Abstract
Kerala is the third most densely populated state in India, with 860 persons per square kilometer. The uniqueness and diversity of the state’s topology make it highly vulnerable to natural hazards. Kerala State Emergency Operations Centre Kerala State Disaster Management Authority (2016). This study was initiated in the backdrop of landslides and floods in 2018, which had wreaked havoc in the region. Among the 4728 landslides reported in the state’s ten districts, Idukki was the worst affected with 2219 landslide occurrences. A statistically significant cluster of landslide hotspots was identified within the Idukki district using Getis-Ord Gi* statistics. Landslide susceptibility analysis was carried out using logistic regression (LR) and artificial neural network (ANN). Natural parameters influencing landslides such as slope, elevation, rainfall, geology, distance to drainage, and anthropogenic conditioning factors such as land use, road density, and quarry density were considered in this study. The results indicate that both natural and anthropogenic conditioning factors have a significant influence on landslide occurrences. According to the LR results, about 37.87% and 38.07% of the district’s total area is situated in high and medium landslide susceptibility zones. The results establish that ANN has better predictive performance compared with LR.
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Landslide inventory data is prepared by the Department of Geoinformation Science and Earth Observation (ITC), University of Twente, Netherlands, in collaboration with the Geological Survey of India and the University of Kerala. Land-use map was prepared from Sentinel-2 satellite image, and elevation data is obtained from USGS. The slope of the study area is generated from the Aster GDEM. Rainfall data is collected from the Indian Metrological Department (IMD) and interpolated for the whole area. Geology and drainage data were acquired from Kerala State Land Use Board, Department of Planning and Economic Affairs, Government of Kerala. The quarry data for the study was obtained from the Forest Health Division, Kerala Forest Research Institute Peechi. Road networks are downloaded from Open Street Maps (OSM).
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Sheelu Jones: data collection, analyses and interpretation, the conceptualization of manuscript, writing, reviewing, and editing of the manuscript. Dr. Kasthurba A.K: conceptualization, methodology, and reviewing. Dr. Anjana Bhagyanathan: conceptualization, methodology, and reviewing. Binoy B V: data interpretation, analyses, the conceptualization of manuscript, visualization, and reviewing.
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Jones, S., Kasthurba, A.K., Bhagyanathan, A. et al. Landslide susceptibility investigation for Idukki district of Kerala using regression analysis and machine learning. Arab J Geosci 14, 838 (2021). https://doi.org/10.1007/s12517-021-07156-6
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DOI: https://doi.org/10.1007/s12517-021-07156-6