I'm trying to work with the data returned by the greyhound read query. It looks like I'm losing precision somewhere along the line. Having written my own code I had assumed my struggles were a bug of mine. However I just discovered your own sample python code ( https://github.com/hobu/greyhound/pull/35/files ) that appears to have the same issue. Playing with the settings in this file, I run it to produce this query:
http://[myipaddress]:8080/resource/[MyDemoResource]/read?bounds=[-13634057.2874,4552379.08325,-13634052.2874,4552384.08325]&compress=false
It returns 30813 points from a 5 meter cube of my data. The las file that's generated looks like this:
You can probably see 30-4 points within the bounds of this data in this image above. When I analyze the data itself, there are really only 6 unique values in each of the X, and Y coordinates. In other words, each point visible in this image is actually about 880 superimposed vertices.
The part that I don't understand is that when I aim Potree at this same area, I see the full point density and it looks nothing like this. It's filled in, and almost solid in appearance until you really zoom in on it.
For what it's worth, this is the point breakdown per depth level (I only have data in 11-21):
11:1,12:2,13:15, 14:61, 15: 255, 16:966, 17:3534, 18:10399, 19:13031, 20:2514, 21:35
My schema:
{"baseDepth":7,"bounds":[-13635560,4545640,-6040,-13623480,4557720,6040],"boundsConforming":[-13635553.321355114,4546474.442458361,-346.13140000000004,-13623524.425497472,4556869.877397481,309.4769],"numPoints":1185748768,"offset":[-13629520,4551680,0],"reprojection":{"in":"","out":"EPSG:3857"},"scale":0.001,"schema":[{"name":"X","size":4,"type":"signed"},{"name":"Y","size":4,"type":"signed"},{"name":"Z","size":4,"type":"signed"},{"name":"Intensity","size":2,"type":"unsigned"},{"name":"ReturnNumber","size":1,"type":"unsigned"},
I feel like I'm missing something fundamental in trying to interpret the returned data. Do you have any ideas what I might be missing?
Thank you.