r.import - GRASS GIS manual
Author: GRASS Development Team
Description: r.import: Imports raster data into a GRASS raster map using GDAL library and reprojects on the fly.
Keywords: raster, import, projection

## NAME

r.import - Imports raster data into a GRASS raster map using GDAL library and reprojects on the fly.

## KEYWORDS

raster, import, projection

## SYNOPSIS

r.import
r.import --help
r.import [-enlo] input=name [band=integer[,integer,...]] [memory=memory in MB] [output=name] [resample=string] [extent=string] [resolution=string] [resolution_value=float] [title=phrase] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

### Flags:

-e
  Estimate resolution only
-n
  Do not perform region cropping optimization
-l
  Force Lat/Lon maps to fit into geographic coordinates (90N,S; 180E,W)
-o
  Override projection check (use current project's CRS)
  Assume that the dataset has the same coordinate reference system (CRS) as the current project
--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=name [required]
  Name of GDAL dataset to be imported
band=integer[,integer,...]
  Input band(s) to select (default is all bands)
memory=memory in MB
  Maximum memory to be used (in MB)
  Cache size for raster rows
  Default: 300
output=name
  Name for output raster map
resample=string
  Resampling method to use for reprojection
  Options: nearest, bilinear, bicubic, lanczos, bilinear_f, bicubic_f, lanczos_f
  Default: nearest
  nearest: nearest neighbor
  bilinear: bilinear interpolation
  bicubic: bicubic interpolation
  lanczos: lanczos filter
  bilinear_f: bilinear interpolation with fallback
  bicubic_f: bicubic interpolation with fallback
  lanczos_f: lanczos filter with fallback
extent=string
  Output raster map extent
  Options: input, region
  Default: input
  input: extent of input map
  region: extent of current region
resolution=string
  Resolution of output raster map (default: estimated)
  Options: estimated, value, region
  Default: estimated
  estimated: estimated resolution
  value: user-specified resolution
  region: current region resolution
resolution_value=float
  Resolution of output raster map (use with option resolution=value)
title=phrase
  Title for resultant raster map

## DESCRIPTION

r.import imports a map or selected bands from a GDAL raster datasource into the current project (previously called location) and mapset. If the coordinate reference system (CRS) of the input does not match the CRS of the project, the input is reprojected into the current project. If the CRS of the input does match the CRS of the project, the input is imported directly with r.in.gdal.

## NOTES

r.import checks the CRS metadata of the dataset to be imported against the current project's CRS. If not identical a related error message is shown.
To override this projection check (i.e. to use current project's CRS) by assuming that the dataset has the same CRS as the current project the -o flag can be used. This is also useful when geodata to be imported do not contain any CRS metadata at all. The user must be sure that the CRS is identical in order to avoid introducing data errors.

### Resolution

r.import reports the estimated target resolution for each input band. The estimated resolution will usually be some floating point number, e.g. 271.301. In case option resolution is set to estimated (default), this floating point number will be used as target resolution. Since the target resolution should be typically the rounded estimated resolution, e.g. 250 or 300 instead of 271.301, flag -e can be used first to obtain the estimate without importing the raster bands. Then the desired resolution is set with option resolution_value and option resolution=value. For latlong projects, the resolution might be set to arc seconds, e.g. 1, 3, 7.5, 15, and 30 arc seconds are commonly used resolutions.

### Resampling methods

When reprojecting a map to a new spatial reference system, the projected data is resampled with one of four different methods: nearest neighbor, bilinear, bicubic interpolation or lanczos.

In the following, common use cases are:

nearest is the simplest method and the only possible method for categorical data.

bilinear does linear interpolation and provides smoother output than nearest. bilinear is recommended when reprojecting a DEM for hydrological analysis or for surfaces where overshoots must be avoided, e.g. precipitation should not become negative.

bicubic produces smoother output than bilinear, at the cost of overshoots. Here, valid pixels that are adjacent to NULL pixels or edge pixels are set to NULL.

lanczos produces the smoothest output of all methods and preserves contrast best. lanczos is recommended for imagery. Both bicubic and lanczos preserve linear features. With nearest or bilinear, linear features can become zigzag features after reprojection.

In the bilinear, bicubic and lanczos methods, if any of the surrounding cells used to interpolate the new cell value are NULL, the resulting cell will be NULL, even if the nearest cell is not NULL. This will cause some thinning along NULL borders, such as the coasts of land areas in a DEM. The bilinear_f, bicubic_f and lanczos_f interpolation methods can be used if thinning along NULL edges is not desired. These methods "fall back" to simpler interpolation methods along NULL borders. That is, from lanczos to bicubic to bilinear to nearest.

For explanation of the -l flag, please refer to the r.in.gdal manual.

When importing whole-world maps the user should disable map-trimming with the -n flag. For further explanations of -n flag, please refer the to r.proj manual.

## EXAMPLES

### Import of SRTM V3 global data at 1 arc-seconds resolution

The SRTM V3 1 arc-second global data (~30 meters resolution) are available from EarthExplorer (https://earthexplorer.usgs.gov/). The SRTM collections are located under the "Digital Elevation" category.

Example for North Carolina sample dataset (the tile name is "n35_w079_1arc_v3.tif"):

    # set computational region to e.g. 10m elevation model:
    g.region raster=elevation -p

    # Import with reprojection on the fly. Recommended parameters:
    # resample   Resampling method to use for reprojection - bilinear
    # extent     Output raster map extent - region: extent of current region
    # resolution Resolution of output raster map
    #  - region: current region resolution - limit to g.region setting from above
    r.import input=n35_w079_1arc_v3.tif output=srtmv3_resamp10m resample=bilinear \
      extent=region resolution=region title="SRTM V3 resampled to 10m resolution"

    # beautify colors:
    r.colors srtmv3_resamp10m color=elevation

### Import of WorldClim data

Import of a subset from WorldClim Bioclim data set, to be reprojected to current project CRS (North Carolina sample dataset). Different resolutions are available, in this example we use the 2.5 arc-minutes resolution data. During import, we spatially subset the world data to the North Carolina region using the extent parameter:

    # download selected Bioclim data (2.5 arc-minutes resolution)
    # optionally tiles are available for the 30 arc-sec resolution
    wget https://geodata.ucdavis.edu/climate/worldclim/1_4/grid/cur/bio_2-5m_bil.zip

    # extract BIO1 from package (BIO1 = Annual Mean Temperature):
    unzip bio_2-5m_bil.zip bio1.bil bio1.hdr

    # prior to import, fix broken WorldClim extent using GDAL tool
    gdal_translate -a_ullr -180 90 180 -60 bio1.bil bio1_fixed.tif

    # set computational region to North Carolina, 4000 m target pixel resolution
    g.region -d res=4000 -ap

    # subset to current region and reproject on the fly to current project CRS,
    # using -n since whole-world map is imported:
    r.import input=bio1_fixed.tif output=bioclim01 resample=bilinear \
             extent=region resolution=region -n

    # temperature data are in °C * 10
    r.info bioclim01
    r.univar -e bioclim01

## SEE ALSO

r.in.gdal, r.proj

## AUTHORS

Markus Metz
Improvements: Martin Landa, Anna Petrasova

## SOURCE CODE

Available at: r.import source code (history)

Latest change: Tuesday Dec 17 20:17:20 2024 in commit: d962e90c026708a4815ea2b9f46c0e84c17de22d

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© 2003-2025 GRASS Development Team, GRASS GIS 8.4.3dev Reference Manual