IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v86y2017i2d10.1007_s11069-016-2725-y.html
   My bibliography  Save this article

Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

Author

Listed:
  • Kamila Pawluszek

    (Wroclaw University of Environmental and Life Sciences)

  • Andrzej Borkowski

    (Wroclaw University of Environmental and Life Sciences)

Abstract

Choosing appropriate landslide-controlling factors (LCFs) in landslide susceptibility mapping (LSM) is a challenging task and depends on the nature of terrain and expert knowledge and experience. Nowadays, it is very common to use digital elevation model (DEM) and DEM-derivatives, as a representation of the topographic conditions. The objective of this study is to explore topography in depth and simultaneously reduce redundant information within DEM-derivatives using principal component analysis. Moreover, this study investigates the impact of DEM-derived factors on LSM. Therefore, three various strategies were tested. The first strategy included a set of LCFs created from the four initial principal components, which were provided from DEM-derived factors. The second strategy included a set of parameters which contained additional lithological and environmental factors. The third strategy utilises the analytical hierarchy process (AHP) to assign weights to each LCF. The LSM was performed based on landslide susceptibility index. Obtained results show that 60% of existing landslides fell into high and very high susceptibility zones using first and second strategies. It proves that topographic factors play a significant role in LSM. Adding additional lithological and environmental factors to the set of LCFs did not improve the results significantly, unless the AHP was used in the third strategy. It improved results significantly; up to 70%. Results from second and third strategies highlight utility of AHP in LSM. Presented studies were performed on the area very prone to landslide occurrence in the region of Rożnów Lake, Poland.

Suggested Citation

  • Kamila Pawluszek & Andrzej Borkowski, 2017. "Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland," 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. 86(2), pages 919-952, March.
  • Handle: RePEc:spr:nathaz:v:86:y:2017:i:2:d:10.1007_s11069-016-2725-y
    DOI: 10.1007/s11069-016-2725-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-016-2725-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11069-016-2725-y?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. Dieu Bui & Owe Lofman & Inge Revhaug & Oystein Dick, 2011. "Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression," 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. 59(3), pages 1413-1444, December.
    2. Juan Remondo & Alberto González & José De Terán & Antonio Cendrero & Andrea Fabbri & Chang-Jo Chung, 2003. "Validation of Landslide Susceptibility Maps; Examples and Applications from a Case Study in Northern Spain," 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 437-449, 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. Richard Mind’je & Lanhai Li & Jean Baptiste Nsengiyumva & Christophe Mupenzi & Enan Muhire Nyesheja & Patient Mindje Kayumba & Aboubakar Gasirabo & Egide Hakorimana, 2020. "Landslide susceptibility and influencing factors analysis in Rwanda," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(8), pages 7985-8012, December.
    2. Rongwei Li & Shucheng Tan & Mingfei Zhang & Shaohan Zhang & Haishan Wang & Lei Zhu, 2024. "Geological Disaster Susceptibility Evaluation Using a Random Forest Empowerment Information Quantity Model," Sustainability, MDPI, vol. 16(2), pages 1-18, January.
    3. Katarzyna A. Kurek & Wim Heijman & Johan Ophem & Stanisław Gędek & Jacek Strojny, 2022. "Measuring local competitiveness: comparing and integrating two methods PCA and AHP," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1371-1389, June.

