1. lasR Etc.
Jacob Strunk
April 11, 2017

2. Why NOT Lidar In R? Slow Inefficient (memory footprint etc.)
Annoying / casual syntax
Weird OOP support (3+ versions)
Python, Java, C# have more capabilities
You WILL run into barriers if you use it long enough
You will likely come to hate (and love) R

3. Why Lidar In R? Great for exploratory analyses Easy, fun Lots of users
Large user support community – e.g. help forums
Simple to append to language
Lots of support for statistics
Simple programming paradigm (high level)
Easy to do research and visualization

4. Presentation 2 Sections R, Rstudio, Git, GitHub toolchain
lidR and lasR – working with lidar in R

5. R Packages
“… the fundamental unit of shareable code is the package. A package bundles together code, data, documentation, and tests, and is easy to share with others.”

6. Why build packages? Portable Testable Extensible
Facilitates collaboration
Reduces redundancy
Encourages more work in your topic of interest
People are freed up to do other cool things (and hopefully create packages)
Once you start (using RStudio) you will never go back…

7. Functional programming
R packages very suited to functional programming:
hello <- function() {
print("Hello, world!") }
Some of us may be more used to this style: …
#print hello world

8. R Packages Rstudio – So easy Not in Rstudio – tedious
Rstudio has a really convenient toolchain that eliminates most of the frustration of package building

9. Rstudio, Very Convenient IDE for R
Package build / test support
R syntax highlighting, suggesting and code execution
ROxygen syntax highlighting, suggesting
R Manual Page previewing
RCPP support
Git support
RShiny support …

10. Step 1 Get / install all of the tools – default settings are fine R
Rtools
Rstudio
Miktex
GIT
Sign up for GIT account

11. Build an R package 4 1 2 3

12. Build Package
New package pre-populated with example function – just build it

13. Git

14. Git commit (first time)
Shift-click to select all items
commit

15. Git commit (add function)
Shift-click to select all items
commit

16. Git Push (to GitHub)
Will need to log in first time

17. Git History
Awesome
See old versions of scripts before you screwed them up…

18. Git branch history
Experiment
Merge in experiment

19. Roxygen maintain one set of code
No need to manage help files separately from code…

20. Roxygen: Auto-populate Help Files (Awesome)
Just paste template into header of code and the appropriate files are auto-created

21. lidR and lasR
Working with lidar in R

22. LidR Read/write las/laz files Read in a dem files
Process point data -> raster
Process point data -> sample plots
Visualize data
… other stuff
Iterate across files in a project

23. lidR limitations
Cannot tile on the fly – lidar data become processing tiles
Assumes footprints of DEM and LIDAR are the same
Cannot easily call external .exe file

24. lidR
Lots of functionality
A few serious limitations

25. lidR::plot()
plot(dat1,bg="white")

26. lidR::lasground()
> lasground(dat1,CellSize = 6,MaxDist = 9,InitDist = 0.1) > plot(dat1, color = "Classification",bg="white")

27. lidR::lasground()
Slow, but seems to work fine

28. lidR::lasground() – Stereo DSM points

29. lidR::catalog & lidR::catalog_apply
ct1=catalog(getwd()) f1=function(x){require(lidR);grid_metrics(readLAS(x), .stdmetrics)} res1=catalog_apply(ct1,f1, mc.cores = 7, combine = "rbind", varlist = "ct1")

30. lasR Very beta Very little functionality Re-tile on the fly!!
Work with fusion exes

31. lasR

32. lasR Read in las data Read in DEM files
Tile lidar project area on the fly
Create lidar processing project
Iterate across processing tiles (not lidar files)
Clip plot from lidar processing project

33. lasR::scan_dtm
Bounding boxes…

34. lasR::scan_las
NAIP 2015 DSM tiles

35. lasR::lasR_project Create processing tiles Subset area
Intersect with lidar files
Intersect with dtm files
Subset area

36. lasR::gridmetrics Create custom metrics in R
Send files to FUSION using system calls

37. lasR::forthcoming Clip plots using projects (deals with edges)
Metrics for plots
Other lidar & inventory steps

38. Thank you