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3 changes: 3 additions & 0 deletions topics/climate/tutorials/3dtrees/faqs/index.md
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---
layout: faq-page
---
42 changes: 42 additions & 0 deletions topics/climate/tutorials/3dtrees/tutorial.bib
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# This is the bibliography file for your tutorial.
#
# To add bibliography (bibtex) entries here, follow these steps:
# 1) Find the DOI for the article you want to cite
# 2) Go to https://doi2bib.org and fill in the DOI
# 3) Copy the resulting bibtex entry into this file
#
# To cite the example below, in your tutorial.md file
# use {% cite Batut2018 %}
#
# If you want to cite an online resourse (website etc)
# you can use the 'online' format (see below)
#
# You can remove the examples below

@article{Batut2018,
doi = {10.1016/j.cels.2018.05.012},
url = {https://doi.org/10.1016/j.cels.2018.05.012},
year = {2018},
month = jun,
publisher = {Elsevier {BV}},
volume = {6},
number = {6},
pages = {752--758.e1},
author = {B{\'{e}}r{\'{e}}nice Batut and Saskia Hiltemann and Andrea Bagnacani and Dannon Baker and Vivek Bhardwaj and
Clemens Blank and Anthony Bretaudeau and Loraine Brillet-Gu{\'{e}}guen and Martin {\v{C}}ech and John Chilton
and Dave Clements and Olivia Doppelt-Azeroual and Anika Erxleben and Mallory Ann Freeberg and Simon Gladman and
Youri Hoogstrate and Hans-Rudolf Hotz and Torsten Houwaart and Pratik Jagtap and Delphine Larivi{\`{e}}re and
Gildas Le Corguill{\'{e}} and Thomas Manke and Fabien Mareuil and Fidel Ram{\'{i}}rez and Devon Ryan and
Florian Christoph Sigloch and Nicola Soranzo and Joachim Wolff and Pavankumar Videm and Markus Wolfien and
Aisanjiang Wubuli and Dilmurat Yusuf and James Taylor and Rolf Backofen and Anton Nekrutenko and Bj\"{o}rn Gr\"{u}ning},
title = {Community-Driven Data Analysis Training for Biology},
journal = {Cell Systems}
}

@online{gtn-website,
author = {GTN community},
title = {GTN Training Materials: Collection of tutorials developed and maintained by the worldwide Galaxy community},
url = {https://training.galaxyproject.org},
urldate = {2021-03-24}
}
277 changes: 277 additions & 0 deletions topics/climate/tutorials/3dtrees/tutorial.md
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---
layout: tutorial_hands_on

title: '3Dtrees: Point cloud processing'
zenodo_link: ''
questions:
- What are LAS data ?
- How can I process and visualise point cloud data ?
objectives:
- Learn to do point cloud processing
-
time_estimation: 3H
key_points:
- The take-home messages
- They will appear at the end of the tutorial
contributors:
autorship:
- kgerb
- Marie59

---

TO DO
=> Add description general of what does the workflow and how it can be usefull (small intro of 3Dtrees here (in a more details box))

=> Introduce the Data used and for what (small intro for data terra in a more details box)


> <agenda-title></agenda-title>
>
> In this tutorial, we will cover:
>
> 1. TOC
> {:toc}
>
{: .agenda}

# Title for your first section

Intro on the forest and its structure ? of IGN data.

## Get data

> <hands-on-title> Data Upload </hands-on-title>
>
> 1. Create a new history for this tutorial
> 2. Import the files from [Recherche Data Gouv](https://entrepot.recherche.data.gouv.fr/) more specifically the Data register underthis [DOI](https://doi.org/10.15454/DMYWPB)
> 3. On the left pannel go on **Upload** select **{% icon pref-cloud %} Choose Remote Files**
>
> ![Image of how the upload pannel looks like](../images/3dtrees/upload_pannel.png)
>
> 4. In the search bar write down "recherche", you should see the repo named **Recherche Data Gouv** appear, click on it.
> 5. In the search bar write down "pic", you should see the repo named **Données lidar acquises par drone au pied du Pic St Loup (34)** appear, click on it.
>
> ![Image of how the remote repo to select](../images/3dtrees/rdg_repo.png)
>
> 6. You should see 4 datasets appear, select them all and then in the bottom right click on **start**
>
> ![Image of how the data to upload](../images/3dtrees/data_upload.png)
>
> 7. The 4 datasets should appear into your history (in yellow when uploading) in green
>
> ![Image of how the data to uploading in the history](../images/3dtrees/data_inhistory.png)
>
> > <tip-title>las format</tip-title>
> > Check that the datatype is **las format**
> >
> > {% snippet faqs/galaxy/datasets_change_datatype.md datatype="datatypes" %}
> {: .tip}
>
> 8. Build a collection
>
> {% snippet faqs/galaxy/collections_autobuild_list.md %}
{: .hands_on}


