013. "Rainfall event-based landslide susceptibility zonation mapping," 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. 69(1), pages 365-388, October.
    4. Yumiao Wang & Xueling Wu & Zhangjian Chen & Fu Ren & Luwei Feng & Qingyun Du, 2019. "Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China," IJERPH, MDPI, vol. 16(3), pages 1-27, January.
    5. Hone-Jay Chu & Yi-Chin Chen, 2018. "Crowdsourcing photograph locations for debris flow hot spot mapping," 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 1259-1276, February.
    6. Hyo-sub Kang & Yun-tae Kim, 2016. "The physical vulnerability of different types of building structure to debris flow events," 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. 80(3), pages 1475-1493, February.
    7. Di Wang & Mengmeng Hao & Shuai Chen & Ze Meng & Dong Jiang & Fangyu Ding, 2021. "Assessment of landslide susceptibility and risk factors in China," 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. 108(3), pages 3045-3059, September.
    8. Thomas Stanley & Dalia B. Kirschbaum, 2017. "A heuristic approach to global landslide susceptibility mapping," 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. 87(1), pages 145-164, May.
    9. George Gaprindashvili & Cees Westen, 2016. "Generation of a national landslide hazard and risk map for the country of Georgia," 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. 80(1), pages 69-101, January.
    10. Jeevan R. Kulkarni & Sneha S. Kulkarni & Mitali U. Inamdar & Nitin M. Tamhankar & Spandan B. Waghmare & Kiran R. Thombare & Paresh S. Mhetre & Tanuja Khatavkar & Yashodhan Panse & Amey Patwardhan & Yo, 2022. "“Satark”: Landslide Prediction System over Western Ghats of India," Land, MDPI, vol. 11(5), pages 1-23, May.
    11. Paúl Carrión-Mero & Néstor Montalván-Burbano & Fernando Morante-Carballo & Adolfo Quesada-Román & Boris Apolo-Masache, 2021. "Worldwide Research Trends in Landslide Science," IJERPH, MDPI, vol. 18(18), pages 1-24, September.
    12. Raquel Melo & José Luís Zêzere, 2017. "Modeling debris flow initiation and run-out in recently burned areas using data-driven methods," 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. 88(3), pages 1373-1407, September.
    13. Zonghu Liao & Yang Hong & Dalia Kirschbaum & Robert Adler & Jonathan Gourley & Rick Wooten, 2011. "Evaluation of TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis)’s predictive skill for hurricane-triggered landslides: a case study in Macon County, North Carol," 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. 58(1), pages 325-339, July.
    14. K. Sajinkumar & S. Anbazhagan, 2015. "Geomorphic appraisal of landslides on the windward slope of Western Ghats, southern India," 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. 75(1), pages 953-973, January.
    15. Danang Hadmoko & Franck Lavigne & Junun Sartohadi & Pramono Hadi & Winaryo, 2010. "Landslide hazard and risk assessment and their application in risk management and landuse planning in eastern flank of Menoreh Mountains, Yogyakarta Province, Indonesia," 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. 54(3), pages 623-642, September.
    16. Paul Sestraș & Ștefan Bilașco & Sanda Roșca & Sanda Naș & Mircea V. Bondrea & Raluca Gâlgău & Ioel Vereș & Tudor Sălăgean & Velibor Spalević & Sorin M. Cîmpeanu, 2019. "Landslides Susceptibility Assessment Based on GIS Statistical Bivariate Analysis in the Hills Surrounding a Metropolitan Area," Sustainability, MDPI, vol. 11(5), pages 1-23, March.
    17. Khabat Khosravi & Ebrahim Nohani & Edris Maroufinia & Hamid Reza Pourghasemi, 2016. "A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with multi-criteria decision-making techn," 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. 83(2), pages 947-987, September.
    18. Paola Gattinoni, 2009. "Parametrical landslide modeling for the hydrogeological susceptibility assessment: from the Crati Valley to the Cavallerizzo landslide (Southern Italy)," 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. 50(1), pages 161-178, July.
    19. Ziyue Zeng & Guoqiang Tang & Di Long & Chao Zeng & Meihong Ma & Yang Hong & Hui Xu & Jing Xu, 2016. "A cascading flash flood guidance system: development and application in Yunnan Province, China," 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(3), pages 2071-2093, December.
    20. Haoyuan Hong & Himan Shahabi & Ataollah Shirzadi & Wei Chen & Kamran Chapi & Baharin Bin Ahmad & Majid Shadman Roodposhti & Arastoo Yari Hesar & Yingying Tian & Dieu Tien Bui, 2019. "Landslide susceptibility assessment at the Wuning area, China: a comparison between multi-criteria decision making, bivariate statistical and machine learning methods," 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. 96(1), pages 173-212, 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:spr:nathaz:v:70:y:2014:i:3:p:1735-1748. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.