Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests

Weiser, Hannah; Schäfer, Jannika; Winiwarter, Lukas; Krašovec, Nina; Fassnacht, Fabian E.; Höfle, Bernhard

doi:https://doi.org/10.5194/essd-14-2989-2022

Articles | Volume 14, issue 7

https://doi.org/10.5194/essd-14-2989-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-14-2989-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 7

Data description paper

|

05 Jul 2022

Data description paper |

| 05 Jul 2022

Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests

Hannah Weiser, Jannika Schäfer, Lukas Winiwarter, Nina Krašovec, Fabian E. Fassnacht, and Bernhard Höfle

Download

Final revised paper (published on 05 Jul 2022)
Supplement to the final revised paper
Preprint (discussion started on 04 Feb 2022)

Interactive discussion

Status: closed

RC1:
'Comment on essd-2022-39', Anonymous Referee #1, 15 Feb 2022

The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2022-39/essd-2022-39-RC1-supplement.pdf

Citation: https://doi.org/10.5194/essd-2022-39-RC1
- AC1:
  'Reply on RC1', Hannah Weiser, 24 Feb 2022
  Thank you for very much for your factual and constructive review. We appreciate your suggestions and provide our replies below.
  
  Abstract and Introduction:
  
  We agree that the data descriptor would benefit from presenting a broader range of applications for the data. We will consider your suggestions and revise these sections.
  
  Methods:
  
  A table with the number of trees by data source per plot seems like a great idea. As on the PANGAEA repository, each plot can (or must) be downloaded separately, this would greatly help users with their choice. We will include this in the revised manuscript.
  
  Data:
  
  We will think about providing such a file with single tree information. However, we also think that this would be a massive (<1400 rows and many columns) and potentially confusing table.
  
  Alternatively, we could write a script which users can run in the folders (as downloaded from the PANGAEA repository) which can create such a file. The user may also provide further parameters, so that e.g., the filenames for a specific data source/species/quality/etc. can be derived.
  
  We are also building up a web-based database, where users can query the point clouds by different filters and download the results. I think this also includes your requested functionality and maybe even goes beyond. This database may later be enriched by further tree point clouds by our working group or other contributors.
  
  Technical corrections:
  
  Thanks a lot! We will correct these errors.
  
  Citation: https://doi.org/10.5194/essd-2022-39-AC1
RC2:
'Comment on essd-2022-39', Anonymous Referee #2, 02 Mar 2022

The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2022-39/essd-2022-39-RC2-supplement.pdf

Citation: https://doi.org/10.5194/essd-2022-39-RC2
- AC2:
  'Reply on RC2', Hannah Weiser, 15 Mar 2022
  Thanks a lot for your helpful review. We appreciate your suggestions and will consider them for the final manuscript. We provide our replies to the comments below.
  
  Basic stand metrics
  
  We think this is a good idea and will include such a supplementary data table. 
  
  Line 226/227; Circle/Ellipse fitting:
  
  We only had a few cases, where it was difficult to fit a circle or an ellipse due to the point cloud quality (e.g., AbiAlb_SP02_01 to AbiAlb_SP02_05). For transparency, we could add the figures of the points and the fitted circles/ellipses for each tree to a supplementary file/folder. We could furthermore point out a) for which trees we had to fit a circle for a slice different than the 1.28 m and 1.32 m that we mentioned in the paper (e.g., thicker slice or different vertical position) and b) for which trees the estimated DBH might be less accurate due to point cloud quality (e.g., few points on the stem).
  
  Line 282:
  
  We did not use a quantitative threshold, but discarded the ALS tree point clouds when they were not recognizable as a tree. This concerns only five trees, which had between 11 and 247 points. We can add this information to the manuscript.
  
  Citation: https://doi.org/10.5194/essd-2022-39-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Hannah Weiser on behalf of the Authors (20 Apr 2022)

EF by Natascha Töpfer (02 May 2022) Manuscript Author's response Author's tracked changes

ED: Referee Nomination & Report Request started (11 May 2022) by Sibylle K. Hassler

RR by Louise Terryn (13 May 2022)

RR by Anonymous Referee #2 (18 May 2022)

ED: Publish subject to minor revisions (review by editor) (02 Jun 2022) by Sibylle K. Hassler

AR by Hannah Weiser on behalf of the Authors (10 Jun 2022) Author's response Author's tracked changes Manuscript

ED: Publish as is (13 Jun 2022) by Sibylle K. Hassler

AR by Hannah Weiser on behalf of the Authors (14 Jun 2022) Author's response Manuscript

Download

Article (10872 KB)
Full-text XML

Short summary

3D point clouds, acquired by laser scanning, allow us to retrieve information about forest structure and individual tree properties. We conducted airborne, UAV-borne and terrestrial laser scanning in German mixed forests, resulting in overlapping point clouds with different characteristics. From these, we generated a comprehensive database of individual tree point clouds and corresponding tree metrics. Our dataset may serve as a benchmark dataset for algorithms in forestry research.