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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLIII-B4-2022
https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-53-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-53-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
01 Jun 2022
| 01 Jun 2022
INTEGRATING CONCEPTS OF ARTIFICIAL INTELLIGENCE IN THE EO4GEO BODY OF KNOWLEDGE
R. Lemmens
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands
S. Lang
Department of Geoinformatics, University of Salzburg, Salzburg, Austria
F. Albrecht
Department of Geoinformatics, University of Salzburg, Salzburg, Austria
E. Augustijn
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands
C. Granell
Institute of New Imaging Technologies (INIT), Universitat Jaume I (UJI), Spain
M. Olijslagers
Spatial Applications Division Leuven, KU Leuven, Belgium
C. Pathe
Department of Earth Observation, Friedrich-Schiller-University, Jena, Germany
C. Dubois
Department of Earth Observation, Friedrich-Schiller-University, Jena, Germany
M. Stelmaszczuk-Górska
Department of Earth Observation, Friedrich-Schiller-University, Jena, Germany
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Short summary
Short summary
Comprehensive and sustainable landslide management, including identification of landslide-susceptible areas, requires a lot of organisations and people to collaborate efficiently. In this study, we propose a concept for a system that provides users with a platform to share the location of landslide events for further collaboration in Nepal. The system can be beneficial for specifying potentially risky regions and consequently, the development of risk mitigation strategies at the local level.
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