# Standardization

***TODO***: *Consider adding a detail box to expand the theory and add some info here*

> <details-title> More details about the theory </details-title>
>
> But to describe more details, it is possible to use the detail boxes which are expandable
>
{: .details}


## 3DTrees: LAS/LAZ Standardization

> <hands-on-title> Standardize individual files in collection </hands-on-title>
>
> 1. {% tool [3DTrees: LAS/LAZ Standardization](toolshed.g2.bx.psu.edu/repos/bgruening/3dtrees_standardization/3dtrees_standardization/1.1.0+galaxy0) %} with the following parameters:
> - *"Mode"*: `Single File Standardization`
> - {% icon param-collection %} *"Point Cloud File"*: `output` (Input dataset collection)
>
>
> > <comment-title> short description </comment-title>
> >
> > A comment about the tool or something else. This box can also be in the main text
> {: .comment}
>
{: .hands_on}

***TODO***: *Consider adding a question to test the learners understanding of the previous exercise*

> <question-title></question-title>
>
> 1. Question1?
> 2. Question2?
>
> > <solution-title></solution-title>
> >
> > 1. Answer for question1
> > 2. Answer for question2
> >
> {: .solution}
>
{: .question}

In the same time you can do this 2nd step even if 1st one has not finished yet.

> <hands-on-title> 3DTrees Collection Check </hands-on-title>
>
> Collection-level validation and consistency check using standardization tool in collection mode
>
> 1. {% tool [3DTrees: LAS/LAZ Standardization](toolshed.g2.bx.psu.edu/repos/bgruening/3dtrees_standardization/3dtrees_standardization/1.1.0+galaxy0) %} with the following parameters:
> - *"Mode"*: `Collection Validation`
> - {% icon param-collection %} *"Point Cloud Collection"*: `output` (Input dataset collection)
>
> > <comment-title> short description </comment-title>
> >
> > A comment about the tool or something else. This box can also be in the main text
> {: .comment}
>
{: .hands_on}

You should have 4 new objects in your history running yellow soon turning green.

![Standardization running](../images/3dtrees/standard_run.png)

# Thumbnail generation

> <hands-on-title> 3D Trees Overview Generator </hands-on-title>
>
> Generate overview images from standardized point clouds
>
> 1. {% tool [3Dtrees: Overviews](toolshed.g2.bx.psu.edu/repos/bgruening/3dtrees_overviews/3dtrees_overviews/1.2.0+galaxy1) %} with the following parameters:
> - {% icon param-file %} *"Point Cloud Collection"*: `pc_standardized` (output of **3DTrees: LAS/LAZ Standardization** {% icon tool %})
>
> You should see to types of section images in your history (4 images in total have been generated)
> > <comment-title> short description </comment-title>
> >
> > A comment about the tool or something else. This box can also be in the main text
> {: .comment}
>
{: .hands_on}

![Example of the overview image on the section ns](../images/3dtrees/sectionns.png)

# Instance Segmentation by SegmentAnyTree

> <hands-on-title> 3DTrees: SmartTile </hands-on-title>
>
> 1. {% tool [3DTrees: SmartTile](toolshed.g2.bx.psu.edu/repos/bgruening/3dtrees_smart_tile/3dtrees_smart_tile/2.0.1+galaxy0) %} with the following parameters:
> - *"Operation"*: `Tile (COPC normalize + tile + subsample)`
> - {% icon param-file %} *"Input point clouds (LAZ/LAS)"*: `pc_standardized` (output of **3DTrees: LAS/LAZ Standardization** {% icon tool %})
>
> 5 new objects should appear in your history.
> > <comment-title> short description </comment-title>
> >
> > A comment about the tool or something else. This box can also be in the main text
> {: .comment}
>
{: .hands_on}

***TODO***: *Consider adding a question to test the learners understanding of the previous exercise*

> <question-title></question-title>
>
> 1. Question1?
> 2. Question2?
>
> > <solution-title></solution-title>
> >
> > 1. Answer for question1
> > 2. Answer for question2
> >
> {: .solution}
>
{: .question}

