Esri has developed technology to optimize LAS format lidar. The format enables fast and efficient access to LAS structured lidar data and is well suited both to direct in desktop applications use as well as for archiving, storage, cloud based data distribution. Optimized LAS was built from the ground up with equal attention paid both to compression and the different modes of use.
Esri’s compression technology reduces file size significantly more than generic compressors can (e.g., gzip) because it was written specifically for LAS. Better compression results in reduced storage and bandwidth requirements.
The lidar point record data is preserved exactly. There is no loss of information so the full integrity of the data is maintained.
The optimized LAS data can be used directly without need to decompress it first. The ArcGIS 10.2.1 platform has been enhanced to support optimized LAS.
Efficient Data Access
Statistics and spatial indexing are added during the compression process. This makes the resulting files easier to use and the data is accessed more efficiently for both spatial and thematic queries. An option to sort point records to improve the I/O efficiency of queries on the optimized files is included.
You can use Esri LAS Optimization free of charge. ArcGIS is not required. This means any client can download an optimized LAS file, decompress it, and use the resulting LAS file in their application of choice. Clients with ArcGIS 10.2.1 currently get the added benefit of being able to use the files directly without the need to decompress. Esri will be providing an Open API to enable other software developers to directly read and write Optimized LAS.
How to Get Optimized
A free single standalone executable that handles both compression and decompression is available for anyone to download from Esri’s web site. It has both a graphical interface as well as support for command line execution. Free libraries that will enable software from other vendors to directly read and write zLAS are planned for release later in 2014.