Latest Contributions by EricKrause

Do you have access to Geostatistical Analyst?  If so, using a Smooth search neighborhood will probably correct this. ... View more

You cannot clip geostatistical layers.  However, if you convert your geostatistical layer to a raster with GA Layer to Grid geoprocessing tool, you can clip the raster.  GA Layer to Grid also supports the Mask environmental setting, so you can provide your area of interest as either a feature or a raster. ... View more

Fitting a cokriging model isn't very different than fitting a kriging model, but it will take more time and more work. On the first page of the Geostatistical Wizard, kriging lets you input up to four datasets.  The first dataset is the one you will interpolate, and the other three are cokriging datasets.  In kriging, you fit a single semivariogram.  In cokriging, you will need to fit semivariograms for each dataset and cross-covariance curves between each pair.  At the top of the semivariogram screen, you'll see something that says "Var1 - Var1".  That means you're fitting the semivariogram for the primary dataset.  "Var2 - Var2" is the semivariogram for the second dataset.  "Var1 - Var2" is the cross-covariance curve for the first and second dataset.  With more than two datasets, there will be more combinations.  You'll need to simultaneously fit all of these semivariograms and covariance curves, which can be difficult.  I would definitely recommend using the Optimize Model button to get you started. ... View more

http://video.arcgis.com/watch/2034/using-areal-interpolation-to-perform-polygon_dash_to_dash_polygon-predictions Watch this video tutorial and see if it helps you get started. ... View more

Sorry for taking so long.  I've been busy and had to debug this problem.  You can recreate the defaults from the Geostatistical Wizard by adding one line to your XML file. You should see a line at the top of the XML that says: <model name="Kriging"> Change this line to: <model name="Kriging" optimize = "BySill"> You actually don't need to change any "auto" flags.  This "optimize" flag will override any auto flags, so it doesn't matter if they are false or true. If you want to automate the Optimize Model button in the Geostatistical Wizard, you can change that same line to: <model name="Kriging" optimize = "ByCrossvalidation"> ... View more

Your Python script looks fine.  Can you post your XML file? ... View more

The creation of a new geostatistical layer is the automation: that new geostatistical layer is the result of kriging on the new dataset.  Once you have the geostatistical layer, you can export it to a raster with GA Layer to Grid, or you can predict directly to a point feature class with GA Layer to Points. Now you just need to iterate all your datasets through the Create Geostatistical Layer tool. ... View more

You should change your code to something like: X = arcpy.GeostatisticalDatasets("C:\\temp\\KrigingordinaryJan152.xml")  #Make sure your xml is saved in C:\temp for this to work X.dataset1 = "C:\\temp\\PM04Jan16.shp" #Make sure your shp file is in C:\temp X.dataset1Field = "Y04PMJan16" arcpy.GACreateGeostatisticalLayer_ga("C:\\temp\\KrigingordinaryJan16.xml", X, "PM04Jan16") You can replace the X with any name you want.  The first line creates a GeostatisticalDatasets object called "X".  It populates the necessary properties by reading your XML.  The second line sets the dataset1 property of X.  The third line sets the field for X.  And the last line uses the XML source and the GeostatisticalDatasets object ("X"), and it creates a geostatistical layer called "PM04Jan16". ... View more

Ok, that makes things easier.  We created the GeostatisticalDatasets arcpy class for 10.2, and it will be useful for you.  Here is the general workflow (notice that you don't need to use any XPATH commands): 1.  Manually create an XML model source and change all the auto flags to "true".  (You already did this) 2.  Here is a quick shell of the Python code (replace the file paths and names with your data): newDataset = arcpy.GeostatisticalDatasets("C:\\temp\\myXML.xml") newDataset.dataset1 = "C:\\temp\\myFeatureClass1.shp" newDataset.dataset1Field = "myField1" arcpy.GACreateGeostatisticalLayer_ga("C:\\temp\\myXML.xml", newDataset, "outGALayer1") In the above code, "myXML.xml" is the XML file that you created in step 1.  "newDataset" is the GeostatisticalDatasets object that controls the datasets and fields that you want to interpolate.  The second line sets the dataset1 property to one of your feature classes, and the third line sets the field.  The fourth line creates the new geostatistical layer by using myXML as the model source and the newDataset object as the data.  It then outputs a geostatistical layer called "outGALayer1".  Again, you only need to make the XML file once, and you don't need any XPATH code. 3.  You need to iterate this so that it cycles through the different datasets and fields.  This will create a geostatistical layer for each dataset where the interpolation parameters have been recalculated for each new dataset. ... View more

