You can get more info on the tile extent here. Lets download two more eastern tiles and mosaic them to get the full extent of Austria. boundaries of Austria together with the SRTM Tile in one plot: plot(srtm)Īs you can see, not all of Austria is covered by this tile. The code above will return one SRTM Tile somewhere around Vienna. Specify Lat: The second argument specifies the lat of the SRTM tile.Specify Lon: The second argument specifies the lon of the SRTM tile.‘SRTM’ returns the SRTM 90 elevation data. Select Dataset: The first argument specifies the dataset.We will use the getData() function one last time: srtm <- getData('SRTM', lon=16, lat=48) Last but not least, lets have a look at the SRTM 90 Data. Plot(climate$bio1, main="Annual Mean Temperature") Lets plot the first indicator “Annual Mean Temperature”: #Plot The code above returns a raster with the 18 bioclimate variables covering the whole world with a resoltion of 2.5 minutes of degrees:īIO2 = Mean Diurnal Range (Mean of monthly (max temp – min temp))īIO4 = Temperature Seasonality (standard deviation *100)īIO7 = Temperature Annual Range (BIO5-BIO6)īIO8 = Mean Temperature of Wettest QuarterīIO9 = Mean Temperature of Driest QuarterīIO10 = Mean Temperature of Warmest QuarterīIO11 = Mean Temperature of Coldest QuarterīIO15 = Precipitation Seasonality (Coefficient of Variation) In the case of res=0.5, you must also provide a lon and lat argument for a tile. Specify resolution: 0.5, 2.5, 5, and 10 (minutes of a degree).Select variable: The second argument specifies the variable: ‘tmin’, ‘tmax’, ‘prec’ and ‘bio’ ( more info here).‘worldclim’ returns the World Climate Data. Lets do the same with the World Climate data, here you also have to specify three arguments: climate <- getData('worldclim', var='bio', res=2.5) Lets compare them to the Level 1 subdivision by plotting both of them: #Get DataĪustria0 <- getData('GADM', country="AUT", level=0)Īustria1 <- getData('GADM', country="AUT", level=1) The code above returns the boundaries for Austria for the level 0. Specify level: The third argument specifies the level of of administrative subdivision (0=country, 1=first level subdivision).Select country: The second argument provides the country name of the boundaries by using its ISO A3 country code ( more info here). ‘GADM’ returns the global administrative boundaries. boundaries we have to specify three arguments: install.packages("raster")Īustria0 <- getData('GADM', country='AUT', level=0) To be able to use the getData() function to acquire data about global amd. Install the raster package and load it first.
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