Yes Anna you're right. New pixel will be created and some might be lost. But the changes in the statistics is what concerns me. If your statistical description of a raster changes significantly after reprojection, which one is right?
On Tue, Nov 17, 2015 at 12:50 PM, Anna Petrášová <[email protected]> wrote: > > > On Tue, Nov 17, 2015 at 7:56 AM, Carlos Grohmann < > [email protected]> wrote: > >> Hello Jörg >> >> The area of cell shouldn't influence here. The statistics are about the >> elevation values, regardless of the area represented by pixel. If I think >> on the pixels as equally-spaced vector points, after projection they won't >> be equally-spaced anymore, but the number of points won't change. So the >> mean of their values (and stddev, etc) shouldn't change as well. >> > > I don't think you can treat pixels as vector points here, I agree with > what Jörg was saying. If some vector points would get further away, you > will get new pixels in between and if the points get close enough, the > information in all points but one is lost. This is at least my intuitive > understanding of the NN reprojection which can be wrong. I wouldn't be > concerned that the results changed but how much they changed. > > Anna > > >> regards >> >> Carlos >> >> >> On Tue, Nov 17, 2015 at 5:15 AM, Robl Jörg Christian < >> [email protected]> wrote: >> >>> Dear Carlos, >>> >>> >>> >>> I’m not an expert for projections. >>> >>> However, on Lat/Long WGS84 the actual area of cells decline from the >>> equator towards the poles. >>> >>> Thus, I would expect that cell values near the poles have “more weight” >>> using Lat/Long WGS84 than using an equal area projection. >>> >>> >>> >>> Near the poles I don’t understand how the values for extent and >>> resolution should be correct (equal area), except there is a huge >>> distortion (very likely for a cylindrical projection)! >>> >>> Are there really 21600 cols with a nsres = 1178 m at the north and south >>> pole. I would call this a huge distortion. >>> >>> >>> >>> 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 >>> >>> >>> >>> >>> >>> >>> >>> *Von:* grass-user [mailto:[email protected]] *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 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 this, as I'm >>> not sure I can trust the stats after projecting. >>> >>> >>> >>> best >>> >>> >>> >>> Carlos >>> >>> >>> >>> >>> >>> GRASS 7.1.svn (latlong):~ > g.region raster=gdem_etopo1_ice -pa >>> >>> projection: 3 (Latitude-Longitude) >>> >>> zone: 0 >>> >>> datum: wgs84 >>> >>> ellipsoid: wgs84 >>> >>> north: 90N >>> >>> south: 90S >>> >>> west: 180W >>> >>> east: 180E >>> >>> nsres: 0:01 >>> >>> ewres: 0:01 >>> >>> rows: 10800 >>> >>> cols: 21600 >>> >>> cells: 233280000 >>> >>> GRASS 7.1.svn (latlong):~ > r.univar map=gdem_etopo1_ice -ge >>> percentile=100 >>> >>> n=233280000 >>> >>> null_cells=0 >>> >>> cells=233280000 >>> >>> min=-10803 >>> >>> max=8333 >>> >>> range=19136 >>> >>> mean=-1892.40422534294 >>> >>> mean_of_abs=2644.91906490912 >>> >>> stddev=2649.98339302808 >>> >>> variance=7022411.98332463 >>> >>> coeff_var=-140.032629262802 >>> >>> sum=-441460057688 >>> >>> first_quartile=-4286 >>> >>> median=-2457 >>> >>> third_quartile=214 >>> >>> percentile_100=8333 >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> GRASS 7.1.svn (eqarea):~ > g.region -p >>> >>> projection: 99 (Equal Area Cylindrical) >>> >>> zone: 0 >>> >>> datum: wgs84 >>> >>> ellipsoid: wgs84 >>> >>> north: 6363885.33192604 >>> >>> south: -6363885.33192604 >>> >>> west: -20037508.34278924 >>> >>> east: 20037508.34278924 >>> >>> nsres: 1178.49728369 >>> >>> ewres: 1855.32484655 >>> >>> rows: 10800 >>> >>> cols: 21600 >>> >>> cells: 233280000 >>> >>> GRASS 7.1.svn (eqarea):~ > r.univar map=gdem_etopo1_ice -ge >>> percentile=100 >>> >>> n=233280000 >>> >>> null_cells=0 >>> >>> cells=233280000 >>> >>> min=-10803 >>> >>> max=8333 >>> >>> range=19136 >>> >>> mean=-2382.28934158093 >>> >>> mean_of_abs=2845.10169015775 >>> >>> stddev=2508.93105538271 >>> >>> variance=6294735.0406638 >>> >>> coeff_var=-105.315966939504 >>> >>> sum=-555740457604 >>> >>> first_quartile=-4544 >>> >>> median=-3285 >>> >>> third_quartile=93 >>> >>> percentile_100=8333 >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> On Mon, Nov 16, 2015 at 7:43 PM, César Augusto Ramírez Franco < >>> [email protected]> wrote: >>> >>> Carlos, >>> >>> >>> >>> 2015-11-16 14:47 GMT-05:00 Carlos Grohmann <[email protected]>: >>> >>> GRASS 7.1.svn (base_maps):~ > g.region -p raster=gdem_etopo1_ice >>> >>> cells: 233280000 >>> >>> >>> >>> GRASS 7.1.svn (base_maps):~ > r.univar map=gdem_etopo1_ice -ge >>> percentile=100 >>> >>> cells=58320000 >>> >>> >>> >>> GRASS 7.1.svn (eqarea):~ > r.univar map=gdem_etopo1_ice -ge >>> percentile=100 >>> >>> cells=233280000 >>> >>> >>> >>> Notice how the number of pixels differs, that's the reason the >>> statistics are not the same, I don't get why the region has a different >>> number of pixels than the raster itself in the original latlong >>> projection... I think that's the root of the issue >>> >>> >>> >>> -- >>> >>> *César Augusto Ramírez Franco* >>> Laboratorio de Sistemas Complejos Naturales >>> Escuela de Geociencias - Facultad de Ciencias >>> Universidad Nacional de Colombia - Sede Medellín >>> Teléfono: (57-4) 430 9369 - 300 459 6085 >>> >>> http://labscn-unalmed.github.io/ >>> >>> >>> >>> >>> >>> -- >>> >>> Prof. Carlos Henrique Grohmann >>> Institute of Energy and Environment - Univ. of São Paulo, Brazil >>> >>> - Digital Terrain Analysis | GIS | Remote Sensing - >>> >>> >>> >>> http://carlosgrohmann.com >>> >>> http://orcid.org/0000-0001-5073-5572 >>> >>> ________________ >>> Can’t stop the signal. >>> >> >> >> >> -- >> Prof. Carlos Henrique Grohmann >> Institute of Energy and Environment - Univ. of São Paulo, Brazil >> - Digital Terrain Analysis | GIS | Remote Sensing - >> >> http://carlosgrohmann.com >> http://orcid.org/0000-0001-5073-5572 >> ________________ >> Can’t stop the signal. >> >> _______________________________________________ >> grass-user mailing list >> [email protected] >> http://lists.osgeo.org/mailman/listinfo/grass-user >> > > -- Prof. Carlos Henrique Grohmann Institute of Energy and Environment - Univ. of São Paulo, Brazil - Digital Terrain Analysis | GIS | Remote Sensing - http://carlosgrohmann.com http://orcid.org/0000-0001-5073-5572 ________________ Can’t stop the signal.
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