Good.
For the next function, I think you are trying to use an sp-function
(gridded) on a raster object. You can convert between these, but not
necessarily use the same functions. Use
spgrid = rasterToPoints(YourRaster, spatial = TRUE)
gridded(spgrid) = TRUE
if you want to convert your raster layer to a spatial object.
Best wishes,
Jon
On 8/5/2015 10:00 AM, Anand Sookun wrote:
Dear John
Thanks again.
this time it worked but the variogram is not plotting well and some other
problems croped.
Error in (function (classes, fdef, mtable) :
unable to find an inherited method for function ?gridded? for signature
?"RasterLayer"
I will try by looking closely at the scripts and be back to you soon
Best Wishes
Anand
On Wed, Aug 5, 2015 at 11:36 AM, Jon Skoien <jon.skoien at jrc.ec.europa.eu>
wrote:
Dear Anand
On 8/5/2015 9:03 AM, Anand Sookun wrote:
Dear John
Greetings
I really appreciate your help. Itried what you proposed but got stuck
with the following:
proj4string(carbon_seq) <- CRS("+init=epsg 4326") # epsg-code for
latlong
Error in CRS("+init=epsg 4326") : no colon in init= string
Sorry, there is a : missing, should be
CRS("+init=epsg:4326")
See if it works better!
Jon
Also I TRIED AGAIN
proj4string(carbon_seq) <- CRS("+init=epsg4326") # epsg-code for latlong
Error in (function (classes, fdef, mtable) :
unable to find an inherited method for function ?proj4string<-? for
signature ?"data.frame", "CRS"
I tried with rgdal but got the same eror
Loading required package: rgdal
rgdal: version: 0.8-16, (SVN revision 498)
Geospatial Data Abstraction Library extensions to R successfully loaded
Loaded GDAL runtime: GDAL 1.10.1, released 2013/08/26
Path to GDAL shared files:
C:/Users/Anand/Documents/R/win-library/3.0/rgdal/gdal
GDAL does not use iconv for recoding strings.
Loaded PROJ.4 runtime: Rel. 4.8.0, 6 March 2012, [PJ_VERSION: 480]
Path to PROJ.4 shared files:
C:/Users/Anand/Documents/R/win-library/3.0/rgdal/proj
im attacing the gri file.
Thanks for your time.
CHEERS
ANAND
On Tue, Aug 4, 2015 at 4:55 PM, Jon Skoien <
<jon.skoien at jrc.ec.europa.eu>jon.skoien at jrc.ec.europa.eu> wrote:
Anand,
I could not open your .grd file in R, I think the .gri file is missing.
However, looking at it in a text editor, and comparing with your
R-script, it seems something went wrong with your projections. Your
.csv-file has LatLong coordinates, but you are setting the projection to
"+proj=utm +zone=40 +south +datum=WGS84 +units=m +no_defs +ellps=WGS84
+towgs84=0,0,0", the same as you seem to have in your prediction raster.
But you need to reproject your observations in this case.
# First set the right projection:
proj4string(carbon_seq) <- CRS("+init=epsg4326") # epsg-code for latlong
# Then transform
carbon_seq = spTransform(carbon_seq, CRS("+proj=utm +zone=40 +south
+datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0"))
If you do this, your prediction grid should overlap your observations,
and the colors should reflect your color ramp. What you essentially did
before was to make a prediction thousands of km away from your
observations, and then all values will be the same.
Best wishes,
Jon
On 8/4/2015 12:48 PM, Anand Sookun wrote:
Dear Jon and Roman
Thanks for the reply.
Im attaching the code.
You may be right that the variogram may be problematic but it fitted
well visually.
I think also that the prediction grid was not well created. I wiould be
grateful to have to hints.code how to create a useful grid and also for
the spplot or other alternatives
I can send more info if required.
Cheers
Anand
On Tue, Aug 4, 2015 at 1:39 PM, Jon Skoien <jon.skoien at jrc.ec.europa.eu
<mailto:jon.skoien at jrc.ec.europa.eu>> wrote:
Hi,
You have attached some data, but we still dont know exactly what you
do with the data (do you use the logarithm, how many bins, did you
project the data set...?). However, having had a quick look using
the LatLong coordinates (not really recommended), I can see that the
variogram from this data set is not particularly well defined, and
it could well be that you fitted a model with pure nugget effect. In
that case you will get the same prediction everywhere and no color
differences.
Have a look at
and particularly the summary of var1.pred.
You could also plot the variogram of the data together with your
model, vmf, and see how they fit.
I am not sure what you mean by not being able to create a prediction
grid with data included. Do you mean that you want a grid which
exactly overlays some of the data points? Matching one point should
not be difficult, 2 and 3 should be possible, but you might get some
problems with precision (FAQ 7.31).
Best wishes,
Jon
On 8/3/2015 5:30 PM, Anand Sookun wrote:
Hi
Thank you Roman for your kind response.
The data is as attached which is part of the whole dataset.
My other problem is that im not able to create an appropriate
prediction grid with some data included.
The codes which failed to show colour ramps are
map <- krige(logcarbseq ~ 1, locations = carbon_seq, newdata =
map,model = vmf)
str(map)
print(spplot(map, "var1.pred", asp=1,
col.regions=bpy.colors(64),main="OK prediction, carbon"))
print(spplot(map, "var1.var",col.regions=cm.colors(64),asp=1,
main="OK prediction variance, carbon"))
I look forward to hopefully get some solutions.
Thanks again and warm regards
Anand
On Mon, Aug 3, 2015 at 4:09 PM, Roman Lu?trik
<roman.lustrik at gmail.com <mailto:roman.lustrik at gmail.com>> wrote:
What is the variability of the plotted variable?
Cheers,
Roman
On Sun, Aug 2, 2015 at 11:03 AM, Anand Sookun
<<mailto: <asookun at gmail.com>asookun at gmail.com>
<asookun at gmail.com>asookun at gmail.com
<mailto: <asookun at gmail.com>asookun at gmail.com>> wrote:
Hi
I have kriged my data but the map shows uniform colours -
no gradual
contour colour plot on map
code: print(spplot(k40, "var1.pred", asp=1,
col.regions=bpy.colors(64),main="OK prediction, log-ppm
Zn"))
thnaks for any help
Anand Sookun
--
-------------------------------------------------------
*Anand Sookun (**MPhil. **PhD Candidate, University of
Mauritius)*
*Director cum Freelance Consultant*
*Soft Sustainable Services (Mauritius)*
*Research and Consultancy*
Website: <http://sustain-ability.webs.com/>
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