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efficient tools for LiDAR processing

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This is a fork of the official LAStools project that only keeps the library section of LAStools (that is to say LASlib and LASzip). This fork is design to be lightweight and self-contained for people who are only interested in the libraries LASlib and LASzip.

If you are interested in the full LAStools software, please refer to the official LAStools project.

LASlib/LASzip

LASlib (with LASzip) is a C++ programming API for reading / writing LIDAR data stored in standard LAS or in compressed LAZ format (1.0 - 1.3). Both libraries - LASlib with LASzip - are released together under the terms of the GNU Lesser General Public Licence also known as LGPL. See LICENSE.txt for details.

Internally LASlib includes the stand-alone LASzip compression library that provides lossless compression for LAS data. This allows you to read or write *.laz (LASzip compressed *.las files) directly like you would an uncompressed .las file using the same LASreader and LASwriter classes.

LASlib (with LASzip) is easy-to-use, light-weight, yet extremely fast.

Compilation

This fork uses CMake to simplify the compilation process. To compile LASlib/LASzip, use the following set of commands:

$ mkdir build
$ cd build
$ cmake ..
$ make

If you wish to install the library to your operating system's dedicated directories, do:

# make install

Example

Here is how simple the programming API is:

#include "lasreader.hpp"
#include "laswriter.hpp"

int main(int argc, char *argv[])
{
  LASreadOpener lasreadopener;
  lasreadopener.set_file_name("original.las");
  LASreader* lasreader = lasreadopener.open();

  LASwriteOpener laswriteopener;
  laswriteopener.set_file_name("compressed.laz");
  LASwriter* laswriter = laswriteopener.open(&lasreader->header);

  while (lasreader->read_point()) laswriter->write_point(&lasreader->point);

  laswriter->close();
  delete laswriter;

  lasreader->close();
  delete lasreader;

  return 0;
}

Latest update

This fork was updated from the original repository for the last time on the 10th August 2017.


(c) 2007-2015 martin.isenburg@rapidlasso.com

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efficient tools for LiDAR processing

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