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NAME

t.rast.import.netcdf - Import netCDF files that adhere to the CF convention as STRDS.

KEYWORDS

temporal, import, raster, time, netcdf

SYNOPSIS

t.rast.import.netcdf
t.rast.import.netcdf --help
t.rast.import.netcdf [-arlfeo] input=Input file(s) ("-" = stdin) [semantic_labels=Input file with configuration for semantic labels ("-" = stdin)] [output=name] [end_time=string] [start_time=string] [temporal_relations=string[,string,...]] [resample=string] [print=string] [color=style] [memory=memory in MB] [nprocs=Number of cores] [separator=character] [nodata=Source nodata[,Source nodata,...]] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

-a
Append to STRDS
-r
Import only within current region
-l
Link the raster files using r.external
-f
Link the raster files in a fast way, without reading metadata using r.external
-e
Extend location extents based on new dataset
-o
Override projection check (use current location's projection)
Assume that the dataset has same projection as the current location
--overwrite
Allow output files to overwrite existing files
--help
Print usage summary
--verbose
Verbose module output
--quiet
Quiet module output
--ui
Force launching GUI dialog

Parameters:

input=Input file(s) ("-" = stdin) [required]
URL or name of input netcdf-file ("-" = stdin)
semantic_labels=Input file with configuration for semantic labels ("-" = stdin)
File with mapping of variables or subdatasets to semantic labels
output=name
Name of the output space time raster dataset
end_time=string
Latest timestamp of temporal extent to include in the output
Timestamp of format "YYYY-MM-DD HH:MM:SS"
start_time=string
Earliest timestamp of temporal extent to include in the output
Timestamp of format "YYYY-MM-DD HH:MM:SS"
temporal_relations=string[,string,...]
Allowed temporal relation for temporal filtering
Allowed temporal relation between time dimension in the netCDF file and temporal window defined by start_time and end_time
Options: equal, during, contains, overlaps, overlapped, starts, started, finishes, finished
Default: equal,during,contains,overlaps,overlapped,starts,started,finishes,finished
resample=string
Resampling method when data is reprojected
Options: nearest, bilinear, bicubic, cubicspline, lanczos, average, mode, max, min, med, Q1, Q3
Default: nearest
print=string
Print metadata and exit
Options: extended, grass
color=style
Color table to assign to imported datasets
Options: aspect, aspectcolr, bcyr, bgyr, blues, byg, byr, celsius, corine, curvature, differences, elevation, etopo2, evi, fahrenheit, forest_cover, gdd, grass, greens, grey, grey.eq, grey.log, grey1.0, grey255, gyr, haxby, inferno, kelvin, magma, ndvi, ndwi, nlcd, oranges, plasma, population, population_dens, precipitation, precipitation_daily, precipitation_monthly, rainbow, ramp, random, reds, roygbiv, rstcurv, ryb, ryg, sepia, slope, soilmoisture, srtm, srtm_plus, terrain, viridis, water, wave
Default: viridis
aspect aspect: aspect oriented grey colors [range: map values]
aspectcolr aspectcolr: aspect oriented rainbow colors [range: 0 to 360]
bcyr bcyr: blue through cyan through yellow to red [range: map values]
bgyr bgyr: blue through green through yellow to red [range: map values]
blues blues: white to blue [range: map values]
byg byg: blue through yellow to green [range: map values]
byr byr: blue through yellow to red [range: map values]
celsius celsius: blue to red for degree Celsius temperature [range: -80 to 80]
corine corine: EU Corine land cover colors [range: 111 to 995]
curvature curvature: for terrain curvatures (from v.surf.rst and r.slope.aspect) [range: map values]
differences differences: differences oriented colors [range: map values]
elevation elevation: maps relative ranges of raster values to elevation color ramp [range: map values]
etopo2 etopo2: colors for ETOPO2 worldwide bathymetry/topography [range: -11000 to 8850]
evi evi: enhanced vegetative index colors [range: -1 to 1]
