This workflow compares a canopy height model (CHM) derived from airborne laser scanning (ALS) data and inventoried tree positions, and proposes a translation in plot position for better matching. It works with circular plots. The method is described in @Monnet2014. The workflow uses field and ALS data acquired in the forest of Lac des Rouges Truites. It is based on functions from packages `lidaRtRee` and `lidR`.
This workflow compares a canopy height model (CHM) derived from airborne laser scanning (ALS) data with tree positions inventoried in the field, and then proposes a translation in plot position for better matching. The method is described in @Monnet2014. Here it is exemplified with circular plots, but it can be applied to any shape of field plots. The workflow is based on functions from packages `lidaRtRee` and `lidR`. Example data were acquired in the forest of Lac des Rouges Truites (Jura, France).
Licence: CC BY
Licence: CC BY / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/coregistration.Rmd)
Airborne laser scanning data on the study area is part of a campaign acquired in 2016 with an airborne RIEGL LMS Q680i sensor. Acquisition was funded by the Région Franche-Comté.
Airborne laser scanning data on the study area is part of a campaign acquired in 2016 with an airborne RIEGL LMS Q680i sensor. Acquisition was funded by the Région Franche-Comté.
ALS data over the plots is provided as a list of LAS objects in rda file.
ALS data over the plots is provided as a list of LAS objects in `rda` file.
```{r las, include = TRUE}
```{r las, include = TRUE}
# load point cloud over reference plots (list of las objects)
# load point cloud over reference plots (list of las objects)