Landslide Dataset Moxi Town

The Landslide Detection dataset focuses on a detailed collection of geospatial imagery and environmental data from Moxi Town, an area known for its challenging mountainous landscapes and volatile weather patterns. Given Moxi Town’s vulnerability to frequent landslides, this dataset plays a pivotal role in improving the accuracy of predictive models for early-warning systems and supporting disaster management efforts.

This dataset encompasses high-resolution satellite and drone images, topographical maps, and meteorological data captured over multiple seasons to account for various conditions that trigger landslides. The images cover different stages of landslide activity—before, during, and after occurrences—allowing for comprehensive analysis and training of AI models focused on detecting and predicting landslide risks.

The dataset is ideal for researchers, engineers, and governmental bodies focused on environmental safety, infrastructure planning, and disaster mitigation. It also facilitates the development of machine learning algorithms designed to identify early signs of landslides, such as soil displacement, erosion patterns, and precipitation trends. The diverse range of data sources enables robust model training, providing a critical resource for creating adaptive and resilient systems for landslide prediction and prevention.