The availability and use of LIDAR continues to grow and has become a vital source of spatial information. More and more organizations are collecting LIDAR, processing it, and sharing it. Like vector and raster GIS data, it is becoming an important piece of public information, and interoperability is a key concern.
Fortunately, there has been a standard format for some time, the “LAS” format, and an open source library, “libLAS”, that can read and write the format. Rather than write their own format support, most vendors have simply used libLAS, and LAS has become an industry standard.
Story over, right? Thanks to open source, the usual decade of broken interoperability in a new data field has been avoided and LIDAR users can get down to the important business of working with their data.
Not so fast!
LAS format is not without its drawbacks:
- While it is a binary format and does not waste any space unnecessarily, neither does it apply any compression to the data it stores. That’s not good for archival use.
- Also, LAS stores points in scan order, so accessing any particular chunk of points involves reading the whole file. That’s not good for random access.
Clearly there is a little more work to be done. Can LAS be improved? In fact, it already has been:
- An open source compression library LASzip can apply 20:1 lossless compression to LAS files, making them great for archival purposes.
- Other LAS users have experimented with re-ordering points in a LAS or LASzip file to allow random access to internal chunks of the LIDAR point cloud.
Basically, making LAS smaller and faster is not rocket science, and if the work were incorporated into libLAS then the whole LIDAR community could leverage it together, and the user community would only have one file type to interchange.
Work together or build your own?
Now, if you were a leading software vendor with a dominant position in the vector data space, a passable position in the raster space and a weak position in the LIDAR space, how would you approach LIDAR support. Would you:
Approach the libLAS community and indicate your interest in collaborating to improve LAS for better compression and random access?
Build your own proprietary compression and random access routine, release it in binary only form, and avoid supporting the existing open source approaches?
If you chose #2, congratulations, you own a huge chunk of southern California agricultural land outside Redlands.
Rather than avoiding a lengthy LIDAR format war, we are now entering one. In some respects, this will be healthy: the open LAS community now has to come up to feature parity faster than it might otherwise. But in most ways, it’s unhealthy: users will have data interchange issues, they’ll have to understand and install format translation software, and add extra steps to their processing chains. The only people who really win here are the those in the format translation business.
What can be done?
Boundless will work with the libLAS and PDAL communities on bringing random access and compression into the open source world. We’ll encourage our customers to keep investing in improving the software commons. And we’ll keep on murmuring quietly to ourselves, as we walk down the street: open standards, open data, open source. There’s no better way.
OpenGeo Suite 4.0 supports many LIDAR formats, including LAS, LASzip, Oracle Pointcloud, PostgreSQL Pointcloud and more.