t;>>
>>>
>>> As a test, I would calculate the statistics for a smaller area centered
>>> at the equator. I would expect that the results are very similar comparing
>>> the lat/long and the reprojected dataset.
>>>
>>>
>>>
>>&
>>
>>
>>
>> As a test, I would calculate the statistics for a smaller area centered
>> at the equator. I would expect that the results are very similar comparing
>> the lat/long and the reprojected dataset.
>>
>>
>>
>> Regards Jörg
.org] *Im Auftrag
> von *Carlos Grohmann
> *Gesendet:* Montag, 16. November 2015 23:32
> *Cc:* GRASS user list
> *Betreff:* Re: [GRASS-user] r.univar: different results with different
> projections?
>
>
>
> Hello Cesar
>
>
>
> That was weird, so I tested it agai
: Montag, 16. November 2015 23:32
Cc: GRASS user list
Betreff: Re: [GRASS-user] r.univar: different results with different
projections?
Hello Cesar
That was weird, so I tested it again. The number of cells is the same for both
projections, but the values differ. This must be related to reprojecting
Hello Cesar
That was weird, so I tested it again. The number of cells is the same for
both projections, but the values differ. This must be related to
reprojecting.
To me, they shouldn't de different, since a nearest neighbor should
preserve the original values. I'm not really comfortable with th
Carlos,
2015-11-16 14:47 GMT-05:00 Carlos Grohmann :
> GRASS 7.1.svn (base_maps):~ > g.region -p raster=gdem_etopo1_ice
> cells: 23328
>
> GRASS 7.1.svn (base_maps):~ > r.univar map=gdem_etopo1_ice -ge
> percentile=100
> cells=5832
>
> GRASS 7.1.svn (eqarea):~ > r.univar map=gdem_eto
On Mon, Nov 16, 2015 at 8:47 PM, Carlos Grohmann
wrote:
> Ok, sorry about the incomplete post.
>
> I reprojected from a latlong location to a cylindrical equal area
> projection, using the default nearest neighbor resampling method.
For continuous surfaces such as DEM I would use bilinear resampl
Ok, sorry about the incomplete post.
I reprojected from a latlong location to a cylindrical equal area
projection, using the default nearest neighbor resampling method.
original location:
>GRASS 7.1.svn (base_maps):~ > g.region -p raster=gdem_etopo1_ice
projection: 3 (Latitude-Longitude)
zone:
On Mon, Nov 16, 2015 at 5:34 PM, Carlos Grohmann
wrote:
> Hi all.
>
> I'm analyzing some global-scale DEMs, like ETOPO1/2, SRTM30_PLUS, etc.
>
> I'm getting the statistics for the whole dataset with r.univar, but today I
> noticed that the results differ if I use different projections. (GRASS 7.1)
Hello Cesar
I wouldn't expect pixel resolution to play a role here. The statistics must
be carried out over the values.
The raster(s) I'm testing are rectangular, without null values. So
reprojecting will change the pixel size (from a square to a rectangle), but
it will (should) not change the num
Hello Carlos,
Maybe it has something to do with the pixel resolution? I would certainly
expect the same results, but with a very similar region (i.e. same number
of rows and columns, or at least very close and a similar number of pixels)
Maybe when projecting the raster, the length of the array i
Hi all.
I'm analyzing some global-scale DEMs, like ETOPO1/2, SRTM30_PLUS, etc.
I'm getting the statistics for the whole dataset with r.univar, but today I
noticed that the results differ if I use different projections. (GRASS 7.1)
For example, ETOPO2:
Using a latlong pseudo-projection (plate ca
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