IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v84y2016i1d10.1007_s11069-016-2443-5.html
   My bibliography  Save this article

Presence-only approach to assess landslide triggering-thickness susceptibility: a test for the Mili catchment (north-eastern Sicily, Italy)

Author

Listed:
  • L. Lombardo

    (King Abdullah University of Science and Technology
    University of Tübingen)

  • G. Fubelli

    (University of Torino)

  • G. Amato

    (Roma Tre University)

  • M. Bonasera

    (Roma Tre University)

Abstract

This study evaluates the performances of the presence-only approach, Maximum Entropy, in assessing landslide triggering-thickness susceptibility within the Mili catchment (Sicily, Italy). This catchment underwent several meteorological stresses, resulting in hundreds of shallow rapid mass movements between 2007 and 2011. In particular, the area has become known for two disasters, which occurred in 2009 and 2010; the first weather system did not pass directly over the catchment; however, peak rainfall was registered over the basin during the second meteorological event. Field data were collected to associate the depth from the slope surface that material was mobilised at the triggering zone to each mass movement within the catchment. This information has been used to model the landslide susceptibility for two classes of processes, divided into shallow failures for maximum depths of 1 m and deep ones in case of values equal or greater than 1 m. Topographic attributes from a 2-m DEM were used as predictors, together with medium resolution vegetation indexes derived from ASTER scenes and geological, land use and tectonic maps. The presence-only approach discriminated between the two depth classes at the landslide trigger zone, producing excellent prediction skills associated with relatively low variances across a set of 50 randomly generated replicates. The role of each predictor was assessed to ascertain the significance to the final model output. This work uses simple field measurements to produce triggering-thickness susceptibility, which is a novel approach and may perform better as a proxy for landslide hazard assessments with respect to more common susceptibility practises.

Suggested Citation

  • L. Lombardo & G. Fubelli & G. Amato & M. Bonasera, 2016. "Presence-only approach to assess landslide triggering-thickness susceptibility: a test for the Mili catchment (north-eastern Sicily, 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. 84(1), pages 565-588, October.
  • Handle: RePEc:spr:nathaz:v:84:y:2016:i:1:d:10.1007_s11069-016-2443-5
    DOI: 10.1007/s11069-016-2443-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-016-2443-5
    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/s11069-016-2443-5?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. 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.
    2. 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.
    3. V. Comerci & E. Vittori & A. Blumetti & E. Brustia & P. Manna & L. Guerrieri & M. Lucarini & L. Serva, 2015. "Environmental effects of the December 28, 1908, Southern Calabria–Messina (Southern Italy) earthquake," 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. 76(3), pages 1849-1891, April.
    4. Hamid Pourghasemi & Biswajeet Pradhan & Candan Gokceoglu, 2012. "Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran," 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. 63(2), pages 965-996, September.
    5. Giulio Iovine & Roberto Greco & Stefano Gariano & Annamaria Pellegrino & Oreste Terranova, 2014. "Shallow-landslide susceptibility in the Costa Viola mountain ridge (southern Calabria, Italy) with considerations on the role of causal 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. 73(1), pages 111-136, August.
    6. Taskin Kavzoglu & Emrehan Kutlug Sahin & Ismail Colkesen, 2015. "An assessment of multivariate and bivariate approaches in landslide susceptibility mapping: a case study of Duzkoy district," 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. 76(1), pages 471-496, March.
    7. Shcheglovitova, Mariya & Anderson, Robert P., 2013. "Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes," Ecological Modelling, Elsevier, vol. 269(C), pages 9-17.
    8. Oke, Oluwatobi A. & Thompson, Ken A., 2015. "Distribution models for mountain plant species: The value of elevation," Ecological Modelling, Elsevier, vol. 301(C), pages 72-77.
    9. Bayes Ahmed, 2015. "Landslide susceptibility modelling applying user-defined weighting and data-driven statistical techniques in Cox’s Bazar Municipality, Bangladesh," 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 1707-1737, December.
    10. Cheng Su & Lili Wang & Xizhi Wang & Zhicai Huang & Xiaocan Zhang, 2015. "Mapping of rainfall-induced landslide susceptibility in Wencheng, China, using support vector machine," 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. 76(3), pages 1759-1779, April.
    11. L. Lombardo & M. Cama & M. Maerker & E. Rotigliano, 2014. "A test of transferability for landslides susceptibility models under extreme climatic events: application to the Messina 2009 disaster," 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 1951-1989, December.
    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. Omid Asadi Nalivan & Ziaedin Badehian & Majid Sadeghinia & Adel Soltani & Iman Islami & Ali Boustan, 2022. "A step beyond susceptibility: an adaptation of risk framework for monetary risk estimation of gully erosion," 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(2), pages 1661-1684, March.
    2. Laurie Jayne Kurilla & Giandomenico Fubelli, 2022. "Global debris flow susceptibility based on a comparative analysis of a single global model versus a continent-by-continent 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. 113(1), pages 527-546, August.
    3. Majid Mohammady & Hamid Reza Pourghasemi & Mojtaba Amiri, 2019. "Assessment of land subsidence susceptibility in Semnan plain (Iran): a comparison of support vector machine and weights of evidence data mining algorithms," 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. 99(2), pages 951-971, November.
    4. Zhuo Chen & Fei Ye & Wenxi Fu & Yutian Ke & Haoyuan Hong, 2020. "The influence of DEM spatial resolution on landslide susceptibility mapping in the Baxie River basin, NW 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. 101(3), pages 853-877, April.
    5. Ali Azedou & Said Lahssini & Abdellatif Khattabi & Modeste Meliho & Nabil Rifai, 2021. "A Methodological Comparison of Three Models for Gully Erosion Susceptibility Mapping in the Rural Municipality of El Faid (Morocco)," Sustainability, MDPI, vol. 13(2), pages 1-30, January.

