Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

There was an error with your search parameters. Please clear your search and try again.

1 to 4 of 4 Results
Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation
Jan 18, 2024
Weiser, Hannah; Ulrich, Veit; Winiwarter, Lukas; Esmorís, Alberto M.; Höfle, Bernhard, 2024, "Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation", https://doi.org/10.11588/data/UUMEDI, heiDATA, V1, UNF:6:9U7BGTgjjsWd1GduT1qXjA== [fileUNF]
This dataset contains 11 terrestrial laser scanning (TLS) tree point clouds (in .LAZ format v1.4) of 7 different species, which have been manually labeled into leaf and wood points. The labels are contained in the Classification field (0 = wood, 1 = leaf). The point clouds have a...
Correspondence-driven plane-based M3C2 for quantification of 3D topographic change with lower uncertainty [Data and Source Code]
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...
M3C2-EP: Pushing the limits of 3D topographic point cloud change detection by error propagation [Data and Source Code]
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...
HELIOS full-waveform laser scanning simulation framework. Source code, precompiled version, example files for study of understory tree height scanning and respective output.
May 22, 2017
Hämmerle, Martin; Lukač, Niko; Chen, Kuei-Chia; Koma, Zsófia; Wang, Chi-Kuei; Anders, Katharina; Höfle, Bernhard, 2017, "HELIOS full-waveform laser scanning simulation framework. Source code, precompiled version, example files for study of understory tree height scanning and respective output.", https://doi.org/10.11588/data/10101, heiDATA, V1
This data collection enables any user to reproduce the study Hämmerle et al. (2017). It provides the source code to compile the applied simulation framework. Furthermore, a precompiled version of the software including the necessary files are provided so that a direct start of th...
Add Data

Sign up or log in to create a dataverse or add a dataset.

Sign Up Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.