This is the first stage that must be called in each pipeline. The stage does nothing and returns
nothing if it is not associated to another processing stage.
It only initializes the pipeline. reader_las() is the main function that dispatches into to other
functions. reader_las_coverage() processes the entire point cloud. reader_las_circles() and
reader_las_rectangles() read and process only some selected regions of interest. If the chosen
reader has no options i.e. using reader_las() it can be omitted.
Usage
reader_las(filter = "", ...)
reader_las_coverage(filter = "", ...)
reader_las_circles(xc, yc, r, filter = "", ...)
reader_las_rectangles(xmin, ymin, xmax, ymax, filter = "", ...)Arguments
- filter
the 'filter' argument allows filtering of the point-cloud to work with points of interest. The available filters are those from LASlib and can be found by running filter_usage. For a given stage when a filter is applied, only the points that meet the criteria are processes. The most common strings are "-keep_first", "-keep_class 2", "drop_z_below 2". For more details see filters.
- ...
passed to other readers
- xc, yc, r
numeric. Circle centres and radius or radii.
- xmin, ymin, xmax, ymax
numeric. Coordinates of the rectangles
Examples
f <- system.file("extdata", "Topography.las", package = "lasR")
pipeline <- reader_las() + rasterize(10, "zmax")
ans <- exec(pipeline, on = f)
# terra::plot(ans)
pipeline <- reader_las(filter = keep_z_above(1.3)) + rasterize(10, "zmean")
ans <- exec(pipeline, on = f)
# terra::plot(ans)
# read_las() with no option can be omitted
ans <- exec(rasterize(10, "zmax"), on = f)
# terra::plot(ans)
# Perform a query and apply the pipeline on a subset
pipeline = reader_las_circles(273500, 5274500, 20) + rasterize(2, "zmax")
ans <- exec(pipeline, on = f)
#> 1 files do not have a spatial index. Spatial indexing speeds up tile buffering and spatial queries drastically.
#> Files will be indexed on-the-fly. This will take some extra time now but will speed up everything later.
# terra::plot(ans)
# Perform a query and apply the pipeline on a subset with 1 output files per query
ofile = paste0(tempdir(), "/*_chm.tif")
pipeline = reader_las_circles(273500, 5274500, 20) + rasterize(2, "zmax", ofile = ofile)
ans <- exec(pipeline, on = f)
# terra::plot(ans)