Integrating multi-user digitising actions for mapping gully outlines using a combined approach of Kalman filtering and machine learning

Integrating multi-user digitising actions for mapping gully outlines using a combined approach of Kalman filtering and machine learning

Scalable and transferable methods for generating reliable reference data for automated remote sensing approaches are crucial, especially for mapping complex Earth surface processes such as gully erosion in low-populated and inaccessible areas. As an alternative for the labour-intense in-situ authori...

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Bibliographic Details
Main Authors: Miguel Vallejo Orti, Katharina Anders, Oluibukun Ajayi, Olaf Bubenzer, Bernhard Höfle
Format: Article
Language:English
Published: Elsevier 2024-04-01
Series:ISPRS Open Journal of Photogrammetry and Remote Sensing
Subjects:
Crowdsourcing
Data integration
Gully monitoring
Kalman filtering
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2667393224000024

Internet

http://www.sciencedirect.com/science/article/pii/S2667393224000024

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