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Research Article Open access CC BY 4.0

Landslide Susceptibility Mapping of Chaliyar River Basin by Multivariate Statistical Model

L. Aiswarya, K. P. Rema, J. Shyla, V. K. Brijesh, V. Vaisakh

Journal of Experimental Agriculture International · pp. 23–35 · Published 15 Dec 2023

10.9734/jeai/2023/v45i122262

Abstract

Landslides were frequently observed in nature that can result in significant property damage and fatalities. Land management in landslide-prone areas can be aided by preparing a landslide susceptibility map. The landslide susceptibility of Chaliyar river basin was evaluated using the logistic regression (LR) technique. For this, an inventory map of 592 prior landslides was created using Landsat 8 OLI satellite imagery. The inventory of landslides was then randomly split into 30% and 70% for model training and validation respectively. Fifteen landslide causative factors viz., Slope, Aspect, Curvature, Relative Relief, TWI, Distance to Road, Distance to Streams, Distance to Lineaments, Land Use Land Cover, Drainage Density, Road Density, Lineament Density, Geomorphology, Soil Texture, NDVI were considered for landslide susceptibility modelling. Utilising a Receiver Operating Characteristics Curve (ROC) and Area Under Curve (AUC) value, the resulting susceptibility maps were validated. Analysis reveals that the validation stage of the LR model had a ROC-AUC value of 0.815. The study also demonstrates that slope, soil texture and LULC play a substantial role on the occurrence of landslides in the study area. The proposed landslide susceptibility model is appropriate, taking into account the ROC-AUC (0.815), and can be applied to future land use planning and landslide mitigation in the Chaliyar basin.

Landslide susceptibility logistic regression causative parameters ROC-AUC chaliyar river basin

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