fahrenheit fahrenheit: blue to red for Fahrenheit temperature [range: -112 to 176]
forest_cover forest_cover: percentage of forest cover [range: 0 to 100]
gdd gdd: accumulated growing degree days [range: 0 to 6000]
grass grass: GRASS GIS green (perceptually uniform) [range: map values]
greens greens: white to green [range: map values]
grey grey: grey scale [range: map values]
grey.eq grey.eq: histogram-equalized grey scale [range: map values]
grey.log grey.log: histogram logarithmic transformed grey scale [range: map values]
grey1.0 grey1.0: grey scale for raster values between 0.0-1.0 [range: 0 to 1]
grey255 grey255: grey scale for raster values between 0-255 [range: 0 to 255]
gyr gyr: green through yellow to red [range: map values]
haxby haxby: relative colors for bathymetry or topography [range: map values]
inferno inferno: perceptually uniform sequential color table inferno [range: map values]
kelvin kelvin: blue to red for temperature in Kelvin scale [range: 193.15 to 353.15]
magma magma: perceptually uniform sequential color table magma [range: map values]
ndvi ndvi: Normalized Difference Vegetation Index colors [range: -1 to 1]
ndwi ndwi: Normalized Difference Water Index colors [range: -200 to 200]
nlcd nlcd: US National Land Cover Dataset colors [range: 0 to 95]
oranges oranges: white to orange [range: map values]
plasma plasma: perceptually uniform sequential color table plasma [range: map values]
population population: color table covering human population classification breaks [range: 0 to 2e+09]
population_dens population_dens: color table covering human population density classification breaks [range: 0 to 1e+09]
precipitation precipitation: precipitation color table (0..2000mm) [range: 0 to 7000]
precipitation_daily precipitation_daily: precipitation color table (0..1000mm) [range: 0 to 10000]
precipitation_monthly precipitation_monthly: precipitation color table (0..1000mm) [range: 0 to 1000]
rainbow rainbow: rainbow color table [range: map values]
ramp ramp: color ramp [range: map values]
random random: random color table [range: map values]
reds reds: white to red [range: map values]
roygbiv roygbiv: [range: map values]
rstcurv rstcurv: terrain curvature (from r.resamp.rst) [range: map values]
ryb ryb: red through yellow to blue [range: map values]
ryg ryg: red through yellow to green [range: map values]
sepia sepia: yellowish-brown through to white [range: map values]
slope slope: r.slope.aspect-type slope colors for raster values 0-90 [range: 0 to 90]
soilmoisture soilmoisture: soilmoisture color table (0.0-1.0) [range: 0 to 1]
srtm srtm: color palette for Shuttle Radar Topography Mission elevation [range: -11000 to 8850]
srtm_plus srtm_plus: color palette for Shuttle Radar Topography Mission elevation (with seafloor colors) [range: -11000 to 8850]
terrain terrain: global elevation color table covering -11000 to +8850m [range: -11000 to 8850]
viridis viridis: perceptually uniform sequential color table viridis [range: map values]
water water: water depth [range: map values]
wave wave: color wave [range: map values]
memory=memory in MB
Maximum memory to be used (in MB)
Cache size for raster rows
Default: 300
nprocs=Number of cores
Number of cores to use during import
Default: 1
separator=character
Field separator
Special characters: pipe, comma, space, tab, newline
Default: pipe
nodata=Source nodata[,Source nodata,...]
Comma separated list of values representing nodata in the input dataset

Table of contents

DESCRIPTION

t.rast.import.netcdf imports content of one or more NetCDF files into a GRASS GIS Space Time Raster Dataset (STRDS). NetCDF files are expected to follow the CF-convention. Files not adhering to those standards may fail to import.

Input URL(s) to NetCDF files can be provided in the input option as either a file, with one URL to a dataset per line, a comma-separated list of URLs or a single URL. "-" causes input to be taken from stdin.

