The raster resolution for the rainfall data was 0.25 degrees, or about 27 km. per pixel. So each pixel covers about 750 sq.km. The column with the precip_sum will be mm/raster cell, or mm over an area of 750,000,000 sq.m.
Does that make more sense?

On 06/22/2010 03:57 PM, Sandile Gumede wrote:
It's in mm/hr.

Are these values normal, to me it seems like big values because they are ranging from 2000-4500, see below I just copied a few:

120795|4076||1|4076|4076|0|4076|0|0|0|4076
120796|4080||1|4080|4080|0|4080|0|0|0|4080
120797|4084||1|4084|4084|0|4084|0|0|0|4084
120798|4088||1|4088|4088|0|4088|0|0|0|4088
120799|4092||1|4092|4092|0|4092|0|0|0|4092
120800|4096||1|4096|4096|0|4096|0|0|0|4096
120801|4100||1|4100|4100|0|4100|0|0|0|4100
120802|4104||1|4104|4104|0|4104|0|0|0|4104
120803|4108||1|4108|4108|0|4108|0|0|0|4108
120804|4112||1|4112|4112|0|4112|0|0|0|4112
120805|4116||1|4116|4116|0|4116|0|0|0|4116
120806|4120||1|4120|4120|0|4120|0|0|0|4120
120807|4124||1|4124|4124|0|4124|0|0|0|4124
120808|4128||1|4128|4128|0|4128|0|0|0|4128
120809|4144||1|4144|4144|0|4144|0|0|0|4144
120810|4148||1|4148|4148|0|4148|0|0|0|4148
120811|4152||1|4152|4152|0|4152|0|0|0|4152
120812|4156||1|4156|4156|0|4156|0|0|0|4156


2010/6/22 Micha Silver <[email protected] <mailto:[email protected]>>

    On 22/06/2010 13:08, Sandile Gumede wrote:
    Thanks, I finally got the results.
    That's good to hear.


    Now the question I would like to ask is that, from these columns
    I got the values but which unit are these values are measured? Is
    it (mm) or ?
    Well, that depends on the units of the raster. If the raster
values are mm. then each column represents mm per *raster cell*. So if you have a rainfall raster with values in mm., and
    resolution of 10 meters, then the numbers in the columns are
    mm/100sq.m.
-- Micha



    On Sat, Jun 19, 2010 at 9:57 PM, Micha Silver <[email protected]
    <mailto:[email protected]>> wrote:

        Hello Sandile:
        I tried to duplicate your steps and it seems to work for me.
        Here's what I did:


        wget
        ftp://trmmopen.gsfc.nasa.gov/pub/gis/3B42RT.2010032900.1day.tif
        wget
        ftp://trmmopen.gsfc.nasa.gov/pub/gis/3B42RT.2010032900.1day.tfw

        gdalinfo 3B42RT.2010032900.1day.tif
        Driver: GTiff/GeoTIFF
        Files: 3B42RT.2010032900.1day.tif
               3B42RT.2010032900.1day.tfw
        Size is 1440, 480
        Coordinate System is `'
        Origin = (-180.000000000000000,60.000000000000000)
        Pixel Size = (0.250000000000000,-0.250000000000000)
        ....

        ---- Note: no projection info above ----

        ---- Now I use the -projwin option of gdal_translate to
        select a small window
        gdal_translate -a_srs EPSG:4326 -projwin 34.0 33.0 36.0 29.0
        3B42RT.2010032900.1day.tif rainfall_il.tif

        ---- GEOGCS entry now shows 4326 ----

        g.mapset map=ASTER_DEM loc=WGS84
        ----- A location setup as EPSG:4326----

        r.in.gdal israel.tif out=rainfall_il

        r.univar rainfall_il
         100%
        total null and non-null cells: 77760000

        total null cells: 0

        Of the non-null cells:
        ----------------------
        n: 77760000
        minimum: 0
        maximum: 34
        range: 34
        mean: 0.364583
        mean of absolute values: 0.364583
        standard deviation: 3.45241
        variance: 11.9192
        variation coefficient: 946.948 %
        sum: 28350000


        ----- Now using an existing catchment vector map ----
        v.rast.stats vect=arava_wsheds rast=rainfall_il colpre=precip
        v.info <http://v.info> -c arava_wsheds
        Displaying column types/names for database connection of layer 1:
        INTEGER|cat
        CHARACTER|label
        DOUBLE PRECISION|area_km
        INTEGER|precip_n
        DOUBLE PRECISION|precip_min
        DOUBLE PRECISION|precip_max
        DOUBLE PRECISION|precip_range
        DOUBLE PRECISION|precip_mean
        DOUBLE PRECISION|precip_stddev
        DOUBLE PRECISION|precip_variance
        DOUBLE PRECISION|precip_cf_var
        DOUBLE PRECISION|precip_sum

        ---- and some values ----

        v.db.select arava_wsheds
        
cat|label|area_km|precip_n|precip_min|precip_max|precip_range|precip_mean|precip_stddev|precip_variance|precip_cf_var|precip_sum
        21|Jordan|1055.231692|2|0|0|0|0|0|0||0
        19|Hidan|987.811979|2|0|0|0|0|0|0||0
        28|Og|124.122969|||||||||
        36|Zarqa|273.606213|||||||||
        24|Kidron|122.460114|||||||||
        9|Darga|289.012122|||||||||
        6|Arugot|236.365116|1|0|0|0|0|0|0||0
        26|Mujib|1277.546513|2|0|0|0|0|0|0||0

        ---- (Many catchments have 0 or no value because of the small
        region I chose. The global data is 1/4 degree resolution and
        my region is only 2 deg E-W.)----

        HTH...
-- Micha



        On 06/17/2010 12:50 PM, Sandile Gumede wrote:
        Hi

        It is still giving me -NULL value error.

