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Integrating VGI contributions for gully mapping using Kalman filter and machine learning

The codes and datsets included are related to experiments and results conducted to integrate different lines digitized by volunteers using Kalman filter with changing amount of input lines. Three approaches are included: i) Kalman filtering integration to investigate the role of basemaps and a numbe...

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Bibliographic Details
Main Authors: Vallejo Orti, Miguel (Author) , Anders, Katharina (Author) , Ajali, Oliubikum (Author) , Bubenzer, Olaf (Author) , Höfle, Bernhard (Author)
Format: Database Research Data
Language:English
Published: Heidelberg Universität 2024-02-19
DOI:10.11588/data/UHSQG0
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Author Notes:Miguel Vallejo Orti, Katharina Anders, Oliubikum Ajali, Olaf Bubenzer, Bernhard Höfle
Description
Summary:The codes and datsets included are related to experiments and results conducted to integrate different lines digitized by volunteers using Kalman filter with changing amount of input lines. Three approaches are included: i) Kalman filtering integration to investigate the role of basemaps and a number of contributions, ii) Kalman filtering coupled with a self-learning stratergy and, iii) a cross-training strategy. (2024-01-03)
Item Description:Gefördert durch: The Kurt-Hiehle-Foundation, Namibia University of Science and Technology - ILMI, DLR TanDEM-X Science Team: DEM_HYDR2024
Gesehen am 13.05.2024
Physical Description:Online Resource
DOI:10.11588/data/UHSQG0

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