I have a NetCDF file of salinity in Indonesia water with 4 dimensions (lon, lat, depth and time). How to create create weekly composite from my data download data here: https://onedrive.live.com/redir?resid=6FFDD661570C7D0A%21177 output map here: https://onedrive.live.com/redir?resid=6FFDD661570C7D0A%21176
I would like to convert the raster into vector and the use apply to get the mean, but I have problem to plot the vector data using rasterVis
With your example, nor really complicated:
# load needed librairies
library(rasterVis)
# open the data
salinity <- brick("data.nc", varname = "salinity")
salinity
# class : RasterBrick
# dimensions : 61, 61, 3721, 5 (nrow, ncol, ncell, nlayers)
# resolution : 0.08333333, 0.08333333 (x, y)
# extent : 104.9583, 110.0417, -5.041667, 0.04166667 (xmin, xmax, ymin, ymax)
# coord. ref. : +proj=longlat +datum=WGS84
# data source : data.nc
# names : X252331200, X252417600, X252504000, X252590400, X252676800
# z-value : 252331200, 252417600, 252504000, 252590400, 252676800
# varname : salinity
# level : 1
# Calculate the mean
m.salinity <- mean(salinity)
m.salinity
# class : RasterLayer
# dimensions : 61, 61, 3721 (nrow, ncol, ncell)
# resolution : 0.08333333, 0.08333333 (x, y)
# extent : 104.9583, 110.0417, -5.041667, 0.04166667 (xmin, xmax, ymin, ymax)
# coord. ref. : +proj=longlat +datum=WGS84
# data source : in memory
# names : layer
# values : 18.85652, 31.84299 (min, max)