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. 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. 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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Esteban Bravo-López & Tomás Fernández Del Castillo & Chester Sellers & Jorge Delgado-García, 2023. "Analysis of Conditioning Factors in Cuenca, Ecuador, for Landslide Susceptibility Maps Generation Employing Machine Learning Methods," Land, MDPI, vol. 12(6), pages 1-28, May.
    11. Chuhan Wang & Qigen Lin & Leibin Wang & Tong Jiang & Buda Su & Yanjun Wang & Sanjit Kumar Mondal & Jinlong Huang & Ying Wang, 2022. "The influences of the spatial extent selection for non-landslide samples on statistical-based landslide susceptibility modelling: a case study of Anhui Province 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. 112(3), pages 1967-1988, July.
    12. 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.
    13. Mansheng Lin & Shuai Teng & Gongfa Chen & David Bassir, 2023. "Transfer Learning with Attributes for Improving the Landslide Spatial Prediction Performance in Sample-Scarce Area Based on Variational Autoencoder Generative Adversarial Network," Land, MDPI, vol. 12(3), pages 1-26, February.
    14. Ginés Suárez & María José Domínguez-Cuesta, 2021. "Improving landslide susceptibility predictive power through colluvium mapping in Tegucigalpa, Honduras," 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 47-66, January.
    15. Ataollah Shirzadi & Lee Saro & Oh Hyun Joo & Kamran Chapi, 2012. "A GIS-based logistic regression model in rock-fall susceptibility mapping along a mountainous road: Salavat Abad case study, Kurdistan, 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. 64(2), pages 1639-1656, November.
    16. 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.
    17. Yanbo Cao & Xinsheng Wei & Wen Fan & Yalin Nan & Wei Xiong & Shilin Zhang, 2021. "Landslide susceptibility assessment using the Weight of Evidence method: A case study in Xunyang area, China," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-18, January.
    18. Krishna Devkota & Amar Regmi & Hamid Pourghasemi & Kohki Yoshida & Biswajeet Pradhan & In Ryu & Megh Dhital & Omar Althuwaynee, 2013. "Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling–Narayanghat road section in Nepal Himalaya," 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(1), pages 135-165, January.
    19. 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.
    20. 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.

    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.