# Tag Info

Accepted

### R gstat krige() - Covariance matrix singular at location [5.88,47.4,0]: skipping

This error is commonly returned because you have duplicate locations. You can check this using the sp::zerodist function. To remove duplicate locations you call sp::zerodist within a bracket index. ...
• 31.9k
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### Performing Kriging in QGIS

The great thing about QGIS is its modular design, based on which you can use the geoprocessing engines of various other systems directly as tools in QGIS (GRASS, SAGA, GDAL, OGR, ...). In order to do ...
• 14.7k

### R 'gstat - Warning: singular model in variogram fit

Some has already been said by Spacedman in the comments. This warning may not pose a problem, if the variogram looks good. A good option might be to initialize some of the variogram parameters in vgm(&...
• 708
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### Backtransformation of kriging predictions and variances

When the prediction error of a model based on log(Y) is Gaussian like here, you normally should use the correction of Laurent (1963) to estimate back to the original scale. In your case: MeanY = exp(a\$...
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### How to calculate kriging weights?

Is it true that we're just using a different set of weight values than the 1/distance in IDW? Yes, both IDW interpolation and Ordinary Kriging (OK) will calculate weights based on distance, but with ...
• 10.3k

### Kriging example with sf object

After the study of https://rpubs.com/nabilabd/118172 and https://rpubs.com/nabilabd/134781 I assembled the following solution. library(sf) library(sp) library(gstat) library(tidyverse) Here are ...

### Backtransformation of kriging predictions and variances

A common misconception is that kriging estimates may be simply exponentiated to recover the field values. Sebastien Rochette's suggests a back-transformation for field values y following Laurent (...
• 160

### How to achieve parallel Kriging in R to speed up the process?

This is a simple and reproducible example with meuse dataset of gstat package based on @Spacedman answer and using the parallel package: More info and help here: Parallelizing and clustering in R # ...
• 3,176

### Understanding regression function output in ArcGIS Kriging?

You are correct about value you referred to, the residuals: An excerpt from Esri's Regression analysis basics Residuals: These are the unexplained portion of the dependent variable, represented in ...
• 12.1k
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### Variogram model - SAGA on QGIS Processing

Finally, I found this template in SAGA GUI (2.0.1), in the interactive mode of Ordinary Kriging (global). So a Spherical model can be like: And I got this; [Note] If anybody kindly volunteer to ...
• 31k

### How to calculate kriging weights?

Maybe I should begin by stating that "the summit issue is reflecting how IDW models the surface, rather than weighting". IDW sees the predicted surface as an averaging model, while Spline tries to ...
• 31k
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### Gstat krige() error: Covariance matrix singular at location [917300,3.6109e+06,0]: skipping

This is caused by the matrix library used by gstat. Historically (gstat was released as open source code in 1997) it used the LDLfactor routine in the meschach library. Around 6 months ago I factored ...
• 2,079
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### How to achieve parallel Kriging in R to speed up the process?

Once you've got a variogram fitted then kriging is trivially parallelizable. Kriging predictions are independent of each other. So, divide your prediction points (grid) into N sets, where N is your ...
• 65.4k
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### Kriging using multiple spatial input variables and one spatial output (response) variable

As I stated in the comments, you need values of your explanatory variables at the prediction locations in order to make predictions. Here is a fully reproducible example: library(automap) Make 100 ...
• 65.4k

### Kriging using multiple spatial input variables and one spatial output (response) variable

There are two widely used packages to achieve Kriging interpolation and variogram model fitting in R, these are gstat and geoR. Depending on the package you use, you can build a native gstat object or ...
• 3,176
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### R kriging cross validation returns NA for all prediction points?

The usual problem with kriging is duplicate locations. You can note that even the function autoKrige gives you the following warning: Removed 197 duplicate observation(s) in input_data You can also ...
• 708
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### Extracting the standard error map from autoKrige in R

The krige_output component of kr is a SpatialPixelsDataFrame. Plotting it only shows the first component. The components are: > names(kr\$krige_output) [1] "var1.pred" "var1.var" "var1.stdev" ...
• 65.4k
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### Interpolating DEM using Kriging in R

Try this. It works by converting the raster out to a data frame of x,y,value columns, making a spatial points data frame, extracting the missing and non-missing points, fitting on the non-missing ...
• 65.4k
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### Error in Kriging function

A common problem is when you have duplicate locations. When I tried to add the following line of code before creating a spatial object from t1: ... t1 = t1[which(!duplicated(t1[1:2])), ] coordinates(...
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### Interpolation of river pollution data

I would recommend the Indicator Kriging approach as well. Using indicator kriging to produce a probability or standard error of indicators map assumes an unknown constant mean. In addition, Indicator ...
• 12.1k

### Getting around no data places on Kriging in ArcGIS Desktop?

Assuming this is with just the standard "Kriging" tool of the Spatial Analyst, honestly, the tools in the Interpolation toolset of Spatial Analyst just don't cut it... They lack all kinds of vital ...
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### Why is SAGA kriging slower in QGIS than in SAGA itself?

A lot depends on your desired grid size output. Kriging itself is generally a computationally expensive process due to the numerous calculations that take place. In qgis 2.18 I regularly use the ...
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### Dealing with data which are not normally distributed when kriging?

Usually, it's not good practice to remove outliers, unless you know why they are outliers and have a good justification for the removal. For example, if you know these points were measured incorrectly ...
• 10.3k
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### kriging vs cokriging

Esri provides a good explanation on Understanding Cokriging and things to consider if using this approach. Cokriging uses information on several variable types. The main variable of interest is Z1, ...
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### Unable to Export Kriging Prediction Map

You will not be able to export symbology from the plot function, only the raster(s). This is not a shapefile (polygon, point, line) but rather a raster format. Whereas there are steps to convert to a ...
• 31.9k
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### Kriging for unevenly spaced points using R?

Have you read the help for gstat::krige: newdata: data frame or Spatial object with prediction/simulation locations; should contain attribute columns with the independent ...
• 65.4k
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### How kriging variance is calculated in R gstat?

I think there's a difference in the variogram between the model fitted here with gstat and the one in the linked question. In the linked question, the model is expressed in terms of the covariance as ...
• 65.4k

### Does the sampling design affect the variogram and mapping?

There's massive literature for sampling schemes for spatial interpolation. Here's some thoughts: On 1: yes they will generate different empirical variograms and different kriged maps. But if the ...
• 65.4k