I see that you're using the Kriging tool from Spatial Analyst.  This tool is not the same as the kriging methods implemented in the Geostatistical Wizard.  If you want to use that tool, it's simple to automate, but it doesn't have advanced options like detrending, transformations, anisotropy, etc.  The workflow I'm describing is about how to automate kriging from the Geostatistical Wizard. I'll talk more about the workflow, but I need to know what version of ArcGIS you have. ... View more

You might be able to convince them with crossvalidation and validation.  EBK typically gives better results, and this is how you can demonstrate it.  Take a couple of your datasets and interpolate them with Ordinary Kriging and EBK and compare the results. ... View more

The Create Geostatistical Layer tool takes a model source as input.  This model source can be a geostatistical layer (either a layer in ArcMap or saved as a .lyr file on disk) or an XML model source.  For your purposes, the XML will be easier to use.  The tool reads all the interpolation parameters from the model source (type of kriging, nugget, range, sill, transformations, etc) and applies them to a new dataset.  This is useful for something like temperature data taken daily.  You can build the model for one day and easily apply that model to each subsequent day. However, if you're using different kinds of data (temperature, elevation, pollution, etc), you don't want to keep using the same model over and over because the interpolation parameters will not fit different types of data.  So, you need to tell the tool to recalculate all these parameters (explained below) for each new dataset.  You only need to manually create one XML file source.  You can do this with the Geostatistical Wizard.  Open the Wizard, choose Ordinary kriging, and give it a dataset.  When you click Finish, the Method Report screen will pop up that shows all the parameters that you used.  Click "Save..." and save the XML file in a convenient location.  You then need to open the XML file with a text editor (Cooktop is a useful and free XML editor, but you can do it with Notepad too).  Inside the XML, you'll see all of the parameters, and most of them will have auto = "false" after them.  This auto flag tells the tool whether to recalculate that parameter or keep it fixed when it is used as a model source.  For every parameter that you want to be recalculated, you need to change the flag to auto = "true" and save the XML.  You only need to do this once, and you'll keep reusing this same model source. You can then set up a loop in Python to iterate through your datasets.  For each dataset, you'll use the XML as the model source in Create Geostatistical Layer.  This will generate a geostatistical layer for each dataset, where the interpolation parameters have been recalculated, and you can use these layers to create the ASCII files that you described in your first post. The difficulty in automating Ordinary/Simple kriging is one of the many reasons we made Empirical Bayesian Kriging as a geoprocessing tool. ... View more

It looks like you only have 8 points.  I would not try to interpolate with such a small dataset.  If Thiessen Polygons are meeting your needs, you should probably stick with that. ... View more

Automation of Ordinary Kriging can be done with a template model and the Create Geostatistical Layer geoprocessing tool.  This blog will take you through the basics, but you'll need to do some extra work: http://blogs.esri.com/esri/arcgis/2010/06/18/automating-geostatistical-interpolation-using-template-layers/ However, you'll need to use a template XML file rather than a geostatistical layer.  You can save this XML file at the end of the Geostatistical Wizard (after you hit Finish, click "Save..." on the Method Report screen).  You'll need to change various "auto" flags in this XML file.  You can change them with the "Set Model Parameter" gp tool, or you can just open the XML file in a text editor and manually change them (this way is probably easier). Read the following topic (be sure to read the whole thing because I make a mistake in my first post): http://forums.arcgis.com/threads/75743-Automatically-generate-anisotropic-semivariogram-parameters The other poster's question was about anisotropic parameters and multiple semivariogram models, so the solution is more complicated that what you need.  See if you can figure it out from those two resources, but I'm happy to help you if you run into any problems. ... View more