Hi

I am new to spacial data processing. For a project of mine I try to load swedish climate data in to my PostGIS installation running/using an openSUSE Tumbleweed installation.

I downloaded the data from https://thredds.met.no/thredds/catalog/senorge/seNorge2/archive/PREC1m/catalog.html?dataset=senorge/seNorge2/archive/PREC1m/seNorge_v2_0_PREC1m_grid_1957_2015.nc and tried to load it by

function load() {
    _FILE=${1}
    _TABLE=$(basename -s .nc ${_FILE})
    nice -n 19 raster2pgsql -d \
                 -C \
                 -r \
                 -P \
                 -R \
                 -F \
                 -I \
                 -M \
                 -Y \
                 ${_FILE} \
                 nc.${_TABLE} | \
                   nice -n 19 psql -d norge -U norge -p 6543
}
load seNorge_v2_0_PREC1m_grid_1957_2015.nc

I could not see any error, however, the file is a good 700 MB size but the data load took only a few seconds. If I query the data, it seems to me that only a fragment of data was loaded:

select ST_MetaData(rast) as meta, -- Kind of a serialisation of the specifics below
       ST_PixelHeight(rast) As pixheight,
       ST_PixelWidth(rast) As pixhwidth,
       ST_IsEmpty(rast) as is_empty,
       ST_MemSize(rast) as space_used_in_B,
       ST_BandMetaData(rast, 1) as band_1_meta_data,
       ST_BandMetaData(rast, 708) as band_708_meta_data,
       ST_MemSize(rast)/1024 as space_used_in_KB,
       ST_GeoReference(rast, 'ESRI') As esri_ref,
       ST_GeoReference(rast, 'GDAL') As gdal_ref
  from nc.senorge_v2_0_prec1m_grid_1957_2015;

Please note I transposed the result of the query to better fit into the mail.
meta                 (-75000,8000000,1195,1550,1000,-1000,0,0,0,708)
pixheight            1000
pixhwidth            1000
is_empty             false
space_used_in_b      34048
band_1_meta_data (32BF,-999.989990234375,t,seNorge_v2_0_PREC1m_grid_1957_2015.nc,1,,) band_708_meta_data (32BF,-999.989990234375,t,seNorge_v2_0_PREC1m_grid_1957_2015.nc,196,,)
space_used_in_kb     33
esri_ref 1000.0000000000 0.0000000000 0.0000000000 -1000.0000000000 -74500.0000000000 7999500.0000000000 gdal_ref 1000.0000000000 0.0000000000 0.0000000000 -1000.0000000000 -75000.0000000000 8000000.0000000000

Can anyone enlighten me?

Kind regards

Thiemo

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