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Esri and rapidlasso develop joint LiDAR compressor

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PRESS RELEASE (April Fools’ Day)
April 1, 2014
rapidlasso GmbH, Gilching, Germany

In a positive spin of events, Esri and rapidlasso are announcing to join forces and together develop a LiDAR compressor for LAS 1.4 in open source avoiding unnecessary format fragmentation. Their new “LASeasy” tool not only compresses but also optimizes LAS files for efficient area-of-interest queries. LASeasy extends the popular LASzip compressor to handle LAS 1.4 content and includes the tiny spatial indexing *.lax files into the *.laz file via Extended Variable Length Records (EVLRs). More importantly, LASeasy provides new features such as optional spatial sorting and precomputed statistics – motivated by Esri – that allow exploiting LiDAR in the cloud.

To minimize disruption in existing workflows, their joint effort uses a clever strategy that capitalizes on the natural “break” in the ASPRS LAS format from version 1.3 to 1.4. LAS files compressed by Esri will automatically be upgraded to the new point types introduced with LAS 1.4 (and be losslessly downgraded on decompression). LiDAR software already supporting LAZ will instantly be able to read all LiDAR produced by Esri with the same DLL update that will be needed to access future compressed LAS 1.4 content – achieving maximum compatibility with minimal disruption for users of ArcGIS, LASzip, and the larger LiDAR community,

Martin Isenburg, chief scientist and CEO of rapidlasso GmbH, was all smiles during the announement. “Yes, I had some hard feelings when hearing about their ‘LAZ clone‘ because our presumed open dialogue suddenly felt so very one-sided,” he said, “So over Martin Luther King weekend I proposed this LAS 1.4 trick as a joint development quoting MLK’s ‘We must accept finite disappointment, but never lose infinite hope’ and that seemed to resonate with them.” Speaking on the condition of anonymity an executive of Esri’s management added “For a global geospatial player like us it can happen that we do something ‘evil-by-accident’. We occasionally need someone like Martin to poke some good-natured fun at Esri to remind us of our values.”

LASeasy optimizes LAS files by reordering points along an adaptive space-filling curve for efficient LiDAR queries in the cloud. To access the corner of the LiDAR tile only the points shown in blue need to be loaded and decompressed.

LASeasy optimizes LAS files by reordering points along an adaptive space-filling curve for efficient LiDAR queries in the cloud. To access the corner of the LiDAR tile only the points shown in blue need to be loaded and decompressed.



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