gstat | 易学教程

Plot a list of lines with R lattice package

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问题 I'm trying to show some variogram model fits on the top of xy.plots . The panel.plots work for all except for a list of lines I wanted to add to corresponding subplots . require(gstat) require(sp) data(meuse) names(meuse) #make directional variograms b<-variogram(log(zinc)~1, meuse, alpha = c(0, 45, 90, 135)) #split the variogram data by direction a<-lapply(1:length(unique(b$dir.hor)), function(i) subset(b, grepl(unique(b$dir.hor)[[i]], b$dir.hor))) #get the model fit parameters for each

Plot a list of lines with R lattice package

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Kriging simulation using ff package

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问题 I'm trying to understand the way I can use the ff package to overcome the error "Error: cannot allocate vector of size 1.1 Mb" while using kriging/ gaussian simulation. I don't know how to change the input data. Is there any idea to help me do that? I'm using the gstat package to perform the simulation as follows: library(sp) data(meuse) coordinates(meuse) = ~x+y data(meuse.grid) gridded(meuse.grid) = ~x+y m <- vgm(.59, "Sph", 874, .04) # ordinary kriging: x <- krige(log(zinc)~1, meuse, meuse

Create variogram in R's gstat package

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问题 Suppose I have rainfall data taken at four weather stations over the span of 2004-2016. I fed the data into a database for retrieval in R. My goal is to take the data for every single day from that period, and krige using those values, repeatedly. So right now my data looks like this, each row corresponds to one of the points, and the columns in order are: lat, long, and rainfall_data. I followed this tutorial: https://rpubs.com/nabilabd/118172, to help me get started. So here's my code so

How to make Ordinary Kriging by using gstat predict

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问题 I am trying to write a code in R that use gstat library in order to create an interpolation. I have already read the gstat manual and based on some examples on internet I had managed to write this code (this is only a part): g <- gstat(id="tec", formula=TEC ~ 1, data=data) ##I create an object v <- variogram(g) # plot the empirical variogram plot(v) mod<-vgm(sill=var(data$TEC),model="Sph",range=200,nugget=200) #create the variogram model v.fit <- fit.variogram(v, model=mod,fit.method=1) #fit

r heatmap on ggmap from kriging data

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问题 I want to plot a heatmap on a ggmap. library(ggmap) turku<-get_map('turku', zoom=13) turkumap<-ggmap(turku, extent="device", legend="topleft") turkumap turkumap+geom_density2d(mapping=aes(x = lon, y = lat),data = test, ) We have made a measurement campaign, so I have 4460 geo-referentiated points. To have a prediction map, I created a grid 400*400, for a total of 160000 points in which I calculate the prediction with kriging. To have a full picture of the phenomenon in my 3 km *3 km i think

Create Grid in R for kriging in gstat

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lat long 7.16 124.21 8.6 123.35 8.43 124.28 8.15 125.08 Consider these coordinates, these coordinates correspond to weather stations that measure rainfall data. The intro to the gstat package in R uses the meuse dataset. At some point in this tutorial: https://rpubs.com/nabilabd/118172 , the guys makes use of a "meuse.grid" in this line of code: data("meuse.grid") I do not have such a file and I do not know how to create it, can I create one using these coordinates? Or at least point me to material that discusses how to create a custom grid for a custom area (i.e not using administrative

Create Grid in R for kriging in gstat

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问题 lat long 7.16 124.21 8.6 123.35 8.43 124.28 8.15 125.08 Consider these coordinates, these coordinates correspond to weather stations that measure rainfall data. The intro to the gstat package in R uses the meuse dataset. At some point in this tutorial: https://rpubs.com/nabilabd/118172, the guys makes use of a "meuse.grid" in this line of code: data("meuse.grid") I do not have such a file and I do not know how to create it, can I create one using these coordinates? Or at least point me to