    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. 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.
    2. Viet-Ha Nhu & Ataollah Shirzadi & Himan Shahabi & Sushant K. Singh & Nadhir Al-Ansari & John J. Clague & Abolfazl Jaafari & Wei Chen & Shaghayegh Miraki & Jie Dou & Chinh Luu & Krzysztof Górski & Binh, 2020. "Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms," IJERPH, MDPI, vol. 17(8), pages 1-30, April.
    3. 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.
    4. 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.
    5. Maria Karpouza & Konstantinos Chousianitis & George D. Bathrellos & Hariklia D. Skilodimou & George Kaviris & Assimina Antonarakou, 2021. "Hazard zonation mapping of earthquake-induced secondary effects using spatial multi-criteria analysis," 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. 109(1), pages 637-669, October.
    6. Rahim Tavakolifar & Himan Shahabi & Mohsen Alizadeh & Sayed M. Bateni & Mazlan Hashim & Ataollah Shirzadi & Effi Helmy Ariffin & Isabelle D. Wolf & Saman Shojae Chaeikar, 2023. "Spatial Prediction of Landslides Using Hybrid Multi-Criteria Decision-Making Methods: A Case Study of the Saqqez-Marivan Mountain Road in Iran," Land, MDPI, vol. 12(6), pages 1-19, May.
    7. Txomin Bornaetxea & Juan Remondo & Jaime Bonachea & Pablo Valenzuela, 2023. "Exploring available landslide inventories for susceptibility analysis in Gipuzkoa province (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. 118(3), pages 2513-2542, September.
    8. Gökhan Demir & Mustafa Aytekin & Aykut Akgün & Sabriye İkizler & Orhan Tatar, 2013. "A comparison of landslide susceptibility mapping of the eastern part of the North Anatolian Fault Zone (Turkey) by likelihood-frequency ratio and analytic hierarchy process 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. 65(3), pages 1481-1506, February.
    9. Rui Yuan & Jing Chen, 2022. "A hybrid deep learning method for landslide susceptibility analysis with the application of InSAR 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. 114(2), pages 1393-1426, November.
    10. Kourosh Shirani & Mehrdad Pasandi & Alireza Arabameri, 2018. "Landslide susceptibility assessment by Dempster–Shafer and Index of Entropy models, Sarkhoun basin, Southwestern Iran," 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 1379-1418, September.
    11. Al-Amin Abba Dabo & Amin Hosseinian-Far, 2023. "An Integrated Methodology for Enhancing Reverse Logistics Flows and Networks in Industry 5.0," Logistics, MDPI, vol. 7(4), pages 1-26, December.
    12. Sadhan Malik & Subodh Chandra Pal & Biswajit Das & Rabin Chakrabortty, 2020. "Assessment of vegetation status of Sali River basin, a tributary of Damodar River in Bankura District, West Bengal, using satellite data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5651-5685, August.
    13. Kibeom Kwon & Minkyu Kang & Dongku Kim & Hangseok Choi, 2023. "Prioritization of Hazardous Zones Using an Advanced Risk Management Model Combining the Analytic Hierarchy Process and Fuzzy Set Theory," Sustainability, MDPI, vol. 15(15), pages 1-15, August.
    14. Wenqun Xiu & Shuying Wang & Wenguang Qi & Xue Li & Chisheng Wang, 2021. "Disaster Chain Analysis of Landfill Landslide: Scenario Simulation and Chain-Cutting Modeling," Sustainability, MDPI, vol. 13(9), pages 1-22, April.
    15. Rajesh Khatakho & Dipendra Gautam & Komal Raj Aryal & Vishnu Prasad Pandey & Rajesh Rupakhety & Suraj Lamichhane & Yi-Chung Liu & Khameis Abdouli & Rocky Talchabhadel & Bhesh Raj Thapa & Rabindra Adhi, 2021. "Multi-Hazard Risk Assessment of Kathmandu Valley, Nepal," Sustainability, MDPI, vol. 13(10), pages 1-27, May.
    16. H. Oğuz Çoban & Ömer K. Örücü & E. Seda Arslan, 2020. "MaxEnt Modeling for Predicting the Current and Future Potential Geographical Distribution of Quercus libani Olivier," Sustainability, MDPI, vol. 12(7), pages 1-17, March.
    17. Christos Polykretis & Manolis G. Grillakis & Athanasios V. Argyriou & Nikos Papadopoulos & Dimitrios D. Alexakis, 2021. "Integrating Multivariate (GeoDetector) and Bivariate (IV) Statistics for Hybrid Landslide Susceptibility Modeling: A Case of the Vicinity of Pinios Artificial Lake, Ilia, Greece," Land, MDPI, vol. 10(9), pages 1-23, September.
    18. Aihua Wei & Duo Li & Yahong Zhou & Qinghai Deng & Liangdong Yan, 2021. "A novel combination approach for karst collapse susceptibility assessment using the analytic hierarchy process, catastrophe, and entropy model," 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. 105(1), pages 405-430, January.
    19. Holder, Anna M. & Markarian, Arev & Doyle, Jessie M. & Olson, John R., 2020. "Predicting geographic distributions of fishes in remote stream networks using maximum entropy modeling and landscape characterizations," Ecological Modelling, Elsevier, vol. 433(C).
    20. Amin Salehpour Jam & Jamal Mosaffaie & Faramarz Sarfaraz & Samad Shadfar & Rouhangiz Akhtari, 2021. "GIS-based landslide susceptibility mapping using hybrid MCDM 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. 108(1), pages 1025-1046, August.

    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:84:y:2016:i:1:d:10.1007_s11069-016-2443-5. 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.