Bayesian Spatial Modeling of Landslide Events Using Integrated Nested Laplace Approximation (INLA): A Study Case on Natural Conditions and Community Actions in East Java, Indonesia - Salman Alfarisi; Athalia Christina; Sadiyana Yaqutna Naqiya; Ro'fah Nur Rachmawati; Amir Machmud; Endah Kinarya Palupi (International Journal of Hydrological and Environmental for Sustainability, 2023)
Bayesian Spatial Modeling Using Integrated Nested Laplace Approximation (INLA) is an advanced statistical technique that can be used to model and analyze occurrences in geographic areas.Â Landslides are one of natural disasters that occur due to natural and human factors and pose a serious threat to East Java Province which has complex natural conditions. The disaster brings various losses, including economic, infrastructural, human life, and environmental. This study investigates the factors contributing to landslides across 29 districts and 9 cities in East Java, Indonesia, using spatial regression modeling by Integrated Nested Laplace Approximation (INLA).Â The factors include the number of seaside villages, the number of slope topography villages, and the area of temporarily uncultivated gardens and fields in 2021. The modeling results show that the number of seaside villages, the number of slope topography villages, and the area of fields that are temporarily uncultivated have a significant influence on the occurrence of landslides so that efforts to mitigate and prevent such disasters can be focused on the contributing factors. We conclude that the model might be able to identify potential landslide risk areas through mapping.