geospatial - Working with irregularly spaced gridded netcdf data in R

Question

I'll be working with modelled air pollution data soon. I've been given some sample data and it looks like the grid is very irregular ('brick' will throw an error about irregular grid), which makes it harder to get it into raster format.

    # load packages ####
    library(ncdf4)
    library(raster)
    library(rgdal)
    library(fields)
    
    # netcdf to data matrix ####
    nc_data <- nc_open('filename.nc')

    cnc_PM2_5       <- ncvar_get(nc_data, attributes(nc_data$var)$names[1])
    longitude       <- ncvar_get(nc_data, "longitude")
    latitude        <- ncvar_get(nc_data, "latitude")
    #time            <- ncvar_get(nc_data, "time")

    # plot matrix, latitude is upside down ####
    image.plot(longitude,rev(latitude), PM2_5, 
               main="PM2_5", ylab="latitude")

    # get quick shapefile for Finland (http://www.diva-gis.org/datadown)####
    finland <- readOGR("FIN_adm4.shp")
    # add map projection
    proj4string(finland) <- CRS("+proj=longlat +datum=WGS84 +init=EPSG:4326")
    helsinki <- finland[finland$NAME_4=="Helsinki",]
    # add Helsinki outline to image.plot
    plot(helsinki, add=TRUE)  

How do I get this irregular data into a spatial object? (SpatialPointsDataFrame or raster)

Reproducible example

    PM25 <- matrix(data=c(4.540674,3.437939,3.373072,2.335204,2.140603,2.529804,
                          4.475807,4.346074,6.42181,3.113605,2.594671,2.854138,
                          3.632539,6.097476,3.308205,5.643409,5.643409,2.140603,
                          4.151473,5.643409,2.529804,2.400071,3.827139,4.994741,
                          3.243339,3.373072,2.075737,2.400071,4.281207,3.697406,
                          2.854138,5.448809,2.075737,3.827139,3.567672,2.854138,
                          4.475807,2.983871,3.697406,5.578542,2.140603,2.20547,
                          6.22721,3.502806,5.773142,4.994741,5.254208,2.594671,
                          3.502806,3.827139,3.502806,2.400071,3.762273,2.724404,
                          3.892006,3.502806,2.724404,2.20547,4.151473,5.838009,
                          6.746144,5.059608,2.140603,2.270337,3.567672,2.140603,
                          3.437939,2.724404,2.140603,3.437939,3.308205,4.994741,
                          4.086606,2.335204,2.140603,5.578542,4.994741,2.724404,
                          3.892006,4.605541,4.281207,4.281207,2.140603,2.529804,
                          3.308205,3.892006,3.697406,3.308205,2.270337,6.097476,
                          3.308205,4.41094,5.319075,4.086606,2.854138,6.162343,
                          2.140603,3.308205,3.048738,4.02174), ncol=10, nrow=10)
    
    # latitude
    latitude <- c(60.1191177368164,60.1192321777344,60.1193504333496,
                          60.1194686889648,60.1195831298828,60.119701385498,
                          60.1198196411133,60.1199340820312,60.1200523376465,
                          60.1201667785645)
    # longitude
    longitude <- c(24.5949993133545,24.595235824585,24.5954704284668,
                          24.5957050323486,24.5959415435791,24.5961761474609,
                          24.5964126586914,24.5966472625732,24.5968818664551,
                          24.5971183776855)
    
    image.plot(longitude,latitude, PM25, main="PM2_5")

question from:https://stackoverflow.com/questions/66047260/working-with-irregularly-spaced-gridded-netcdf-data-in-r

Answer 1

This has now been answered on gis.stackexchange (#386628) by @Spacedman.

see answer here