> <hands-on-title> 3Dtrees: SegmentAnyTree </hands-on-title>
>
> Deep learning tree segmentation
>
> 1. {% tool [3Dtrees: SegmentAnyTree](toolshed.g2.bx.psu.edu/repos/bgruening/3dtrees_segmentanytree/3dtrees_segmentanytree/1.2.2+galaxy0) %} with the following parameters:
> - {% icon param-file %} *"Input Dataset"*: `output_subsampled_res2` (output of **3DTrees: SmartTile** {% icon tool %})
> - *"Predicted instance dimension name"*: `PredInstance`
> - *"Predicted semantic dimension name"*: `PredSemantic`
>
> Your tool should look like that before running. It can take a few minutes to run.
> ![Image of the inputs within this tool](../images/3dtrees/smartile.png)
>
> > <comment-title> short description </comment-title>
> >
> > A comment about the tool or something else. This box can also be in the main text
> {: .comment}
>
{: .hands_on}


> <hands-on-title> 3DTrees: SmartTile </hands-on-title>
>
> 1. {% tool [3DTrees: SmartTile](toolshed.g2.bx.psu.edu/repos/bgruening/3dtrees_smart_tile/3dtrees_smart_tile/2.0.1+galaxy0) %} with the following parameters:
> - *"Operation"*: `Filter (remove overlap-only instances)`
> - {% icon param-file %} *"Segmented tiles (LAZ/LAS)"*: `output` (output of **3Dtrees: SegmentAnyTree** {% icon tool %})
> - {% icon param-file %} *"Tile layout JSON (tile_bounds_tindex.json)"*: `output_tile_bounds_json` (output of **3DTrees: SmartTile** {% icon tool %})
> - *"Border zone width"*: `Derive from tile layout JSON (recommended)`
> - *"Small cluster reassignment"*: `Enabled`
> - *"After filtering"*: `Also remap filtered dimensions to another collection`
> - *"Remap target files"*: `Originals and subsampled targets`
> - {% icon param-file %} *"Original files (LAZ/LAS)"*: `output_original_copc` (output of **3DTrees: SmartTile** {% icon tool %})
> - {% icon param-file %} *"Subsampled target files (LAZ/LAS)"*: `output_subsample_res1` (output of **3DTrees: SmartTile** {% icon tool %})
> - *"Also write one merged output (LAZ)"*: `Yes`
> - *"Enrich merged output with original attributes"*: `Yes`
> - {% icon param-file %} *"Standardization summary (optional)"*: `collection_summary` (output of **3DTrees: LAS/LAZ Standardization** {% icon tool %})
>
>
> > <comment-title> See exactly how the tols is filled in </comment-title>
> >
> > ![Image of how to fill in the tool form step 1](../images/3dtrees/form1.png)
> > ![Image of how to fill in the tool form step 2](../images/3dtrees/form2.png)
> > ![Image of how to fill in the tool form step 3](../images/3dtrees/form3.png)
> {: .comment}
>
{: .hands_on}

# Point cloud visualization by Potree

> <hands-on-title> 3Dtrees: Potree Converter </hands-on-title>
>
> Convert segmented collection to Potree octree format
>
> 1. {% tool [3Dtrees: Potree Converter](toolshed.g2.bx.psu.edu/repos/bgruening/3dtrees_potree/3dtrees_potree/1.0.2+galaxy0) %} with the following parameters:
> - {% icon param-file %} *"Point Cloud Files"*: `output_merged_with_originals` (output of **3DTrees: SmartTile** {% icon tool %})
>
> ***TODO***: *Check parameter descriptions*
>
> ***TODO***: *Consider adding a comment or tip box*
>
> > <comment-title> short description </comment-title>
> >
> > A comment about the tool or something else. This box can also be in the main text
> {: .comment}
>
{: .hands_on}

***TODO***: *Consider adding a question to test the learners understanding of the previous exercise*

> <question-title></question-title>
>
> 1. Question1?
> 2. Question2?
>
> > <solution-title></solution-title>
> >
> > 1. Answer for question1
> > 2. Answer for question2
> >
> {: .solution}
>
{: .question}

# Conclusion

Sum up the tutorial and the key takeaways here. We encourage adding an overview image of the
pipeline used.
3 changes: 3 additions & 0 deletions topics/climate/tutorials/3dtrees/workflows/index.md
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---
layout: workflow-list
---
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