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Soil micromorphology for modeling spatial on landslide susceptibility mapping: a case study in Kelara Subwatershed, Jeneponto Regency of South Sulawesi, Indonesia

Author

Listed:
  • Asmita Ahmad

    (Hasanuddin University)

  • Meutia Farida

    (Hasanuddin University)

  • Nirmala Juita

    (Hasanuddin University)

  • Muh Jayadi

    (Hasanuddin University)

Abstract

Comprehensively, the results of categorizing the susceptibility levels demonstrate distinct results, where landslides are more common in areas with a relatively high to moderate susceptibility class in comparison with those with a high susceptibility class. For this research, the soil parameter test method was conducted by utilizing a split-plot design with land use as the main plot, slope as a subplot, and soil physics (permeability, bulk density, and porosity) as a sub-subplot with three replications. Spatial modeling through regression analysis by incorporating ordinary least squares. The interaction between the type of land use, slope, and physical properties of the soil on the occurrence of landslides at the study site demonstrates a strong relationship with a significant p-value = 0.043. Increased land use by the community has accelerated the formation of soil micromorphology in the form of plane voids, cross-striated and grano-striated, thereby catalyzing internal shifts (micro-shifts) in the soil body. The landslide susceptibility map at the study site has been categorized into seven spatial susceptibility classes: extremely low, very low, low, moderate, high, very high, and extremely high. Spatial modeling with OLS illustrates that the independent factors in the form of lithology, rainfall, slope, land cover/land use, and population only get an R2 value of 30.8%. Adding landslide independent parameter data in the form of soil organic carbon factor, texture, erodibility, and soil micromorphology produces a spatial model of landslide susceptibility with an increase in the accuracy value of R2 by 66.66%. The spatial model demonstrates a high level of consistency with very significant soil micromorphology at a p-value of

Suggested Citation

  • Asmita Ahmad & Meutia Farida & Nirmala Juita & Muh Jayadi, 2023. "Soil micromorphology for modeling spatial on landslide susceptibility mapping: a case study in Kelara Subwatershed, Jeneponto Regency of South Sulawesi, Indonesia," 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(2), pages 1445-1462, September.
  • Handle: RePEc:spr:nathaz:v:118:y:2023:i:2:d:10.1007_s11069-023-06063-1
    DOI: 10.1007/s11069-023-06063-1
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    References listed on IDEAS

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    1. Nussaïbah B. Raja & Ihsan Çiçek & Necla Türkoğlu & Olgu Aydin & Akiyuki Kawasaki, 2017. "Landslide susceptibility mapping of the Sera River Basin using logistic regression 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. 85(3), pages 1323-1346, February.
    2. Emmanouil Psomiadis & Andreas Papazachariou & Konstantinos X. Soulis & Despoina-Simoni Alexiou & Ioannis Charalampopoulos, 2020. "Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data," Land, MDPI, vol. 9(5), pages 1-26, April.
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