search for: meuse

...I'm asking: Usually spplot() automatically divides the data into fitting slices and makes a color legend (also automatically). I want to assign the slices myself and have a fixed scale instead of an automatic/dynamic scale. I think what I want gets clear in this example: library(sp) data(meuse.grid) gridded(meuse.grid) = ~x+y ## DATA GENERATION meuse.grid$random <- rnorm(nrow(meuse.grid), 7, 2) # generate random data meuse.grid$random[meuse.grid$random < 0] <- 0 # make sure there is no value is smaller than zero ... meuse.grid$random[meuse.grid$random > 10] <- 10 # and b...

Hi! How does one change the background color of the map-panel in spplot()? Example: library(sp) data(meuse.grid) gridded(meuse.grid) = ~x+y spplot(meuse.grid, "part.a") How would I get another background-color for the map-panel (but not for the whole plot) here? Thank you! Marcel

...on I'm asking: Usually spplot() automatically divides the data into fitting slices and makes a color legend (also automatically). I want to assign the slices myself and have a fixed scale instead of an automatic/dynamic scale. I think what I want gets clear in this example: library(sp) data(meuse.grid) gridded(meuse.grid) = ~x+y ## DATA GENERATION meuse.grid$random <- rnorm(nrow(meuse.grid), 7, 2) # generate random data meuse.grid$random[meuse.grid$random < 0] <- 0 # make sure there is no value is smaller than zero ... meuse.grid$random[meuse.grid$random > 10] <- 10 # and bi...

Dear all can you help me? i have this problem: i have a dataset in a text file in a matrix of 3 columns: x, y, z where x and y are the coordinates and Z are the mesurements. How can i do a variogram with R?

...sp, and uses internally with Spatial* classes from sp if data are provided in the old-fashoned way (as data.frame) + has a vignette to get you started with the classes in sp + defines krige as a generic; two typical uses are: # "old-style", using data.frame's: library(gstat) data(meuse) data(meuse.grid) v = vgm(0.6, "Sph", 900, 0.1) # spherical variogram model zn.kri1 = krige(log(zinc)~1, ~x+y, meuse, meuse.grid, v) image(zn.kri1) # "new-style", using SpatialPointsDataFrame's: coordinates(meuse) = c("x", "y") # promote meuse to Spatial...

...sp, and uses internally with Spatial* classes from sp if data are provided in the old-fashoned way (as data.frame) + has a vignette to get you started with the classes in sp + defines krige as a generic; two typical uses are: # "old-style", using data.frame's: library(gstat) data(meuse) data(meuse.grid) v = vgm(0.6, "Sph", 900, 0.1) # spherical variogram model zn.kri1 = krige(log(zinc)~1, ~x+y, meuse, meuse.grid, v) image(zn.kri1) # "new-style", using SpatialPointsDataFrame's: coordinates(meuse) = c("x", "y") # promote meuse to Spatial...

...ng R-2.13.1 and I have the following packages: - AKIMA - RGDAL - RSAGA - SP I was trying to run the simple example that I found at the following web page: http://spatial-analyst.net/wiki/index.php?title=Export_maps_to_GE The lines that I can run are: data(meuse.grid) coordinates(meuse.grid) <- ~x+y gridded(meuse.grid) <- TRUE proj4string(meuse.grid) = CRS("+init=epsg:28992") # raster to polygon conversion; writeGDAL(meuse.grid["soil"], "meuse_soil.sdat", "SAGA", mvFlag=-99999) rsaga.geoprocessor(lib="shap...

Hello all, A question for plotting of intamap results : Is it possible, and in so, how, to specify the cutoff points for changing colors of plots ? Using the example : data(meuse) meuse$value = log(meuse$zinc) data(meuse.grid) coordinates(meuse) = ~x+y coordinates(meuse.grid) = ~x+y object = interpolate(meuse,meuse.grid,outputWhat = list(mean = TRUE, variance = TRUE, excprob = 7, excprob = 8, quantile = 0.9, quantile = 0.95),methodName = "automap") plot(object) W...

