On 9/9/2011 6:42 AM, Scott Sinclair wrote:
> On 8 September 2011 19:20, Matt Funk <matze...@gmail.com> wrote:
>> Hi,
>> sorry that it has taken me so long to reply. Anyway, i could be wrong, but i
>> don't think that the code:
>>     xi = np.linspace(llcrnlon,urcrnlon,1000)
>>     yi = np.linspace(llcrnlat,urcrnlat,1000)
>>
>> will produce a grid which gives the lat/lon coordinates with 1km spacing.
>> The reason being is that the distance between 2 lons (say -117.731659 and
>> -91.303642) is different depending on where you are in terms of the latitude
>> (i.e. the extreme examples are of course the north pole vs the equator). So
>> the above gives a regular grid in terms of degrees but not in terms of
>> distance.
> Yes, that's correct. You'll need to project your original data
> locations into a cartesian co-ordinate system before interpolating
> their values onto a regular grid in that co-ordinate system using
> griddata et al.
>
> You might like to use pyproj (included with the basemap toolkit) to
> help you project from lat/lon to your chosen co-ordinate system..
I have been using gdal for many of my geographic needs. Is there an
advantage/disadvantage using pyproj vs capabilities found in gdal (from
what i understand both are based on PROJ.4)? Can you comment on this?
Also, i was thinking of projecting things to UTM for interpolation
purposes. Is there any apparent reason this is a bad idea vs a different
projected coordinate system?

matt

>
> Cheers,
> Scott
>
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-- 
Matt Funk
Research Associate
Plant and Environmental Scienc. Dept.
New Mexico State University


------------------------------------------------------------------------------
Why Cloud-Based Security and Archiving Make Sense
Osterman Research conducted this study that outlines how and why cloud
computing security and archiving is rapidly being adopted across the IT 
space for its ease of implementation, lower cost, and increased 
reliability. Learn more. http://www.accelacomm.com/jaw/sfnl/114/51425301/
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