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@Jean-Romain Jean-Romain released this 26 Sep 12:48
· 241 commits to master since this release
v3.2.0
8f9e7b9

lidR v3.2.0 (Release date: 2021-09-26)

ANNOUCEMENT

rgdal and rgeos will be retired on Jan 1st 2024. raster and sp are based on rgdal/rgeos. lidR is based on raster and sp because it was created before sf, terra and stars. This means that sooner or later lidR will run into trouble (actually it has already started to be the case). So, it is time to fully embrace sf, terra/stars and to leave sp and raster. This will require an in-depth rebase of lidR. We have started the work and we plan to release lidR 4.0.0 that will no longer have any internal code that uses sp and raster. This version already no longer uses rgdal. We hope make these changes with minimal breakage in backward compatibility by maintaining the conversion to sp/raster for functions from v < 4.0.0, but some backward incompatibilities will necessarily arise. In particular, LAS will no longer inherit the sp::Spatial class and will no longer contain a sp::CRS but a sf::crs and LAScatalog will no longer be sp::SpatialPolygonDataFrame. Our plan is (hopefully) to rebase lidR in such a way that nobody will notice the changes expect users who dig a little deeper into the objects.

CHANGES

  1. hexbin_metrics() was an unused function and has been removed from lidR. It can be retrieved in lidRplugins

  2. Functions using the former namespace such as lassomething() that were renamed into verb_noun() in version 3.0.0 now throw a warning. In v3.0.0 they were still usable for backward compatibility but not documented. In v3.1.0 they printed a message saying to move on to the new namespace. Now in 3.2.0 they throw a formal warning saying to move on to the new namespace. They will throw an error in the next version.

NEW FEATURES

  1. classify_poi(). New function capable of attributing a class of choice to any points that meet a logical criterion (e.g. Z > 2) and/or a spatial criterion (e.g. inside a polygon). For example, the following will attribute the class "high vegetation" to each non-ground point that is not in the lake polygon.

    las <- classify_poi(las, LASHIGHVEGETATION, poi = ~Classification != 2, roi = lakes, inverse = TRUE)

  2. LAScatalog

    • New function rbind() for LAScatalog.
    • New functions projection()<- and crs()<- for LAScatalog. Those two functions were already working in previous versions but in absence of dedicated functions in lidR the functions that were actually called were raster::projection() and raster::crs() thanks to class inheritance. However the functions from raster do not support crs from sf or numbers as input. Adding a dedicated function in lidR brings consistency between LAS and LAScatalog (#405): 
      projection(ctg) <- st_crs(3625)
# or
projection(ctg) <- 3625
    • The processing engine has a new option to drop some chunks under ctg@chunk_options$drop. This generates regions that won't be processed. This option accepts a vector of chunk IDs that are dropped and is thus versatile, but its main role is to allow restarting a computation that failed. We consequently introduced the function opt_restart(). Let's assume that the computation failed after few hours at 80% in chunk number 800. Users get a partial output for the first 799 chunks but chunk 800 has a problem that can be solved. It is now possible to restart at 800 and get the second part of the output without restarting from 0: 
      output <-    catlog_apply(ctg, myfun, param)
# Failed after 80%, 'output' contains a partial output
# Fix the trouble

opt_restart(ctg) <- 800
output2 <- catlog_apply(ctg, myfun, param)

# Merge 'output' and 'output2'
    • The vignette LAScatalog engine and the manual LAScatalog-class were updated to reflect these features

  3. LASheader

    • The function LASheader() can now create a LASheader object from a data.frame. This addition aims to facilitate the creation of valid LAS objects from external data.
    • las_check() can now check a standalone LASheader 
      las_check(las@header)

  4. LAS

    • The function LAS now automatically fixes the font case of attributes names to match the naming convention of the rlas package. This simplifies the creation of compatible objects from non-LAS file sources. 
      data <- data.frame(x = runif(10), Y = runif(10), z = runif(10), pointsourceid = 1:10)
las <- LAS(data)
#> Attribute 'x' renamed 'X' to match with default attribute names.
#> Attribute 'z' renamed 'Z' to match with default attribute names.
#> Attribute 'pointsourceid' renamed 'PointSourceID' to match with default attribute names.
las$PointSourceID
#> [1]  1  2  3  4  5  6  7  8  9 10

  5. Full waveform: with most recent versions of the rlas package, full waveform (FWF) can be read and lidR provides some compatible functions. However the support of FWF is still a work in progress in the rlas package. How it is read, interpreted and represented in R may change. Consequently, tools provided by lidR may also change until the support of FWF becomes mature and stable in rlas.