Hi everybody: Could anybody help how I solve the next problem?. I'm doing interpolation maps of tropospheric ozone of my region, and after create it using IDW, and kriging methods, I want from shapefiles (*.shx, *.shp, *.dbf, *.sbx & *.sbn ) create contour over the interpolation maps. Could anybody tell me how do it?. Thanks in advance. ###################################### Antonio

Hi, I would know how to plot two variograms on a same graph. I can plot one by one but I would draw both on the same one. Is it possible? Do i need any special package? Thanks! Cordialement Damien Landais

Hi ALL, With the pakage gstat How can one create a grid of points as in the meuse.grid example, from measuring sites as in the Meuse example Thanks in advance! Alain PONSERO Conservateur Réserve Naturelle de la Baie de Saint-Brieuc site de l'Etoile 22120 HILLION tel/fax : 02.96.32.31.40 <mailto:aponsero@cabri22.com> aponsero@cabri22.com <http://www.reserve...

...ot;gstatVariogram", "data.frame") 3. Compatibility with package sp and variogram maps On http://sourceforge.net/projects/r-spatial/ beta releases for the upcoming package sp are available; sp provides classes and methods for spatial data. Instead of: > library(gstat) > data(meuse) > variogram(zinc~1, ~x+y, meuse) you could, with package sp loaded, do: > coordinates(meuse) = ~x+y # promotes meuse to SpatialDataFrame > variogram(zinc~1, meuse) # no coordinates required. In addition, sp provides classes for gridded data and polygon data. With sp loaded, gstat ca...

...ot;gstatVariogram", "data.frame") 3. Compatibility with package sp and variogram maps On http://sourceforge.net/projects/r-spatial/ beta releases for the upcoming package sp are available; sp provides classes and methods for spatial data. Instead of: > library(gstat) > data(meuse) > variogram(zinc~1, ~x+y, meuse) you could, with package sp loaded, do: > coordinates(meuse) = ~x+y # promotes meuse to SpatialDataFrame > variogram(zinc~1, meuse) # no coordinates required. In addition, sp provides classes for gridded data and polygon data. With sp loaded, gstat ca...

Hello! I have a dataset with the dates and positions - Lat and Long columns How do I make a scatter plot? Do I have to cbind to combine the Lat and Long columns? Any suggestions will be much appreciated! Thank you Julia [[alternative HTML version deleted]]

Hello, I'm using the gstat package within R for an automated procedure that uses ordinary kriging. I can see that there is a logical ("singular") atrtibute of some adjusted model semivariograms: .- attr(*, "singular")= logi TRUE I cannot find documentation about the exact meaning and the implications of this attribute, and I dont know anything about the inner calculations

hello, i do the following in order to get an persp-plot x<-c(2,2,2,2,2,2,3,3,3,3) y<-c(41,41,83,83,124,166,208,208,208,208) z<-c(90366,90366,92240,92240,92240,96473,100995,100995,100995,100995) x<-data$x y<-data$y z<-matrix(data$z,length(y),length(x)) persp(x,y,z, col="gray") but i always get the error message increasing 'x' and 'y' values expected,

Boa Tarde, Estou com problemas para autentica??o de meus computadores no dominio samba. Quando tento pelo pr?prio windows ou na m?o pelo console adicionar uma m?quina ao dominio, ela ? cadastrada com sucesso, ela fica em ou=Computers,dc=xxx,dc=xxx por?m o smbd a procura em people o que resulta que meus usu?rios n?o conseguem logar... assim ... ao inves de o sambra procurar em ou=Computers ele

I downloaded the iid.test, but I can't run it. I get the following message: Error: could not find function "iid.test" Where am I supposed to save this package in order that it works? Thanks, EZ [[alternative HTML version deleted]]

Hi, please help!! I've been trying to fit variogram models using the REML method in the gstat package. Every time the Windows GUI crashes. For example library(gstat) data(meuse) x <- variogram(zinc ~ 1, ~x + y, meuse) v <- vgm(140000, "Sph", 800, nug = 10000) plot(x, model = fit.variogram(x, model = v, fit.method=5)) Other fit methods are non problematic (eg. fit.method=7 for WLS or fit.method=1 for OLS) I've tried the code on Windows XP, 98 and NT...

Hi, I'm using R 2.5.1 and gstat 0.9-39 library and I'm working with the jura data set provided by gstat library. I tried to plot a graph of metal concentrations (let's say Cd) with the command spplot, but I realized that the default lags are equally distributed between Min and Max. I did: library(gstat) data(jura) jura.pred.xy <- jura.pred names(jura.pred.xy)[1:2] <-