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Earthquakes and tropical cyclones cause the suffering of millions of peoplearound the world every year. The resulting landslides exacerbate the effects ofthese disasters. Landslide detection is, therefore, a critical task for theprotection of human life and livelihood in mountainous areas. To tackle thisproblem, we propose a combination of satellite technology and Deep NeuralNetworks (DNNs). We evaluate the performance of multiple DNN-based methods forlandslide detection on actual satellite images of landslide damage. Ouranalysis demonstrates the potential for a meaningful social impact in terms ofdisasters and rescue.

Large-Scale Landslides Detection from Satellite Images with Incomplete Labels