Latest Contributions by EricKrause

‎03-14-2013

You'll fit the cross-covariance curve the same way you fit a semivariogram. You'll see empirical covariances (blue crosses), and you need to manipulate the parameters (range, nugget, sill, lag size, etc) to get the curve to go through the crosses as best you can. The first thing to try should be the "Optimize Model" button. Hopefully that will be able to fit everything automatically, though you may want to do some manual tweaking from there. Also, if you're doing external research, the cross-covariance curve is often called a "covariogram."

‎03-13-2013

See my response here: http://forums.arcgis.com/threads/79627-joining-two-datasets-into-one

‎03-13-2013

My recommendation would be to not attempt to merge the two datasets. Instead, perform cokriging. Cokriging will use information from both datasets to make predictions, but it won't assume that the two datasets have the same statistical properties. Even if the two datasets do have identical statistical properties (implying you can safely merge them), you won't lose much by performing cokriging compared to merging the datasets and performing univariate kriging. The only disadvantage is that you will have to estimate two semivariograms and one cross-covariance curve rather than just one semivariogram.

‎03-04-2013

The default cell size is calculated as min(width,height)/250. So, if your default is .000236, setting a cell size of 1 is way too large (the one cell will be many times larger than the entire study area). You shouldn't use a cell size larger than .000236*250 = .059, and if you want more than one cell, you need something a lot smaller. I tested using an enormous cell size in ArcGIS 10.1, and I got the same max/min as you (3.40282e+038 is the maximum value of a floating point), but ArcGIS 10.1 displayed the cell size correctly.

‎03-01-2013

When you talk about the output being between 115.85 and 259.94, is that from a raster or a geostatistical layer? Next, check how many data points have Null values or empty geometry. Any point with Null values or empty geometry will not be used in the calculation.

‎02-28-2013

IDW cannot predict standard errors because it is not a statistical model. You can only predict standard errors (and, hence, average standard error) for statistical models like kriging.

‎02-26-2013

How did you determine that the software isn't using all your points?

‎02-25-2013

Kernel Interpolation with Barriers calculates distances as the shortest distance around the barrier. If two points can be connected with a straight line and the line does not cross a barrier, the distance will not be altered. If a barrier blocks the line connecting two points, the distance between them will be altered to the shortest path around the barrier. In the case of polygon barriers, it may not be possible to go "around" a barrier. In that case, the points do not influence each other.

‎02-11-2013

Glad I could help. You're definitely not the first person to be confused by this.

‎02-11-2013

The thing to understand is that the geostatistical layer is a continuous surface. It has infinite resolution (up to the precision of your computer). The best way to think of a geostatistical layer is that it is a function that takes an (x,y) location and returns a value. It doesn't know its own values until you ask it to calculate them. The contours that you see are drawn from a course grid in order to give an idea what the surface looks like, and the symbology comes from min/max of the input points (since there's no way to calculate a histogram of a continuous surface). When you export to raster, you are calling the function at the center of each cell, and the symbology is based on the histogram of the output raster. If you change the number of points in the horizontal/vertical directions, you will call the function multiple times within each raster cell, and the output cell will be assigned the average of these values. The visual difference between the geostatistical layer and the raster is due entirely to the different contouring and symbology, but they do contain the same values at the same locations.

‎02-11-2013

If you only have 10 points for each day, we do not recommend kriging. No interperpolator is going to be very effective with so few points, but if I had to choose one, I would go with Kernel Interpolation with Barriers. Just don't supply a barrier.

‎02-08-2013

The geostatistical layer and the output raster may look very different, but I assure you that they have the same values at the same locations. Please read this blog and let me know if it still isn't clear. http://blogs.esri.com/esri/arcgis/2008/09/29/understanding-geostatistical-analyst-layers/

‎02-06-2013

Areal interpolation allows you to use one cokriging variable. For the cokriging variable to be effective, it should be highly correlated with the primary variable. You can investigate the correlation with something like a scatterplot. You can input the cokriging variable on the first page of the Geostatistical Wizard. After selecting "Areal Interpolation," you can provide "Dataset" and "Dataset2". "Dataset" is the primary variable, the one you will interpolate. "Dataset2" is the cokriging variable.

‎02-05-2013

That's a tough question to answer. By pure theory, using a cokriging variable won't help with nonstationarity issues, but it is still likely to give better results. A nonstationary variable will make the kriging equations non-optimal. Using a cokriging variable will likely give better results, but the improvement has little to do with the nonstationarity.

‎02-04-2013

The mean and variance of the temperature are two different variables, and one may display spatially autocorrelated residuals while the other doesn't. There may be a physical reason for this, but I don't know what it could be.

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My Ideas

Latest Contributions by EricKrause

Re: joining two datasets into one

Re: Combining two data sets

Re: joining two datasets into one

Re: Kriging export to raster cell size

Re: Kriging issue - not using all my data points

Re: Manual Calculation of Average Standard Error for IDW

Re: Kriging issue - not using all my data points

Re: geostatistical interpolation questions

Re: kriging results to raster

Re: kriging results to raster

Re: geostatistical interpolation questions

Re: kriging results to raster

Re: Interpolation of polygons

Re: Interpolation of polygons

Re: Universal Kriging with External Drift

Re: Why exporting EBK 3D to voxel layer change org...

Re: Access geostatistical layer created using ArcP...

Re: Why exporting EBK 3D to voxel layer change org...

Re: K-Bessel Semivariogram Equation

Re: Kriging Model Types

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