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OGC Climate Disaster and Resilience Pilot 2024: Landslide Demonstrators Report
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| Definitionskos:definition | Landslides pose a significant threat, often triggered by extreme weather events like heavy rainfall or earthquakes, leading to extensive damage and loss of life. Traditional methods for detecting and measuring landslides are typically time-consuming and lack accuracy. This report introduces Landslideflow, a workflow based on the Common Workflow Language (CWL) designed to improve the detection and measurement of landslides. Utilizing remote sensing data, such as satellite images and digital elevation models, Landslideflow generates precise landslide displacement maps. The workflow is scalable and cloud-optimized, enabling it to handle large data volumes efficiently. Moreover, Landslideflow leverages advanced computer vision and machine learning techniques to enhance accuracy, offering a robust solution that is easy to deploy on cloud platforms. As an open-source tool, Landslideflow is freely accessible, providing a valuable resource for researchers and practitioners in the field. Landslideflow is a powerful tool for detecting and measuring landslides. It is accurate, scalable, cloud-optimized, and open source. Landslideflow can be used by scientists, engineers, and policymakers to better understand and mitigate the risks associated with landslides. |
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| Broaderbroader | http://www.opengis.net/def/doc-type/techpaper |
| http://purl.org/dc/terms/createdcreated | 2025-01-18 |
| Creatorcreator | Gérald Fenoy, Rajat Shinde |
| seeAlsoseeAlso | https://portal.ogc.org/files/?artifact_id=110244&version=1 |
| Statusstatus | valid |
| Notationnotation | 24-074 |
| Alternative LabelaltLabel | 24-074 |
| OGC Climate Disaster and Resilience Pilot 2024: Landslide Demonstrators Report | |
| OGC document typedoctype | http://www.opengis.net/def/doc-type/techpaper |