It was wonderful to reconnect with old friends and colleagues, and just as exciting to make new ones.

A huge thank you to the organizers — what a well-organized and energizing conference!

#SilviLaser2025 #RemoteSensing #Forestry #LiDAR

@dr-spoon.bsky.social you're on fire!!!

We're also working to keep this information up to date on this website:

📍 Canada's Forest LiDAR Coverage➡️ ptompalski.github.io/CanadaForest...

#ForestScience #LiDAR #SustainableForestry #RemoteSensing #ForestManagement #CanadaForests

📄 White et al. 2025 – Enhanced Forest Inventories in Canada: Implementation, Status, and Research Needs

🔗 Read here: cdnsciencepub.com/doi/10.1139/...

If you'd like to learn more or give it a try, you can find it here: [ptompalski.github.io/lidRmetrics/](ptompalski.github.io/lidRmetrics/ "https://ptompalski.github.io/lidRmetrics/")

#Lidar #Forestry #RemoteSensing #RStats

For convenience, `lidRmetrics` also includes "metric sets"—predefined combinations of multiple metric groups that allow for comprehensive analysis with a single function call.

The package organizes metrics into specific functions:

- `metrics_basic()` – general point cloud statistics
- `metrics_percentiles()` – height percentiles
- `metrics_percabove()` & `metrics_dispersion()` – assess vertical structure
- `metrics_echo()` & `metrics_echo2()` – return type proportions

I was surprised it worked!

So far easier to use, but lubridate can do a lot more

not a mac user myself, but you could try asking JR directly (i.e. submitting an issue on github). JR usually replies quite quickly!

For me some of the not-very-helpful error messages (especially for new users).
good example would be "object of type closure is not subsettable"... 🤯

option 1 for me as well. Fits well with other elements of the workflow.