    • New function interpret_waveform() to transform waveform into a regular point cloud
    • New supported flag W for parameter select in readLAS()
    • New automatic colouring scheme for attribute Amplitude in plot(las, color = "Amplitude") that aims to be used with FWF.

  6. catalog_intersect() now supports sf, sfc, Extent and bbox objects

  7. Concave hull: lidR now includes its own C++ code to compute concave hulls using concaveman-cpp.

    • New function concaveman() to compute concave hulls
    • delineate_crowns() using concave hulls is now between 10 to 50 times faster. 
      LASfile <- system.file("extdata", "MixedConifer.laz", package="lidR")
las = readLAS(LASfile, select = "xyz0")
concave_hulls <- delineate_crowns(las, "concave")
# Before v3.2.0: 7.1 seconds
# From v3.2.0  : 0.2 seconds
    • grid_terrain() with is_concave = TRUE should also be faster.

  8. New function catalog_boundary() to compute the actual shape of the point-cloud

  9. In find_trees() and segment_trees() the bitmerge strategy to generate robust unique IDs was not actually a valid and robust procedure. It had the advantage of generating integers but was not 100% unique. The probability to generate duplicates was low but we changed the strategy to use a true bit-merging procedure anyway. The new IDs thus generated are weird decimal number such as 5.001120e-310 but are guaranteed to be unique. The documentation has been updated to explain the method.

  10. New algorithm random_per_voxel() for decimate_points that keep n points per voxel (#406).

  11. 3D rendering:

    • plot() gains a new parameter voxels = TRUE or voxels = 0.5 to render a point cloud with voxels. This is useful to render the output of voxelize_points() or voxel_metrics(), for example. This is computationally demanding and takes time so it should be reserved to small scenes with 30,000 or 40,000 voxels maximum, but note that there is no hard coded limit. 
      vm <- voxel_metrics(las, ~list(N = length(Z)), 8)
plot(vm, color = "V1", voxels = T)
    • specular reflections are now disable in plot().

  12. New function plot_metrics() that wraps several other functions into one seamless function that extracts ground inventory plots, computes metrics for each plot and returns a ready to use data.frame for statistical modelling.

  13. New function point_eigenvalue() that is equivalent to point_metrics(las, .stdshapemetrics) but specialized, optimized and parallelized to be 10 times faster.

  14. grid_metrics() gains a new parameters by_echo allowing users to compute the metrics for different types of echos independently. It is now possible to map e.g. mean(Intensity) for first returns only + multiple return only + single return only. All metrics are computed in a single run and returned in a raster stack.

  15. merge_spatial() supports sfc

ENHANCEMENTS

  1. grid_density() is 10 times faster

FIXES

  1. Fix: quantize() now preserves NaN values instead of converting them into minus infinity (#460).
  2. Fix: stdmetrics_i() now fails with an informative message when the sum of intensities is greater than .Machine$integer.max and becomes double (#463)
  3. Fix: find_localmaxima() respects the filter argument. It was previously not considered.

MISCELLANEOUS

  1. Remove crayon and hexbin dependencies
  2. Packages RCSF and rgeos are now only suggested and they are consequently no longer installed by default with lidR
  3. Change: rgdal will be retired in 2024. Code using rgdal internally has been removed. In many cases this will not change anything for users but in some cases it may fail when assigning an EPSG code to the LAS file. Also, old versions of rgdal built with old versions of gdal and proj are no longer supported (#466)
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