11 to 12 of 12 Results
Jan 25, 2022 - 3D Spatial Data Processing
Zahs, Vivien; Winiwarter, Lukas; Anders, Katharina; Williams, Jack G.; Rutzinger, Martin; Bremer, Magnus; Höfle, Bernhard, 2021, "Correspondence-driven plane-based M3C2 for quantification of 3D topographic change with lower uncertainty [Data and Source Code]", https://doi.org/10.11588/data/TGSVUI, heiDATA, V2
The analysis and interpretation of 3D topographic change requires methods that achieve low uncertainties in change quantification. Many recent geoscientific studies that perform point cloud-based topographic change analysis have used the multi-scale-model-to-model-cloudcomparison... |
Oct 12, 2021 - GIScience / Geoinformatics Research Group
Li, Hao; Zech, Johannes; Ludwig, Christina; Fendrich, Sascha; Shapiro, Aurelie; Schultz, Michael; Zipf, Alexander, 2021, "Automatic mapping of national surface water with OpenStreetMap and Sentinel-2 MSI data using deep learning [Research Data]", https://doi.org/10.11588/data/AAKAF9, heiDATA, V1
DATASET FOR JOURNAL PAPER (https://doi.org/10.1016/j.jag.2021.102571) Large-scale mapping activities can benefit from the vastly increasing availability of earth observation (EO) data, especially when combined with volunteered geographical information (VGI) using machine learning... |