> On Sep 12, 2019, at 9:03 AM, Sarah Goslee wrote:
>
> Creating the NetCDF file is easy - there are multiple packages to do that.
Can I just gently amend this statement. Writing an arbitrary netCDF file is
easy, writing a useful netCDF file is hard. The difference is the first just
Hi,
Without knowing any details of what you did, the general procedure is:
Use your fitted Random Forest or SVM model to predict the class for
each pixel in your region of interest - the predict() function.
Use standard spatial data methods to aggregate the resulting spatial
data, or even
Hi,
Creating the NetCDF file is easy - there are multiple packages to do that.
Everything else you ask about is hard, and not really R questions.
You need to know:
What is the best way to impute missing precipitation data to fit my needs?
What is the best way to grid point-based precipitation
Dear community,
I have a daily time series of precipitation, which I intend to transform it
into a single NetCDF file of daily precipitation. So, first, I would like
to explore the best way to impute missing values, grid the daily values of
the different available weather stations and get daily
After going round in circles most of the day, I finally discovered that the
PROJ_LIB environment variable within my Dockerfile did not match my conda
environment. When I loaded rgdal I saw
Path to PROJ.4 shared files: (autodetected)
in the output and assumed all was OK, but having explicitly
CRAN, btw, reports similar errors on all debian testing platforms, of
the kind
> st_crs("+init=epsg:3857")$epsg
proj_create: init=epsg:/init=IGNF: syntax not supported in non-PROJ4
emulation mode
see
On 9/12/19 10:55 AM, James Sample wrote:
> Thanks Edzer - that's very helpful!
>
> Would it be possible for you to link/share your Ubuntu Dockerfile, please?
> (I completely understand if you'd rather not, of course).
https://github.com/r-spatial/sf/tree/master/inst/docker/gdal
>
> Perhaps
Thanks Edzer - that's very helpful!
Would it be possible for you to link/share your Ubuntu Dockerfile, please?
(I completely understand if you'd rather not, of course).
Perhaps if I can see how you're setting thing up in Ubuntu I can modify my
Jupyter Dockerfile accordingly, and if I can
Dear List,
Please I have carried out an RF and SVM forest cover classification in R. I
want to determine the area in hectors for each of the forest cover classes.
I have not been able to find my way out on it. I wanted to ask if it is
possible to do this in R and will be glad to have assistance
