getData {raster} | R Documentation |
Get geographic data for anywhere in the world. Data are read from files that are first downloaded if necessary. Function ccodes
returns country names and the ISO codes
getData(name, download=TRUE, path='', ...) ccodes()
name |
Data set name, currently supported are 'GADM', 'countries', 'SRTM', 'alt', and 'worldclim'. See Details for more info |
download |
Logical. If |
path |
Character. Path name indicating where to store the data. Default is the current working directory |
... |
Additional required (!) parameters. These are data set specific. See Details |
'alt' stands for altitude (elevation); the data were aggregated from SRTM 90 m resolution data between -60 and 60 latitude. 'GADM' is a database of global administrative boundaries. 'worldclim' is a database of global interpolated climate data. 'SRTM' refers to the hole-filled CGIAR-SRTM (90 m resolution). 'countries' has polygons for all countries at a higher resolution than the 'wrld_simpl' data in the maptools pacakge .
If name
is 'alt' or 'GADM' you must provide a 'country=' argument. Countries are specified by their 3 letter ISO codes. Use getData('ISO3') to see these codes. In the case of GADM you must also provide the level of administrative subdivision (0=country, 1=first level subdivision). In the case of alt you can set 'mask' to FALSE. If it is TRUE values for neighbouring countries are set to NA. For example:
getData('GADM', country='FRA', level=1)
getData('alt', country='FRA', mask=TRUE)
If name
is 'SRTM' you must provide 'lon' and 'lat' arguments (longitude and latitude). These should be single numbers somewhere within the SRTM tile that you want.
getData('SRTM', lon=5, lat=45)
If name='worldclim'
you must also provide a variable name 'var=', and a resolution 'res='. Valid variables names are 'tmin', 'tmax', 'prec' and 'bio'. Valid resolutions are 0.5, 2.5, 5, and 10 (minutes of a degree). In the case of res=0.5, you must also provide a lon and lat argument for a tile; for the lower resolutions global data will be downloaded. In all cases there are 12 (monthly) files for each variable except for 'bio' which contains 19 files.
getData('worldclim', var='tmin', res=0.5, lon=5, lat=45)
getData('worldclim', var='bio', res=10)
A spatial object (Raster* or Spatial*)