This gridding method uses the kriging method of estimation to create a model of your data. Kriging differs from some of the other gridding methods by bringing out directional influences in your data. Kriging is based on the following assumptions:
* The value for an unknown point can be estimated from neighboring points, but that the unknown point is not necessarily completely dependent upon the values of the known points.
* Variability in the z-values of a data set is a function of two factors: distance and direction. In general, points close together tend to show less variability than points far apart, and in many cases, points along certain bearings will show less variability than equidistant points along a different bearing.
This relationship of variability versus distance can be displayed graphically using a "variogram," which plots the variability of the Z values for point pairs as a function of the distance between the points. Variograms generated for point pairs in different directions show different trends of distance versus variance. RockWorks creates observed variograms of your data, and then finds the variogram model that offers the best fit - thus defining the distance and directional relationships in your data - and uses that equation to interpolate the grid model.
Kriging is one of the most complex modeling methods. To keep your life simple, RockWorks can perform this analysis in an automatic way, finding the optimal point samplings and the best variogram model to use. Or, if you prefer, you can establish the variables manually and generate detailed variograms and reports; these are discussed below.
Advantages: Kriging is a good all-around gridding method, and is excellent at defining directional trends in your data. It can prevent the bull's-eye pattern of Inverse-Distance and the angularity of Triangulation.
Disadvantages: Its complexity, should you opt for Manual settings.
We encourage you to explore the web for kriging reference information (equations, variograms, etc.).
Menu Options
Step-by-Step Summary
- Variography: The first decision to make when using Kriging is whether you want the program to do most of the heavy-lifting ("Automatic") or whether you want full control ("Manual"). Many users find it helpful to run the kriging automatically, with a variety of reports, and then refine the modeling manually.
- Automatic: Click in this radio button if you want the program to set the kriging variables automatically for you (probably the best place to start). When set to Automatic, the program will determine the variogram type to use, based on the type with the highest correlation with your data. It will search the data using a variety of spoke directions and variogram types.
- Manual: Click this button if you prefer to set the kriging variables manually.
- Pre-Grid Points for Variogram: This setting tells RockWorks to first create a regular grid of points (using Inverse-Distance squared) which will then be used for generating the variogram. Keeping this turned on can create better variograms for small data sets. Turning this off can help create a better match between Automatic and Manual settings.
- Edit / Examine Variogram: Check this box to see the interactive Variogram Editor prior to gridding.
- Reporting Options: The second decision to make regarding kriging is what kind of reporting options you wish to use for generating reports and graphs of your data.
- Textual Report: Check this box to generate a textual report that list the various kriging parameters that were used to create the grid model.
- 2D Variogram Matrix: Check this box to generate a detailed diagram that depicts all of the variograms, and a large number of other statistics. (More info)
- Items: Use these check-boxes to select which variogram models you wish to include in the matrix diagram.
- Variograms per Row: Defines the maximum number of variograms to be plotted per row, for each activated variogram type. Default = 10.
(Typically you won't have that many. For a 90 degree spoke spacing, you'd have two variograms per model. For a 45 degree spoke spacing, you'd have 4.)
- Kriging Options:
- Neighbors: Kriging is the process of determining the weights to assign the given data points to minimize the error in grid node assignment, based on the selected variogram. This prompt permits you to specify just how many data points will be used and weighted in estimating the value for a given grid node. A typical value is "6"; the greater the value, the more regional the gridding. The maximum number you can choose is 64. Using more neighbors can result in a smoother, less polygonal model.
The steps that you and the program will follow to create the grid model will depend on the settings you've established, above, but here's a general scenario of what happens when you click the Continue button in the map options window:
- If you've selected Automatic kriging, the program will compute the average minimum and maximum spacing of your control points, to suggest default sampling distance increments and total distance. It will search for point pairs at 90 degree spoke increments using these lag bins, and then at successively smaller spoke increments, pitching bins without a minimum number of samples. It will compute the observed variograms for all spoke samples, and will determine the variogram model that has the best correlation.
- If you've selected Manual kriging, the program will search for point pairs along the spoke and distance increments you've specified, out to the maximum distance, and will compute the observed variograms for these bearings. It will fit the selected variogram model to the data.
- If you have requested to Edit / Examine Variogram, the best-fit variogram model will be displayed, along with a reference range plot. Adjust this as you wish, and click OK. The program will create the grid model using the selected variogram model and settings.
- If you've requested the text report or 2D variogram matix, they will be displayed along with the completed map.
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