?`rasterFromXYZ` states that "x and y represent spatial coordinates and must be on a regular grid." And, it appears to me that you might be losing values by rounding lon/lat values. The help file further suggests that `rasterize` might be the function you're looking for. List members will (certainly I will) find it more helpful to propose other solutions if you post a small reproducible example of your original georeferenced dataset so that we get an idea of what data you're using.
Sorry, I cannot be of more help. On Wed, Jul 31, 2019 at 10:45 AM Miluji Sb <miluj...@gmail.com> wrote: > Dear all, > > I have georeferenced dataset with multiple variables and years. The data is > at ~100 km (1° × 1°) spatial resolution. I would like to convert this into > a raster. > > I have filtered the data for one year and one variable and did the > following; > > try <- subset(df, year==2010) > try <- try[,c(1,2,4)] > try$lon <- round(try$lon) > try$lat <- round(try$lat) > r_imp <- rasterFromXYZ(try) > > Two issues; is it possible to convert the original dataset with the > multiple variables and years to a raster? If not, how can I avoid rounding > the coordinates? Currently, I get this error "Error in rasterFromXYZ(try) : > x cell sizes are not regular" without rounding. > > Any help will be greatly appreciated. Thank you! > > Sincerely, > > Shouro > > ## Data > df <- structure(list(lon = c(180, 179.762810919291, 179.523658017568, > 179.311342656601, 179.067616041778, 178.851382109362, 178.648816406322, > 178.501097394651, 178.662722495847, 178.860599151485), lat = > c(-16.1529296875, > -16.21659020822, -16.266117894201, -16.393550535614, -16.4457378034442, > -16.561653799838, -16.6533087696649, -16.7741069281329, -16.914110607613, > -16.9049389730284), nsdec = structure(c(1L, 3L, 4L, 5L, 6L, 7L, > 8L, 9L, 10L, 2L), .Label = c("1 of 10", "10 of 10", "2 of 10", > "3 of 10", "4 of 10", "5 of 10", "6 of 10", "7 of 10", "8 of 10", > "9 of 10"), class = "factor"), TWL_5 = c(2.13810426616849, > 2.16767864033646, > 2.16881240361846, 2.20727073247015, 2.27771608519709, 2.3649601141941, > 2.44210984856767, 2.52466349543977, 2.63982954290745, 2.71828906773926 > ), TWL_50 = c(2.38302354555823, 2.43142793944275, 2.45733044901087, > 2.53057109758284, 2.61391337469939, 2.71040967066483, 2.82546443373866, > 2.9709907727849, 3.1785797371187, 3.33227647990861), TWL_95 = > c(2.63753852023063, > 2.7080249053612, 2.75483681166049, 2.86893038433795, 2.97758282474101, > 3.14541928966618, 3.3986143008625, 3.68043269045659, 4.09571655859075, > 4.57299670034984), year = c(2010, 2020, 2030, 2040, 2050, 2060, > 2070, 2080, 2090, 2100)), row.names = c(NA, 10L), class = "data.frame") > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo