Compressions¶

One of the issues with LIDAR data is that there is a lot of it. To deal with data volumes, the Point Cloud extension allows schemas to declare their preferred compression method in the <pc:metadata> block of the schema document. In the example schema, we declared our compression as follows:

<pc:metadata>
  <Metadata name="compression">dimensional</Metadata>
</pc:metadata>

There are currently three supported compressions:

• None, which stores points and patches as byte arrays using the type and formats described in the schema document.
• Dimensional, which stores points the same as “none” but stores patches as collections of dimensional data arrays, with an “appropriate” compression applied. Dimensional compression makes the most sense for smaller patch sizes, since small patches will tend to have more homogeneous dimensions.
• GHT or “GeoHash Tree”, which stores the points in a tree where each node stores the common values shared by all nodes below. For larger patch sizes, GHT should provide effective compression and performance for patch-wise operations.

If no compression is declared in <pc:metadata>, then a compression of “none” is assumed.

{"pcid":1,"pts":[
      [-126.99,45.01,1,0],[-126.98,45.02,2,0],[-126.97,45.03,3,0],
      [-126.96,45.04,4,0],[-126.95,45.05,5,0],[-126.94,45.06,6,0]
     ]}

{"pcid":1,"dims":[
      [-126.99,-126.98,-126.97,-126.96,-126.95,-126.94],
      [45.01,45.02,45.03,45.04,45.05,45.06],
      [1,2,3,4,5,6],
      [0,0,0,0,0,0]
     ]}