In pseudocode (I can't find your data set): library(sf) Importantly, you'll need to make sure the layers have the same coordinate reference system. Once you have a stars object in your environment, you can add layers to your ggplot in the same way you'd work with non-spatial data. Within stars is the geom_stars function that allows for rasters to play nice with ggplot2. R <- raster(t(ndvi.slice), xmn=min(lon), xmx=max(lon), ymn=min(lat), ymx=max(lat), crs=CRS('+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs+ towgs84=0,0,0'))Ĭheck out the stars package for manipulating spatiotemporal arrays. Ndvi.array <- ncvar_get(nc_data, 'pr') # store the data in a 3-dimensional arrayįillvalue <- ncatt_get(nc_data, 'pr', '_FillValue') Lat <- ncvar_get(nc_data, 'lat', verbose = F) Library(rgdal) # package for geospatial analysis Library(raster) # package for raster manipulation Library(ncdf4) # package for netcdf manipulation and a global map of the differences in precipitation for that dataset. I want to find out how to zoom in and add a title? Please help! I am so close!Ĭan I manipulate this to put it in ggplot to give me more tools?Įssentially, the goal is: to take a slice of the data (such as time = 1 is January) and have a U.S. The data I'm using can be found ( with variable 'pr', frequency 'mon' and source ID 'EC-Earth3' File -> pr_Amon_EC-Earth3_historical_r1i1p1f1_gr_199801-199812) I am trying to plot a netCDF (.nc) file in R using ggplot to create a map.

Reading cdf files r