An Intelligent Geospatial Framework for Landslide Prediction Through AI and Satellite Data

Abstract

The effects of landslides and other natural catastrophes on both the built environment and people can be devastating. Monitoring sensors and conducting expensive and labor-intensive geological studies are commonplace in traditional landslide prediction approaches. An artificial intelligence (AI) based approach to landslide prediction using satellite image analysis is investigated in this paper. In order to determine the probability of landslides, the software analyzes high-resolution satellite images using deep learning techniques, particularly Convolutional Neural Networks (CNNs). Using past data, topographical features, and environmental variables, the strategy improves the accuracy of predictions. This AI-driven approach makes it easier for disaster management officials to establish early warning systems and implement preventive measures. The findings suggest that models powered by AI can improve the precision and practicality of landslide forecasts, leading to less damage from natural catastrophes.