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An Automatic Iterative Random Forest approach to derive gully activity maps in large areas with training data scarcity [Data and Source Code]
May 13, 2024 - 3D Spatial Data Processing
Vallejo-Orti, Miguel; Winiwarter, Lukas; Corral, Eva; Williams, Jack; Bubenzer, Olaf; Höfle, Bernhard, 2024, "An Automatic Iterative Random Forest approach to derive gully activity maps in large areas with training data scarcity [Data and Source Code]", https://doi.org/10.11588/data/WGAU4Q, heiDATA, V1
Gullies are landforms with specific patterns of shape, topography, hydrology, vegetation, and soil characteristics. Remote sensing products (TanDEM-X, Sentinel-1, and Sentinel-2) serve as inputs into an iterative algorithm, initialized using a micro-mapping simulation as training...
Integrating VGI contributions for gully mapping using Kalman filter and machine learning
Feb 19, 2024 - 3D Spatial Data Processing
Vallejo Orti, Miguel; Anders, Katharina; Ajali, Oliubikum; Bubenzer, Olaf; Höfle, Bernhard, 2024, "Integrating VGI contributions for gully mapping using Kalman filter and machine learning", https://doi.org/10.11588/data/UHSQG0, heiDATA, V1, UNF:6:dbfZe/C8CmWXcBEZJg2RPw== [fileUNF]
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...
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