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This workflow implements in `R` a tree segmentation on Airborne Laser Scanning (lidar remote sensing) data. It is based on functions from R packages `lidaRtRee` and `lidR`, and it includes the following steps:
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+ treetop detection,
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+ crown segmentation,
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+ accuracy assessment with field inventory,
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+ species classification
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The following files are provided:
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* [Rmarkdown source](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/tree.detection.Rmd),
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* [html output](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/raw/master/export/tree.detection.html?inline=false),
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* [pdf output](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/export/tree.detection.pdf)
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* datasets and a [bibliography file](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/bib/bibliography.bib) required to run the source code are also available on the repository.
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Changelog
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* Jan 26, 2021: updated to comply with package `lidR` 3.1.0 and `lidaRtRee` 3.0.0
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* Oct 12, 2020: checked compatibility with package `lidR` 3.0.3
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* Jan 17, 2020: checked compatibility with package `lidR` 2.2
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* Dec 6, 2019: `cloudMetrics` function used for point cloud stats in segments
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* Feb 4, 2019: updated for compatibilty with packages `lidR` 2.0.0 and `lidaRtRee` 2.0.0
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* May 18, 2018: first release</sup> |
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