IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i3p659-d1094432.html
   My bibliography  Save this article

The Role of Historical Data to Investigate Slow-Moving Landslides by Long-Term Monitoring Systems in Lower Austria

Author

Listed:
  • Philipp Marr

    (Geomorphological Systems and Risk Research, Department of Geography and Regional Research, University of Vienna, Universitätsstraße 7, 1010 Vienna, Austria)

  • Yenny Alejandra Jiménez Donato

    (Geomorphological Systems and Risk Research, Department of Geography and Regional Research, University of Vienna, Universitätsstraße 7, 1010 Vienna, Austria)

  • Edoardo Carraro

    (Geomorphological Systems and Risk Research, Department of Geography and Regional Research, University of Vienna, Universitätsstraße 7, 1010 Vienna, Austria)

  • Robert Kanta

    (Geomorphological Systems and Risk Research, Department of Geography and Regional Research, University of Vienna, Universitätsstraße 7, 1010 Vienna, Austria)

  • Thomas Glade

    (Geomorphological Systems and Risk Research, Department of Geography and Regional Research, University of Vienna, Universitätsstraße 7, 1010 Vienna, Austria)

Abstract

Landslides are one of the most significant natural hazards worldwide. They can have far-reaching negative impacts on societies in different socio-economic sectors as well as on the landscape. Among the different types and processes that can also affect infrastructure and land use planning, slow-moving landslides are often underestimated. Therefore, studying areas affected by slow movements provide an opportunity to better understand the spatial and temporal patterns of these processes, their forcings, mechanisms, and potential risks. This study aims to investigate the importance of historical data for improving landslide hazard assessment in Lower Austria (Austria), which is particularly prone to landslides. This paper focuses on how historical information formed the basis for the establishment of three long-term landslide monitoring observatories in this region. The analysis conducted highlights the importance of using historical data to better assess the frequency and magnitude relationships and phases of landslide activity. In particular, they can extend the temporal window and provide relevant information on past events and accelerations to improve knowledge of landslide dynamics and the resulting socio-economic impacts. In order to better assess the landslide hazard associated, it is necessary to integrate historical data and monitoring datasets obtained by surface and subsurface methods. Both components allow for the characterization of the spatio-temporal evolution of slow movements and the analysis of the hazard over time. Based on a variety of historical sources, it was possible to install the instruments constituting the long-term landslide monitoring observatories in a meaningful manner. The results demonstrate the influential role of human impact on the stability conditions, which may also contribute to landslide occurrence. In this regard, the attempt to combine historical data and long-term, continuous monitoring systems in the presented landslide observatories can improve landslide risk reduction measures in the region. The integration of different techniques and tools, along with ongoing research and collaboration with local authorities, will further improve our understanding of these slow-moving processes and the development of effective management strategies.

Suggested Citation

  • Philipp Marr & Yenny Alejandra Jiménez Donato & Edoardo Carraro & Robert Kanta & Thomas Glade, 2023. "The Role of Historical Data to Investigate Slow-Moving Landslides by Long-Term Monitoring Systems in Lower Austria," Land, MDPI, vol. 12(3), pages 1-22, March.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:3:p:659-:d:1094432
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/3/659/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/12/3/659/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gianluca Esposito & Cristiano Carabella & Giorgio Paglia & Enrico Miccadei, 2021. "Relationships between Morphostructural/Geological Framework and Landslide Types: Historical Landslides in the Hilly Piedmont Area of Abruzzo Region (Central Italy)," Land, MDPI, vol. 10(3), pages 1-28, March.
    2. Shirin Moradi & Thomas Heinze & Jasmin Budler & Thanushika Gunatilake & Andreas Kemna & Johan Alexander Huisman, 2021. "Combining Site Characterization, Monitoring and Hydromechanical Modeling for Assessing Slope Stability," Land, MDPI, vol. 10(4), pages 1-23, April.
    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. Weisong Chen & Zhuo Chen & Danqing Song & Hongjin He & Hao Li & Yuxian Zhu, 2024. "Landslide Detection Using the Unsupervised Domain-Adaptive Image Segmentation Method," Land, MDPI, vol. 13(7), pages 1-24, 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. Enrico Miccadei & Cristiano Carabella & Giorgio Paglia, 2022. "Landslide Hazard and Environment Risk Assessment," Land, MDPI, vol. 11(3), pages 1-5, March.
    2. Anup Neupane & Kabi Raj Paudyal, 2021. "Lithological Control on Landslide in the Siwalik Section of the Lakhandehi Khola Watershed of Sarlahi District, South-Eastern Nepal," Journal of Development Innovations, KarmaQuest International, vol. 5(2), pages 44-65, December.
    3. Fabio Luino & Jerome De Graff & Marcella Biddoccu & Francesco Faccini & Michele Freppaz & Anna Roccati & Fabrizio Ungaro & Michele D’Amico & Laura Turconi, 2022. "The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy)," Land, MDPI, vol. 11(8), pages 1-26, July.
    4. Samuele Segoni & Francesco Caleca, 2021. "Definition of Environmental Indicators for a Fast Estimation of Landslide Risk at National Scale," Land, MDPI, vol. 10(6), pages 1-14, June.
    5. Jasmin Grifka & Maximilian Weigand & Andreas Kemna & Thomas Heinze, 2022. "Impact of an Uncertain Structural Constraint on Electrical Resistivity Tomography for Water Content Estimation in Landslides," Land, MDPI, vol. 11(8), pages 1-13, July.

    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:jlands:v:12:y:2023:i:3:p:659-:d:1094432. 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.