The module works for both local and remote data (e.g. on a Thredds Server). Data can be imported via r.in.gdal or linked with r.external.

t.rast.import.netcdf can use GDALs Virtual Raster format (VRT) if data's Coordinate Reference system differs from the one of the current location where they are supposed to be imported.

Starting with GRASS GIS version 8.0, different variables or subdatasets in a NetCDF file can be imported as "semantic_label" into one STRDS. To achieve this, a configuration file has to be provided in the semantic_labels option. That configuration file maps subdatasets in the NetCDF file to GRASS GIS semantic_labels. Each line in that file must have the following format: input_netcdf_subdataset=grass_gis_semantic_label The equal sign = is required. If a semantic_labels configuration file is provided, the import of subdatasets is limited to those subdatasets listed in the file. Hence, it can be used to filter variables of interest.

KNOWN ISSUES

The VRT format is also used when linking NetCDF data that contains subdatasets, as subdatasets are currently not supported in r.external.

Reading NetCDF files directly via HTTP protocol (like in the examples below) is currently not supported on MS Windows.

GDAL versions prior to 3.4.1 do not support reading NetCDF files directly via HTTP protocol on newer Linux kernels either. Please make sure to have at least GDAL version 3.4.1 on recent Linux systems. See posts on the GDAL-dev mailing list. for reference.

REQUIREMENTS

Support of semantic_labels is only available with GRASS GIS 8.0 or later. t.rast.import.netcdf uses the following non-standard Python modules:

EXAMPLES

Link Sentinel-2 scenes from the Norwegian Ground Segment

# Choose Scenes to import (see also m.crawl.thredds module)
echo "https://nbstds.met.no/thredds/fileServer/NBS/S2A/2021/02/28/S2A_MSIL1C_20210228T103021_N0202_R108_T35WPU_20210228T201033_DTERRENGDATA.nc
https://nbstds.met.no/thredds/fileServer/NBS/S2A/2021/02/28/S2A_MSIL1C_20210228T103021_N0202_R108_T32VNL_20210228T201033_DTERRENGDATA.nc" > nc.txt

# Create a semantic_label configuration file
echo "B1=S2_1
B2=S2_2" > semantic_labels.conf

# Import data (link NetCDF files without downloading them)
t.rast.import.netcdf -l input=nc.txt output=S2A semantic_labels=semantic_labels.conf \
memory=2048 nprocs=2 nodata="-1"

Import Norwegian Climate data

# Create a semantic_label configuration file
echo "tg=temperature_avg
tn=temperature_min" > semantic_labels.conf

# Import data within a selected time window
t.rast.import.netcdf output=SeNorge semantic_labels=semantic_labels.conf \
memory=2048 nprocs=2 start_time="2020-08-01" end_time="2021-08-01" \
input=https://thredds.met.no/thredds/fileServer/senorge/seNorge_2018/Archive/seNorge2018_2020.nc

Append to STRDS from previous imports

# Choose dataset to import (see also m.crawl.thredds module)

# Create a semantic_label configuration file
echo "tg=temperature_avg
tn=temperature_min" > semantic_labels.conf

# Import data within a selected time window
t.rast.import.netcdf output=SeNorge semantic_labels=semantic_labels.conf \
memory=2048 nprocs=2 -a start_time="2020-08-01" end_time="2021-08-01" \
input=https://thredds.met.no/thredds/fileServer/senorge/seNorge_2018/Archive/seNorge2018_2021.nc

TODO

  1. Capture and store extended metadata in a way that allows for filtering of relevant maps.
  2. Improve printing of metadata and file structure
  3. Support more options of Virtual Raster files (data type, ...)

SEE ALSO

t.rast.import, r3.out.netcdf, r.semantic_labels, i.bands_library, r.support m.crawl.thredds,

AUTHORS

Stefan Blumentrath, Norwegian Institute for Nature Research (NINA), Oslo

SOURCE CODE

Available at: t.rast.import.netcdf source code (history)

Latest change: Monday Oct 17 23:43:06 2022 in commit: bd6388fb24994d4367473f35cbbc8067f64e19f7


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