    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. E. Rotigliano & C. Cappadonia & C. Conoscenti & D. Costanzo & V. Agnesi, 2012. "Slope units-based flow susceptibility model: using validation tests to select controlling factors," 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. 61(1), pages 143-153, March.
    2. Nisar Ali Shah & Muhammad Shafique & Muhammad Ishfaq & Kamil Faisal & Mark Van der Meijde, 2023. "Integrated Approach for Landslide Risk Assessment Using Geoinformation Tools and Field Data in Hindukush Mountain Ranges, Northern Pakistan," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    3. Xiaoqing Zhao & Junwei Pu & Xingyou Wang & Junxu Chen & Liang Emlyn Yang & Zexian Gu, 2018. "Land-Use Spatio-Temporal Change and Its Driving Factors in an Artificial Forest Area in Southwest China," Sustainability, MDPI, vol. 10(11), pages 1-19, November.
    4. 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.
    5. C. Irigaray & T. Fernández & R. El Hamdouni & J. Chacón, 2007. "Evaluation and validation of landslide-susceptibility maps obtained by a GIS matrix method: examples from the Betic Cordillera (southern Spain)," 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. 41(1), pages 61-79, April.
    6. Moung-Jin Lee & Wonkyong Song & Saro Lee, 2015. "Habitat Mapping of the Leopard Cat ( Prionailurus bengalensis ) in South Korea Using GIS," Sustainability, MDPI, vol. 7(4), pages 1-21, April.
    7. L. Lombardo & M. Cama & C. Conoscenti & M. Märker & E. Rotigliano, 2015. "Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messi," 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. 79(3), pages 1621-1648, December.
    8. 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.
    9. Omid Rahmati & Ali Haghizadeh & Hamid Reza Pourghasemi & Farhad Noormohamadi, 2016. "Gully erosion susceptibility mapping: the role of GIS-based bivariate statistical models and their comparison," 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. 82(2), pages 1231-1258, June.
    10. Amin Hosseinpoor Milaghardan & Rahim Ali Abbaspour & Mina Khalesian, 2020. "Evaluation of the effects of uncertainty on the predictions of landslide occurrences using the Shannon entropy theory and Dempster–Shafer theory," 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. 100(1), pages 49-67, January.
    11. Christos Polykretis & Christos Chalkias, 2018. "Comparison and evaluation of landslide susceptibility maps obtained from weight of evidence, logistic regression, and artificial neural network models," 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(1), pages 249-274, August.
    12. E. Rotigliano & V. Agnesi & C. Cappadonia & C. Conoscenti, 2011. "The role of the diagnostic areas in the assessment of landslide susceptibility models: a test in the sicilian chain," 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(3), pages 981-999, September.
    13. Chonghao Zhu & Jianjing Zhang & Yang Liu & Donghua Ma & Mengfang Li & Bo Xiang, 2020. "Comparison of GA-BP and PSO-BP neural network models with initial BP model for rainfall-induced landslides risk assessment in regional scale: a case study in Sichuan, 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. 100(1), pages 173-204, January.
    14. Chen Cao & Peihua Xu & Yihong Wang & Jianping Chen & Lianjing Zheng & Cencen Niu, 2016. "Flash Flood Hazard Susceptibility Mapping Using Frequency Ratio and Statistical Index Methods in Coalmine Subsidence Areas," Sustainability, MDPI, vol. 8(9), pages 1-18, September.
    15. Jaime Bonachea & Juan Remondo & José Ramón Díaz De Terán & Alberto González‐Díez & Antonio Cendrero, 2009. "Landslide Risk Models for Decision Making," Risk Analysis, John Wiley & Sons, vol. 29(11), pages 1629-1643, November.
    16. Anna Małka, 2021. "Landslide susceptibility mapping of Gdynia using geographic information system-based statistical models," 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. 107(1), pages 639-674, May.
    17. Helen Cristina Dias & Marcelo Fischer Gramani & Carlos Henrique Grohmann & Carlos Bateira & Bianca Carvalho Vieira, 2021. "Statistical-based shallow landslide susceptibility assessment for a tropical environment: a case study in the southeastern Brazilian coast," 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(1), pages 205-223, August.
    18. Abazar Esmali Ouri & Mohammad Golshan & Saeid Janizadeh & Artemi Cerdà & Assefa M. Melesse, 2020. "Soil Erosion Susceptibility Mapping in Kozetopraghi Catchment, Iran: A Mixed Approach Using Rainfall Simulator and Data Mining Techniques," Land, MDPI, vol. 9(10), pages 1-18, October.
    19. Michele Marconi & Beatrice Gatto & Michele Magni & Fausto Marincioni, 2016. "A rapid method for flood susceptibility mapping in two districts of Phatthalung Province (Thailand): present and projected conditions for 2050," 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. 81(1), pages 329-346, March.
    20. Keisuke Ono & So Kazama & Chaiwat Ekkawatpanit, 2014. "Assessment of rainfall-induced shallow landslides in Phetchabun and Krabi provinces, Thailand," 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. 74(3), pages 2089-2107, December.

    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:86:y:2017:i:2:d:10.1007_s11069-016-2725-y. 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.