Dragon5

Dragon 5: Integration of multi-source Remote Sensing Data to detect and monitoring large and rapid landslides and use of Artificial Intelligence for Cultural Heritage preservation

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Remote sensing (RS) data is successfully applied since decades for the identification and monitoring of landslide phenomena at different spatio-temporal scales. However, limitations associated with data availability/accessibility might still hamper the development of operational tools. The Dragon5 project (D5) foresees to continue the monitoring activities started with the Dragon4 project by further testing multi-source RS data in diverse areas located in China and additional mountainous test areas. The overall goal of the project is to use a wide range of remote sensing data to detect and map landslides, to assess their activity and velocity, to determine the spatio-temporal variation of landslides in relation to pre-disposing factors such as land use, to assess the related consequences, and to analyze the hazards and risks to aid local and regional decision makers. In this context, the Eurac team will collaborate with the Nanjing Normal University (China) to exploit optical remote sensing data to automatically map landslide phenomena in the Alps and China. 


Contact person: Stefan Steger (stefan.steger@eurac.edu) 

Publications
Using machine learning and satellite data from multiple sources to analyze mining, water management, and preservation of cultural heritage
Sousa JJ, Lin J, Wang Q, Liu G, Fan J, Bai S, Zhao H, Pan H, Wei W, Rittlinger V, Mayrhofer P, Sonnenschein R, Steger S, Reis LP (2023)
Journal article
Geo-Spatial Information Science

More information: https://www.tandfonline.com/doi/citedby/10.1080/10095020.202 ...

https://doi.org/10.1080/10095020.2023.2234008

Project Team
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Stefan Steger

Stefan Steger

Project Manager
Stefan Steger

Stefan Steger

Team Member