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Sen12Landslides (S12LS)

Authors: Paul Höhn

Keywords: Landslides, Sentinel-1, Sentinel-2, DEM, SITS

https://github.com/PaulH97/Sen12Landslides

Sen12Landslides is a large-scale, multi-modal dataset featuring 75,000 annotations from Sentinel-1/2 timeseries and DEM data designed to advance spatio-temporal landslide detection and geohazard monitoring. By providing precise pre- and post-event imagery across 15 global regions, it enables deep learning models to capture the complex temporal dynamics of landslide behavior.

Publications

A Spatio-Temporal Dataset for Satellite-Based Landslide Detection

Höhn P, Heidler K, Behling R, Zhu X - Scientific Data - 2025

10.1038/s41597-025-06167-2

Sen12Landslides

Paul Höhn, Konrad Heidler, Robert Behling, Xiao Xiang Zhu - Hugging Face - 2025

10.57967/hf/5883

Helmholtz Imaging Projects

2021: WeMonitor - Weekly Supervised Deep Learning Models for Detecting and Monitoring Spatio-Temporal Earth Surface Anomalies in Optical and Radar Satellite Time Series

License

CC-BY-4.0

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Paul Höhn

Deutsches Zentrum für Luft- und Raumfahrt - Munich

I work on spatio-temporal anomaly detection in multi-modal and multi-temporal satellite image time series (SITS), with a focus on natural hazards such as landslides, floods and wildfires. My research involves developing novel datasets and model architectures to advance spatio-temporal learning …

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