        Do you think maybe its the way I downloaded my rainfall
        data? This is the site where I downloaded my data sets_
        ftp://trmmopen.gsfc.nasa.gov/pub/gis/ _and this data covers
        the whole world, the only thing I did was to clip a specific
        region (using coordinates) that is in South Africa to do my
        analysis. I used a bash script to download and project the
        data, see below:


        #!/bin/bash

        wget
        ftp://trmmopen.gsfc.nasa.gov/pub/gis/3B42RT.2010032900.1day.tif
        wget
        ftp://trmmopen.gsfc.nasa.gov/pub/gis/3B42RT.2010032900.1day.tfw

        gdal_translate -of GTiff -co "PROFILE=GeoTIFF" -co
        "INTERLEAVE=PIXEL" -co "COMPRESS=LZW" -co "TILED=YES" -a_srs
        EPSG:4326 -a_ullr 18.2987501 -33.6795831 19.1712501
        -34.3487498 3B42RT.2010032900.1day.tif TRMMLast1day.tif




        On Thu, Jun 17, 2010 at 8:41 AM, Sandile Gumede
        <[email protected] <mailto:[email protected]>> wrote:

            Hi

            It is still giving me -NULL value error.

            Do you think maybe its the way I downloaded my rainfall
            data? This is the site where I downloaded my data sets_
            ftp://trmmopen.gsfc.nasa.gov/pub/gis/ _and this data
            covers the whole world, the only thing I did was to clip
            a specific region (using coordinates) that is in South
            Africa to do my analysis. I used a bash script to
            download and project the data, see below:


            #!/bin/bash

            wget
            ftp://trmmopen.gsfc.nasa.gov/pub/gis/3B42RT.2010032900.1day.tif
            wget
            ftp://trmmopen.gsfc.nasa.gov/pub/gis/3B42RT.2010032900.1day.tfw

            gdal_translate -of GTiff -co "PROFILE=GeoTIFF" -co
            "INTERLEAVE=PIXEL" -co "COMPRESS=LZW" -co "TILED=YES"
            -a_srs EPSG:4326 -a_ullr 18.2987501 -33.6795831
            19.1712501 -34.3487498 3B42RT.2010032900.1day.tif
            TRMMLast1day.tif



            2010/6/15 Micha Silver <[email protected]
            <mailto:[email protected]>>

                On 15/06/2010 14:35, Sandile Gumede wrote:
                Hi
                If I run g.region rast=rainfall -p, I get:
                OK, what you've done here is change the current
                region to match the raster "rainfall".
                Can you now try:
                v.rast.stats -c vect=catchments rast=rainfall
                pref=precip



                projection: 3 (Latitude-Longitude)
                zone:       0
                datum:      wgs84
                ellipsoid:  wgs84
                north:      33:40:46.49916S
                south:      34:20:55.49928S
                west:       18:17:55.50036E
                east:       19:10:16.50036E
                nsres:      0:00:05.01875
                ewres:      0:00:02.18125
                rows:       480
                cols:       1440
                cells:      691200

                and If I run r.univar rainfall, I get the following
                output:

                 100%
                total null and non-null cells: 691200
                total null cells: 0

                Of the non-null cells:
                ----------------------
                n: 691200
                minimum: 0
                maximum: 3094
                range: 3094
                mean: 22.0228
                mean of absolute values: 22.0228
                standard deviation: 76.1639
                variance: 5800.94
                variation coefficient: 345.841 %
                sum: 15222164



                On Tue, Jun 15, 2010 at 12:22 PM, Hamish
                <[email protected] <mailto:[email protected]>> wrote:

                    Micha wrote:
                    > The only unusual thing I notice above is that
                    the resolution settings
                    > for the raster are different N-S and E-W.
                    This came from the original
                    > tiff (see below) which also has rectangular
                    pixels,

                    that is perfectly normal for a lat/lon map away
                    from the equator.
                    longitude scales a cos(lat).


                    > (the v.rast.stats module creates a temp
                    raster at the *current region's
                    > resolution* settings, which might be
                    different from this rainfall
                    > raster's rectangular resolution...)

                    the results of:

                    g.region -p rast=mapname
                    r.univar mapname


                    could help.


                    Hamish






-- Kind Regards
                TS Gumede
                CSIR, Meraka Institute
                072 258 1650


                This mail was received via Mail-SeCure System.


-- Micha Silver
                http://www.surfaces.co.il/
                Arava Development Co.  +972-52-3665918



-- Kind Regards
            TS Gumede
            CSIR, Meraka Institute
            072 258 1650




-- Kind Regards
        TS Gumede
        CSIR, Meraka Institute
        072 258 1650


        This mail was received via Mail-SeCure System.


-- Micha Silver
        Arava Development Co. +972-52-3665918
        http://surfaces.co.il




-- Kind Regards
    TS Gumede
    CSIR, Meraka Institute
    072 258 1650


    This mail was received via Mail-SeCure System.


-- Micha Silver
    http://www.surfaces.co.il/
    Arava Development Co.  +972-52-3665918



--
Kind Regards
TS Gumede
CSIR, Meraka Institute
072 258 1650


This mail was received via Mail-SeCure System.


--
Micha Silver
http://www.surfaces.co.il/
Arava Development Co.  +972-52-3665918

_______________________________________________
grass-user mailing list
[email protected]
http://lists.osgeo.org/mailman/listinfo/grass-user

Reply via email to