Landslide Detection System Using Remote Sensed Image Classification

In this work, a novel technique for identifying and predicting landslide using remote sensing and image classification. Landslide pose a serious threat to communities and infrastructure and require careful monitoring. Our system uses machine learning techniques and high-resolution satellite photos to identify key features in the terrain that indicate landslide-prone areas. We classify earthquakes-prone areas using convolutional neural networks (CNN) and spectral analysis. The effectiveness of the system is demonstrated through extensive use of historical landslide data, demonstrating its potential as an early warning system for landslide mitigation and resource allocation.