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Landslide Susceptibility Assessment of a Part of the Western Ghats (India) Employing the AHP and F-AHP Models and Comparison with Existing Susceptibility Maps

Author

Listed:
  • Sheela Bhuvanendran Bhagya

    (Department of Coastal Disaster Management, Pondicherry University, Brookshabad Campus, Port Blair 744103, India)

  • Anita Saji Sumi

    (Department of Coastal Disaster Management, Pondicherry University, Brookshabad Campus, Port Blair 744103, India)

  • Sankaran Balaji

    (Department of Coastal Disaster Management, Pondicherry University, Brookshabad Campus, Port Blair 744103, India)

  • Jean Homian Danumah

    (Centre Universitaire de Recherche et d’Application en Télédétection (CURAT), Université Félix Houphouët-Boigny, Abidjan 00225, Côte d’Ivoire)

  • Romulus Costache

    (National Institute of Hydrology and Water Management, 013686 Bucharest, Romania
    Department of Civil Engineering, Transilvania University of Brasov, 500036 Brasov, Romania
    Danube Delta National Institute for Research & Development, 820112 Tulcea, Romania)

  • Ambujendran Rajaneesh

    (Department of Geology, University of Kerala, Thiruvananthapuram 695581, India)

  • Ajayakumar Gokul

    (Kerala State Emergency Operations Centre (KSEOC), Kerala State Disaster Management Authority (KSDMA), Thiruvananthapuram 695033, India)

  • Chandini Padmanabhapanicker Chandrasenan

    (Kerala State Emergency Operations Centre (KSEOC), Kerala State Disaster Management Authority (KSDMA), Thiruvananthapuram 695033, India)

  • Renata Pacheco Quevedo

    (Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), São José dos Campos 12227010, Brazil)

  • Alfred Johny

    (Kerala State Emergency Operations Centre (KSEOC), Kerala State Disaster Management Authority (KSDMA), Thiruvananthapuram 695033, India)

  • Kochappi Sathyan Sajinkumar

    (Department of Geology, University of Kerala, Thiruvananthapuram 695581, India
    Department of Geological & Mining Engineering & Sciences, Michigan Technological University, Houghton, MI 49931, USA)

  • Sunil Saha

    (Department of Geography, University of Gour Banga, Malda 732101, India)

  • Rajendran Shobha Ajin

    (Kerala State Emergency Operations Centre (KSEOC), Kerala State Disaster Management Authority (KSDMA), Thiruvananthapuram 695033, India
    Resilience Development Initiative (RDI), Bandung 40123, Indonesia)

  • Pratheesh Chacko Mammen

    (Kerala State Emergency Operations Centre (KSEOC), Kerala State Disaster Management Authority (KSDMA), Thiruvananthapuram 695033, India)

  • Kamal Abdelrahman

    (Department of Geology & Geophysics, College of Science, King Saud University, Riyadh 11451, Saudi Arabia)

  • Mohammed S. Fnais

    (Department of Geology & Geophysics, College of Science, King Saud University, Riyadh 11451, Saudi Arabia)

  • Mohamed Abioui

    (Department of Earth Sciences, Faculty of Sciences, Ibn Zohr University, Agadir 80000, Morocco
    MARE-Marine and Environmental Sciences Centre, Sedimentary Geology Group, Department of Earth Sciences, Faculty of Sciences and Technology, University of Coimbra, 3030-790 Coimbra, Portugal)

Abstract

Landslides are prevalent in the Western Ghats, and the incidences that happened in 2021 in the Koottickal area of the Kottayam district (Western Ghats) resulted in the loss of 10 lives. The objectives of this study are to assess the landslide susceptibility of the high-range local self-governments (LSGs) in the Kottayam district using the analytical hierarchy process (AHP) and fuzzy-AHP (F-AHP) models and to compare the performance of existing landslide susceptible maps. This area never witnessed any massive landslides of this dimension, which warrants the necessity of relooking into the existing landslide-susceptible models. For AHP and F-AHP modeling, ten conditioning factors were selected: slope, soil texture, land use/land cover (LULC), geomorphology, road buffer, lithology, and satellite image-derived indices such as the normalized difference road landslide index (NDRLI), the normalized difference water index (NDWI), the normalized burn ratio (NBR), and the soil-adjusted vegetation index (SAVI). The landslide-susceptible zones were categorized into three: low, moderate, and high. The validation of the maps created using the receiver operating characteristic (ROC) technique ascertained the performances of the AHP, F-AHP, and TISSA maps as excellent, with an area under the ROC curve (AUC) value above 0.80, and the NCESS map as acceptable, with an AUC value above 0.70. Though the difference is negligible, the map prepared using the TISSA model has better performance (AUC = 0.889) than the F-AHP (AUC = 0.872), AHP (AUC = 0.867), and NCESS (AUC = 0.789) models. The validation of maps employing other matrices such as accuracy, mean absolute error (MAE), and root mean square error (RMSE) also confirmed that the TISSA model (0.869, 0.226, and 0.122, respectively) has better performance, followed by the F-AHP (0.856, 0.243, and 0.147, respectively), AHP (0.855, 0.249, and 0.159, respectively), and NCESS (0.770, 0.309, and 0.177, respectively) models. The most landslide-inducing factors in this area that were identified through this study are slope, soil texture, LULC, geomorphology, and NDRLI. Koottickal, Poonjar-Thekkekara, Moonnilavu, Thalanad, and Koruthodu are the LSGs that are highly susceptible to landslides. The identification of landslide-susceptible areas using diversified techniques will aid decision-makers in identifying critical infrastructure at risk and alternate routes for emergency evacuation of people to safer terrain during an exigency.

Suggested Citation

  • Sheela Bhuvanendran Bhagya & Anita Saji Sumi & Sankaran Balaji & Jean Homian Danumah & Romulus Costache & Ambujendran Rajaneesh & Ajayakumar Gokul & Chandini Padmanabhapanicker Chandrasenan & Renata P, 2023. "Landslide Susceptibility Assessment of a Part of the Western Ghats (India) Employing the AHP and F-AHP Models and Comparison with Existing Susceptibility Maps," Land, MDPI, vol. 12(2), pages 1-29, February.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:2:p:468-:d:1067042
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    References listed on IDEAS

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    1. Feifei Jiang & Fu Chen & Yan Sun & Ziyi Hua & Xinhua Zhu & Jing Ma, 2023. "Spatiotemporal Pattern and Driving Mechanism of Cultivated Land Use Transition in China," Land, MDPI, vol. 12(10), pages 1-20, September.

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