Thanks a lot. It seems to be a very basic question, as you might
relize, I'm making my firsts baby steps on GIS...

And the acronym pcs wasn't easy to search on the web...



2011/8/31, Robert Sanson <[email protected]>:
> Hi Juan
>
> Projected Coordinate System. Usually means a cartesian system (2D
> plane) rather than a spherical system (lat/long).
>
> Regards,
>
> Robert Sanson
>
>>>> Juan F Paulini <[email protected]> 31/08/2011 9:32 p.m. >>>
> Thanks Hanlie,
>
> But I'm not sure about the meaning of the PCS acronym..
>
>
>
> El 31/08/2011, a las 01:25, ping <[email protected]>
> escribió:
>
>> Hi jpaulinin,
>>
>> I agree with Tyler that one can work in any coordinate system, as
> long
>> as you're using the same one for the gauge and the satellite data.
>>
>> I used a Transverse Mercator projected coordinate system for various
>> reasons that were not connected with the rainfall.
>>
>> In the PCS, the TRMM grid cells are not all of equal size and they
> are
>> no longer squares.
>>
>> If you'll need the area of the grid cells for some reason, I think
>> you'll have to work in a PCS.
>>
>> Regards
>> Hanlie
>>
>>
>>
>> On Aug 30, 9:48 pm, jpaulini <[email protected]> wrote:
>>> Thanks Tyler
>>>
>>> Well. I've found that the readme of TRMM file (3B42):
>>>
>>> The *grid* on which each field of values is presented is a
> 0.25*x0.25*
>>> lat./lon. (Cylindrical
>>> Equal Distance) global array of points. It is size 1440x400, with X
>>> (longitude) incrementing
>>> most rapidly West to East from the Dateline, and then Y (latitude)
>>> incrementing South to North
>>> from the southern edge. Quarter-degree latitude and longitude
> values
>>> are at grid edges:
>>> First point center (49.875*S,179.875*W)
>>> Second point center (49.875*S,179.625*W)
>>> Last point center (49.875*N,179.875*E)
>>> The reference datum is WGS84.
>>>
>>> It is the same datum used for gauges georeference. So I think that
> its
>>> ok to compare the x,y coordinates.
>>>
>>> I've not compared the gauges information against the satellite
>>> information yet, but I'll have this in mind.
>>>
>>> Thanks again for your help.
>>>
>>> On Aug 30, 2:18 pm, Tyler Erickson <[email protected]> wrote:
>>>
>>>> jpaulini,
>>>
>>>> A few thoughts:
>>>
>>>>    - Precipitation is usually measured in units of length/time, so
> if the
>>>>    area of the grid cell changes with latitute it doesn't matter.
> If it is
>>>>    reported as a volume per grid cell (which I doubt it would be)
> then it does
>>>>    matter.
>>>>    - If you are comparing point gauge data to a gridded spatial
> variable,
>>>>    you will need to reproject one of the other to match projections
> (and
>>>>    datums). Because reprojecting a raster will alter the cell
> values (by some
>>>>    interpolation method, whether explicitly known or not), I would
> suggest
>>>>    reprojecting the point data.  If the datums are not actually the
> same and
>>>>    you assume they are, you could easily be misaligned by 10km (the
> error
>>>>    varies by latitude).
>>>
>>>> - Tyler
>>>
>>>> On Tue, Aug 30, 2011 at 6:51 AM, jpaulini <[email protected]>
> wrote:
>>>>> Hi all,
>>>
>>>>> This question goes mainly for Hanlie, but everyone is welcome..
>>>
>>>>> I'm thinking on doing some similar to you, Hanlie, comparing
> satellite
>>>>> information vs rain gauges. But I had the following doubt:
>>>
>>>>> Do you need to change the projection of the satellite information
> to
>>>>> match the projection of the rain gauges georeferenced
> localization? I
>>>>> see that you are assuming 28 sq. km grid, but depending on the
>>>>> latitude that you are, it can be a different surface, right?
>>>
>>>>> On Aug 15, 12:27 pm, Andy Wilson <[email protected]>
> wrote:
>>>>>> If you calculate Thiessen polygons for your 6 gauges and clip
> them to
>>>>> your
>>>>>> grid cell boundary then you'll be able to see how much each gauge
> would
>>>>>> contribute to the interpolated mean grid cell value. So you can
> just use
>>>>> the
>>>>>> areas of the polygons as weights for a weighted mean, and that
> should
>>>>> come
>>>>>> out the same as interpolating and then aggregating. If the
> position of
>>>>> the
>>>>>> gauges doesn't change, then the weights don't change so you only
> have to
>>>>> do
>>>>>> that once. Then you just apply your weighted mean function 730
> times.
>>>
>>>>>> Does that make sense or did I misunderstand something?
>>>
>>>>>> On Mon, Aug 15, 2011 at 2:03 AM, Hanlie Pretorius <
>>>
>>>>>> [email protected]> wrote:
>>>>>>> Hi,
>>>
>>>>>>> I have rainfall measurements from 6 gauges that I want to
> interpolate
>>>>>>> to an areal value (a 'surface'), so that I can compare the
>>>>>>> interpolated gauge values to a satellite rainfall estimate that
> covers
>>>>>>> a grid cell of 28kmx28km. Two of the gauges are outside, but
> close to
>>>>>>> the border of the grid cell. Therefore, I also need to clip the
>>>>>>> interpolated surface to the grid cell and to get the average of
> the
>>>>>>> surface value in this clipped surface.
>>>
>>>>>>> However, for each rain gauge I have 730 values representing a
> daily
>>>>>>> measurement over two years. As output, I need a text file
>>>>>>> with the interpolated rainfall values for each day in my time
> series.
>>>>>>> So, I was wondering if there is an 'easy' way to get my output
> without
>>>>>>> creating 730 GIS layers?
>>>
>>>>>>> Regards
>>>>>>> Hanlie
>
>
> This email and any attachments are confidential and intended solely for the
> addressee(s). If you are not the intended recipient, please notify us
> immediately and then delete this email from your system.
>
> This message has been scanned for Malware and Viruses by Websense Hosted
> Security.
> www.websense.com
>

Reply via email to