Jason
-----Original Message-----
From: gdal-dev-boun...@lists.osgeo.org
[mailto:gdal-dev-boun...@lists.osgeo.org] On Behalf Of Christopher Barker
Sent: Saturday, June 19, 2010 5:45 PM
To: gdal-dev@lists.osgeo.org
Subject: Re: [gdal-dev] How to represent multi-dimensional array
Thanks to Michael, Joaquim, Ivan, and Jason.
I'll explore some of the tools and suggestions you made.
Michael Sumner wrote:
NetCDF will tend to store dimensions in
reverse order to the natural one, and I think GDAL reverses that - but
you can tell by the dimension and number of your bands, and the named
metadata on the GDAL bands.
yup -- I figured that out - it got better when we re-ordered to (t, z,
y, x).
NetCDF cannot store multi-attribute arrays (it will store several
same-size, same-metadata arrays for that purpose),
Actually, I think it can -- though maybe that's only for netcdf4 (based
on hdf5), but the conventions don't suggest you do that -- particularly
if different attributes are different data types.
Manifold reads in multiple rasters
Eonfusion will do its best to read the array in its natural state
R can read NetCDF natively or with GDAL (RNetCDF, ncdf, rgdal
We're not really looking for other tools at this point -- we are doing
visualization with IDV, which handles 4-d data in netcdf just fine. This
part is all about getting this data into Arc.
I may deal with it by figuring out what we really need to do in Arc, and
just exporting that part of the data -- we're writing these files with
Python anyway, so doing some pre-processing there won't be a big deal.
Joaquim Luis wrote:
Don't know if this is what you are looking for but if those netCDF files
are of a similar type that one can get from the poet site
(http://poet.jpl.nasa.gov/), Mirone has a tool called "Aquamoto" (a tool
original developed to show time stamps of a tsunami propagation models)
that loads those files and show their content interactively with the
help of a slider.
Not much help for this, but it's a cool tool, thanks for the link.
Jason Roberts wrote:
I have some experience trying to get ArcGIS to work well with time series
satellite imagery and 4D ocean models (e.g. HYCOM, ROMS).
Exactly our situation, here.
I am part of a working group initiated
by ESRI and led by an ESRI program manager (Nawajish Noman) that is trying,
in essence, to get the community of users who use both ArcGIS and netCDF to
develop some Python geoprocessing tools for ArcGIS that provide more
functionality than out-of-box tools already in ArcGIS.
cool -- do you have contact information for that project? Is there code
anywhere we can get at it?
1. The Make NetCDF Raster Layer tool can represent 3D netCDF variables as
multiband raster layers.
We'll give this a try. It may be what our GIS person is using already,
but I got a bit confused by the "Dimension Values parameter". We'll poke
at it some more.
The trick is your netCDF has to meet a bunch
of constraints for ArcGIS to recognize it. It has to have square cells.
bingo -- that was one of our key problems -- wait -- they have to be
"square" -- rectangular won't do? arrgg!
Anyway, the way we have it now the cells ar rectangular in meters, but
we un-projectee them to lat-long, so they are no longer simle
rectangular -- I think I may change this an output in meters, with the
projection info. But if it has to be square, we're kind of dea in the
water...
It
has adhere to the CF or COARDS conventions (I forget which versions)
that we do have.
2. Under contract to NOAA, Applied Science Associates built a couple of
tools that might be useful: the Environmental Data Connector (EDC) and
TimeSlider Extension. Download from
http://www.asascience.com/software/downloads/index.shtml, see other parts of
the website for more info. EDC was built to download multidimensional
OPeNDAP datasets into multiband rasters.
Hmm -- did know about those tools, but didn't realize that EDC was
OPenDAP based -- nice to know.
TimeSlider is a UI extension to
help with playback of time-series data.
That too -- by the way, I'm pretty sure the Coast Guard funded a bunhc
of that, for their Search and Rescue tools.
I think they can both work with
netCDFs directly, not just OPeNDAP.
That I didn't know -- we'll try that out.
3. If you don't want to use netCDFs, you can fake multidimensionality for
some scenarios by building a raster catalog with columns for the time and
depth.
I have no idea how to do that -- can GDAL build a raster catalog?
4. My group, the Duke University Marine Geospatial Ecology Lab, is currently
building 3D and 4D awareness into a collection of tools we publish, Marine
Geospatial Ecology Tools (MGET, see
http://code.nicholas.duke.edu/projects/mget), built in Python on GDAL and
other FOSS packages.
Very cool. I'll keep an eye on that.
Thanks for everyone's help,
-Chris
