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Large-scale-multi-spatiotemporal-landslide-mapping
By using the pre-trained models, this method enables quick and simple mapping of landslides at various spatiotemporal scales. The method also offers the adaptability of re-training a pretrained model to identify landslides caused by both rainfall and earthquakes on different target locations.HR-GLDD-A-Global-Landslide-Mapping-Data-Repository
Multi-Temporal-Landslide-Mapping-Nepal
Introducing a transfer learning approach to map landslides temporally over a given spatial location.Building-Footprint-Extraction
This repository is for the Python Elective course at the Faculty of ITC, University of Twente, Netherlands. The repository consists of the data, model and instructions required to perform building footprint extraction from satellite imagery using a U-Net model.Building-Identification-for-Exp-Vul-Risk-Assessment
Information about buildings is, sufficed to say, a very important aspect not just for urban land registry or transportation but also for disaster/hazard risk assessment. Specifically, typological attributes of buildings like number of residents living in them, number of floors, and many more. The study aims at figuring and capturing the typological attributes of the buildings by incorporating deep learning and other proxy information as a means of detecting and characterising the buildings.Love Open Source and this site? Check out how you can help us