Geospatial Data-Based Predictive Modelling of Landslide Events in Raigad District

In regions with steep hills like India’s Raigad District, landslides pose an imminent danger to human life and property. This study utilises the latest methods in machine learning and Geographic Information Systems (GIS) to present an extensive look into the development of a robust landslide alerting system. The system’s objective is to increase detection accuracy. In addition to assisting the disaster management efforts, this research enables authorities and researchers in the area with helpful data. Modern machine learning and deep learning techniques, such as ANN, Logistic Regression and Gradient Boosting, are included in our approach. The datasets were developed to provide reliable method for detecting landslides. To train our models for risk assessment, we took advantage of the temporal and spatial information present in the datasets. Processing data, feature engineering and predictive model building are all included in the research. The research paper presents an effective approach to locate landslides through the use of advanced machine learning and Geographic information systems (GIS). This research could significantly improve disaster management in Raigad District and other landslide-prone areas by addressing the regions that need improvement.