[R] How to produce rainfall maps

Stefano Sofia stefano.sofia at regione.marche.it
Thu Nov 23 09:04:34 CET 2017

Thank you Sarah and Mike for your explanations.
My final objective is to produce maps (png image or any kind of extension I can import in LaTeX) where rainfall data are interpolated, using the Inverse Distance method or Kriging.
My input file (pointfile.csv in the reported example) reports the station code, lat and long of the meteorological station and the rainfall value (which might be the cumulate of a week or ten days or the period I need to investigate). Here a small example:

Station_Code, Init_Year, Init_Month, Init_Day, Init_Hour, Init_Minute, Fin_Year, Fin_Month, Fin_Day, Fin_Hour, Fin_Minute, Rainfall_Cumulate, Long, Lat
1056,  2017 , 11 , 1 , 0 , 0 ,  2017 , 11 , 11 , 0 , 0 ,  28.40, 12.786904,  43.851849
1064,  2017 , 11 , 1 , 0 , 0 ,  2017 , 11 , 11 , 0 , 0 ,  27.20, 12.967556,  43.762669
1072,  2017 , 11 , 1 , 0 , 0 ,  2017 , 11 , 11 , 0 , 0 ,  21.80, 12.897710,  43.907555

As far as I can understand (as you can see, I am not an expert on GIS or any spatial topic)
- my input file pointfile.csv is in "observation-per-row form";
- I need a grid (file.asc) where I can interpolate my rainfall data (I can get it, a resolution of 1km will be enough for me)
- ggplot should produce the map I need; but where are the options for the interpolation method?

Again, any help will be appreciated.

--oOO--( )--OOo----------------
Stefano Sofia PhD
Area Meteorologica e  Area Nivologica - Centro Funzionale
Servizio Protezione Civile - Regione Marche
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.sofia at regione.marche.it
Da: Michael Sumner [mdsumner at gmail.com]
Inviato: mercoledì 22 novembre 2017 10.48
A: Sarah Goslee
Cc: Stefano Sofia; r-help at r-project.org
Oggetto: Re: [R] How to produce rainfall maps

Fwiw the engine behind geom_raster needs explicit observation-per-row form for input (with no structural normalization), so conversion to points is perfectly proper here,  albeit confusing in context. (It's closer to what graphics devices actually use ultimately, but the expansion is laid out very early in ggplot2 because there's no standard for intermediate forms.)

Cheers, Mike

On Wed, 22 Nov 2017, 07:12 Sarah Goslee, <sarah.goslee at gmail.com<mailto:sarah.goslee at gmail.com>> wrote:

You might get more help from the R-sig-geo list, which is devoted to
spatial topics.


The *.asc file is an ArcGIS raster export format. You should use
whatever the appropriate import commands are for your own gridded
rainfall data. If you have a different format, you might or might not
be able to import it directly with raster.

?raster will tell you more about the kinds of formats that function
can handle importing.

I'm not sure what the intent of converting a raster to point data
actually is; if you have point data, then import it as point data. If
you have gridded data, then map it as gridded data. But if it makes
sense to you, then go for it.

The comments in your code sample explain what the CSV file should be:
coordinates of the points to be mapped.

I'm not even certain from your question what your objective is.

What kind of rainfall data are you starting with?
What kind of maps do you want to produce?


On Fri, Nov 17, 2017 at 3:40 AM, Stefano Sofia
<stefano.sofia at regione.marche.it<mailto:stefano.sofia at regione.marche.it>> wrote:
> Dear R users,
> I need to produce rainfall maps using R.
> I know that this is possible, I looked though the web, I found the example below reported (the author is Andrew Tredennick).
> I would ask you if this is the most performing way to make rainfall maps; if yes would someone be able to give me an example of how file.asc and pointfile.csv should be? If no would somebody please show me another way providing a small example?
> Thank you for your help
> Stefano
> library(raster)
> library(ggplot2)
> #open ASCII file using ‘raster’ command, which converts the ASCII to a raster object
> map <- raster(“/your/path/to/file.asc”)
> #convert the raster to points for plotting
> map.p <- rasterToPoints(map)
> #Make the points a dataframe for ggplot
> df <- data.frame(map.p)
> #Make appropriate column headings
> colnames(df) <- c(“Longitude”, “Latitude”, “MAP”)
> #Call in point data, in this case a fake transect (csv file with lat and lon coordinates)
> sites <- data.frame(read.csv(“/your/path/to/pointfile.csv”))
> #Now make the map
> ggplot(data=df, aes(y=Latitude, x=Longitude)) +
> geom_raster(aes(fill=MAP)) +
> geom_point(data=sites, aes(x=x, y=y), color=”white”, size=3, shape=4) +
> theme_bw() +
> coord_equal() +
> scale_fill_gradient(“MAP (mm/yr)”, limits=c(0,2500)) +
> theme(axis.title.x = element_text(size=16),
> axis.title.y = element_text(size=16, angle=90),
> axis.text.x = element_text(size=14),
> axis.text.y = element_text(size=14),
> panel.grid.major = element_blank(),
> panel.grid.minor = element_blank(),
> legend.position = “right”,
> legend.key = element_blank()
> )
>          (oo)
> --oOO--( )--OOo----------------
> Stefano Sofia PhD
> Area Meteorologica e  Area nivologica - Centro Funzionale
> Servizio Protezione Civile - Regione Marche
> Via del Colle Ameno 5
> 60126 Torrette di Ancona, Ancona
> Uff: 071 806 7743
> E-mail: stefano.sofia at regione.marche.it<mailto:stefano.sofia at regione.marche.it>
> ---Oo---------oO----------------

Sarah Goslee

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and provide commented, minimal, self-contained, reproducible code.
Dr. Michael Sumner
Software and Database Engineer
Australian Antarctic Division
203 Channel Highway
Kingston Tasmania 7050 Australia


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