IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v110y2022i3d10.1007_s11069-021-05028-6.html
   My bibliography  Save this article

Investigation of landslides with natural lineaments derived from integrated manual and automatic techniques applied on geospatial data

Author

Listed:
  • Simon Sadiq

    (COMSATS University Islamabad (CUI)
    Geological Survey of Pakistan (GSP))

  • Umar Muhammad

    (COMSATS University Islamabad (CUI))

  • Michael Fuchs

    (Federal Institute for Geosciences and Natural Resources (BGR))

Abstract

Lineament extraction has long been performed through extensive field mapping. Recent advances in the field of remote sensing have made possible the availability of imageries from earth observation satellites with different Spatio-temporal resolutions, paving way for new automatic, semi-automatic, and manual techniques for the extraction of natural lineaments. The study focuses on the extraction of lineaments representing tectonic fault zones; the lineaments are extracted automatically and semi-automatically/manually. Results show that indirect information about the tectonic lineaments can be derived through automatic techniques whereas, the semi-automatic techniques are more effective to directly identify them. Detailed analyses of lineaments and landslides revealed that areas near lineaments, in general, experienced higher frequency of landslides. Moreover, it is also observed that lineaments are not the only factor that affects landslide density; other parameters like slope and lithology were also found to be the controlling factors in determining the spatial landslide distribution. Lastly, some recommendations have been made based on observations.

Suggested Citation

  • Simon Sadiq & Umar Muhammad & Michael Fuchs, 2022. "Investigation of landslides with natural lineaments derived from integrated manual and automatic techniques applied on geospatial 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. 110(3), pages 2141-2162, February.
    • Handle: RePEc:spr:nathaz:v:110:y:2022:i:3:d:10.1007_s11069-021-05028-6
    DOI: 10.1007/s11069-021-05028-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-021-05028-6
    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/s11069-021-05028-6?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. Binh Thai Pham & Dieu Tien Bui & Indra Prakash & M. B. Dholakia, 2016. "Rotation forest fuzzy rule-based classifier ensemble for spatial prediction of landslides using GIS," 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(1), pages 97-127, August.
    2. Chang-Jo Chung & Andrea Fabbri, 2003. "Validation of Spatial Prediction Models for Landslide Hazard 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. 30(3), pages 451-472, November.
    3. Jewgenij Torizin & Michael Fuchs & Adnan Alam Awan & Ijaz Ahmad & Sardar Saeed Akhtar & Simon Sadiq & Asif Razzak & Daniel Weggenmann & Faseeh Fawad & Nimra Khalid & Faisan Sabir & Ahsan Jamal Khan, 2017. "Statistical landslide susceptibility assessment of the Mansehra and Torghar districts, Khyber Pakhtunkhwa Province, Pakistan," 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. 89(2), pages 757-784, November.
    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. D. Costanzo & C. Cappadonia & C. Conoscenti & E. Rotigliano, 2012. "Exporting a Google Earth ™ aided earth-flow susceptibility model: a test in central Sicily," 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 103-114, March.
    2. 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.
    3. 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.
    4. 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.
    5. Quoc Bao Pham & Sk Ajim Ali & Elzbieta Bielecka & Beata Calka & Agata Orych & Farhana Parvin & Ewa Łupikasza, 2022. "Flood vulnerability and buildings’ flood exposure assessment in a densely urbanised city: comparative analysis of three scenarios using a neural network 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(2), pages 1043-1081, September.
    6. Viet-Tien Nguyen & Trong Hien Tran & Ngoc Anh Ha & Van Liem Ngo & Al-Ansari Nadhir & Van Phong Tran & Huu Duy Nguyen & Malek M. A. & Ata Amini & Indra Prakash & Lanh Si Ho & Binh Thai Pham, 2019. "GIS Based Novel Hybrid Computational Intelligence Models for Mapping Landslide Susceptibility: A Case Study at Da Lat City, Vietnam," Sustainability, MDPI, vol. 11(24), pages 1-24, December.
    7. 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.
    8. Israr Ullah & Bilal Aslam & Syed Hassan Iqbal Ahmad Shah & Aqil Tariq & Shujing Qin & Muhammad Majeed & Hans-Balder Havenith, 2022. "An Integrated Approach of Machine Learning, Remote Sensing, and GIS Data for the Landslide Susceptibility Mapping," Land, MDPI, vol. 11(8), pages 1-20, August.
    9. Alejandro Gonzalez-Ollauri & Slobodan B. Mickovski, 2021. "A Simple GIS-Based Tool for the Detection of Landslide-Prone Zones on a Coastal Slope in Scotland," Land, MDPI, vol. 10(7), pages 1-15, June.
    10. Massimo Conforti & Pietro Aucelli & Gaetano Robustelli & Fabio Scarciglia, 2011. "Geomorphology and GIS analysis for mapping gully erosion susceptibility in the Turbolo stream catchment (Northern Calabria, 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. 56(3), pages 881-898, March.
    11. Nikolaos Tavoularis & George Papathanassiou & Athanassios Ganas & Panagiotis Argyrakis, 2021. "Development of the Landslide Susceptibility Map of Attica Region, Greece, Based on the Method of Rock Engineering System," Land, MDPI, vol. 10(2), pages 1-31, February.
    12. Paulo Rodolpho Pereira Hader & Fábio Augusto Gomes Vieira Reis & Anna Silvia Palcheco Peixoto, 2022. "Landslide risk assessment considering socionatural factors: methodology and application to Cubatão municipality, São Paulo, Brazil," 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. 110(2), pages 1273-1304, January.
    13. 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.
    14. Massimo Conforti & Gaetano Robustelli & Francesco Muto & Salvatore Critelli, 2012. "Application and validation of bivariate GIS-based landslide susceptibility assessment for the Vitravo river catchment (Calabria, south 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. 61(1), pages 127-141, March.
    15. Muhammad Basharat & Muhammad Tayyib Riaz & M. Qasim Jan & Chong Xu & Saima Riaz, 2021. "A review of landslides related to the 2005 Kashmir Earthquake: implication and future challenges," 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 1-30, August.
    16. Jörg Grunert & Sigrid Hess, 2010. "The Upper Middle Rhine Valley as a risk area," 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. 55(3), pages 577-597, December.
    17. Halil Akinci & Mustafa Zeybek, 2021. "Comparing classical statistic and machine learning models in landslide susceptibility mapping in Ardanuc (Artvin), Turkey," 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(2), pages 1515-1543, September.
    18. Mehrnoosh Jadda & Helmi Shafri & Shattri Mansor, 2011. "PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, 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. 57(2), pages 395-412, May.
    19. I. P. Kovács & T. Bugya & Sz. Czigány & M. Defilippi & D. Lóczy & P. Riccardi & L. Ronczyk & P. Pasquali, 2019. "How to avoid false interpretations of Sentinel-1A TOPSAR interferometric data in landslide mapping? A case study: recent landslides in Transdanubia, Hungary," 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(2), pages 693-712, March.
    20. Prafull Singh & Ankit Sharma & Ujjwal Sur & Praveen Kumar Rai, 2021. "Comparative landslide susceptibility assessment using statistical information value and index of entropy model in Bhanupali-Beri region, Himachal Pradesh, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 5233-5250, April.

    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:110:y:2022:i:3:d:10.1007_s11069-021-05028-6. 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.