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1 to 5 of 5 Results
Jan 25, 2022
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...
Dec 9, 2021
Anders, Katharina; Winiwarter, Lukas; Höfle, Bernhard, 2021, "Improving change analysis from near-continuous 3D time series by considering full temporal information [Data and Source Code]", https://doi.org/10.11588/data/1L11SQ, heiDATA, V1
This dataset comprises the source code (Python scripts) and data to perform spatiotemporal segmentation in time series of surface change data for a (i) synthetic dataset and (ii) hourly snow cover changes acquired by terrestrial laser scanning. Further details are given in the co...
Aug 18, 2021
Weiser, Hannah; Winiwarter, Lukas; Anders, Katharina; Fassnacht, Fabian Ewald; Höfle, Bernhard, 2021, "Opaque Voxel-based Tree Models for Virtual Laser Scanning in Forestry Applications [Research Data and Source Code]", https://doi.org/10.11588/data/MZBO7T, heiDATA, V1
Virtual laser scanning (VLS), the simulation of laser scanning in a computer environment, is as a useful tool for field campaign planning, acquisition optimisation, and development and sensitivity analyses of algorithms in various disciplines including forestry research. One key...
Jun 15, 2021
Winiwarter, Lukas; Anders, Katharina; Zahs, Vivien; Hämmerle, Martin; Höfle, Bernhard, 2021, "M3C2-EP: Pushing the limits of 3D topographic point cloud change detection by error propagation [Data and Source Code]", https://doi.org/10.11588/data/XHYB10, heiDATA, V1
The analysis of topographic time series is often based on bitemporal change detection and quantification. For 3D point clouds, acquired using laser scanning or photogrammetry, random and systematic noise has to be separated from the signal of surface change by determining the mini...
Jan 13, 2021
Anders, Katharina; Winiwarter, Lukas; Mara, Hubert; Lindenbergh, Roderik; Vos, Sander E.; Höfle, Bernhard, 2021, "Fully Automatic Spatiotemporal Segmentation of 3D LiDAR Time Series for the Extraction of Natural Surface Changes [Source Code, Validation Material and Validation Results]", https://doi.org/10.11588/data/4HJHAA, heiDATA, V1
This dataset comprises the source code to perform fully automatic spatiotemporal segmentation in time series of topographic surface change data (Python scripts). Further provided is the validation material of the resulting extraction of 4D objects-by-change at the study site of a...
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