Interesting. I came across this paper detailing the design of
opentopography.org's lidar system, and they indicate they are doing
something akin to load the LAS data in, and then running a spatial
index (I'm too early in this game to know the difference between what
they are describing and how the GIST index works):
http://www.springerlink.com/content/x5q937840983un76/fulltext.pdf
Once I build an index for this 3-d data, setting aside the file size
issues, should the spatial querying be relatively efficient? If so,
how would I go about doing a cross-tile query?
Howard, I am interested in checking out your tools but I don't have
access to Oracle, just open source databases. Can I use postgresql to
utilize your algorithms?
Thanks!
--j
On Fri, Jun 24, 2011 at 12:39 PM, Shaun Langley shaunlang...@gmail.com wrote:
Hi Howard,
I think this is an excellent question! I'm actually in the process of
developing a manuscript that outlines the different methods for storage and
querying of spatial data such as LIDAR. In my situation, I'm leaning towards
using triggers to create dynamic views that would allow me to simultaneously
query all tables of a given type. I intent to explore a variety of different
storage types though... I would love to hear about what you decide to do!
Keep in touch!
Cheers,
Shaun
On Jun 24, 2011, at 2:46 PM, Jonathan Greenberg wrote:
Folks:
This topic I believe has been brought up before, but I thought I'd
send an email since I'm a bit of a noob with POSTGIS. We have a large
collection of Lidar points that I would like to perform spatial
querying on (e.g. give me all points within a certain bounding box).
The data (currently in LAS format, but easily loadable into the DB),
is tiled up into smaller subsets. The data is x,y,z,intensity (and
some other attributes that aren't so important) I have a few
questions:
1) Should I load ALL of the LAS files into one massive table for
querying (this is going to be a LOT of points).
2) If not, is there a trick where if I load up each LAS file into a
separate table (which would, in theory be preferable since I'd like to
do some testing before dealing with a database of this size), but
somehow when I do a spatial query, the query can span multiple tables
(e.g. say the query box is at the intersection of two adjacent tiles)?
Related: what is the most efficient way to do a spatial query that
effectively rasterizes this data, e.g. the min z value between x1
and x2, and y1 and y2, where x2-x1 and y2-y1 are the x and y pixel
sizes? I'm not talking about interpolation, I'm talking an exact
query.
Thanks!
--j
--
Jonathan A. Greenberg, PhD
Assistant Project Scientist
Center for Spatial Technologies and Remote Sensing (CSTARS)
Department of Land, Air and Water Resources
University of California, Davis
One Shields Avenue
Davis, CA 95616
Phone: 415-763-5476
AIM: jgrn307, MSN: jgrn...@hotmail.com, Gchat: jgrn307
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Shaun Langley
Graduate Student, PhD
Department of Geography
Michigan State University
Home: (517) 974-9346
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