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.
Stefano
(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.so...@regione.marche.it
---Oo---------oO----------------
________________________________
Da: Michael Sumner [mdsum...@gmail.com]
Inviato: mercoled� 22 novembre 2017 10.48
A: Sarah Goslee
Cc: Stefano Sofia; r-help@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.gos...@gmail.com<mailto:sarah.gos...@gmail.com>> wrote:
Hi,
You might get more help from the R-sig-geo list, which is devoted to
spatial topics.
However.
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?
Sarah
On Fri, Nov 17, 2017 at 3:40 AM, Stefano Sofia
<stefano.so...@regione.marche.it<mailto:stefano.so...@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.so...@regione.marche.it<mailto:stefano.so...@regione.marche.it>
> ---Oo---------oO----------------
>
--
Sarah Goslee
http://www.functionaldiversity.org
______________________________________________
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--
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Software and Database Engineer
Australian Antarctic Division
203 Channel Highway
Kingston Tasmania 7050 Australia
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