Creating maps using inverse distance weighted interpolation

Inverse distance weighted interpolation assumes that the characteristics of the surface are driven by local variation. IDW works best if the sample points are evenly distributed throughout the area and are not clustered. Important parameters for this method are the power parameter and the search neighborhood specifications (including anisotropy, if it is included as part of the model).

手順:

1. Click the point layer in the ArcMap table of contents that contains the attributes you are interested in.

   Alternatively, go directly to step 2 and browse to the dataset you are interested in on the first page of Geostatistical Wizard.

2. Start Geostatistical Wizard.
3. Under the Methods section, choose Inverse Distance Weighting, which is located under Deterministic Methods.

   The lower portion of Geostatistical Wizard shows information about inverse distance weighted interpolation. There is also a link that will take you directly to more detailed information on inverse distance weighting in the main help system.

4. Under the Input Data section, notice that Source Dataset has been set to the layer you clicked in the ArcMap table of contents. Under Data Field, choose the attribute that you want to interpolate.

   In addition, you can specify a Weight field. This will weigh the data values and alter the interpolated surface. Including a weight can be a useful option when you want to include a measure of confidence in the data (for example, GPS locations taken inside a forest may be less reliable than those taken in clear areas, so you might choose to assign them less weight in the interpolation).

5. Click Next.
6. Modify the Power value, which can vary between 1 and 100.

   Step 2 of Geostatistical Wizard is where the parameter values for this method must be defined. For inverse distance weighting, one of the parameters that you can change is Power. You can investigate the effects of changing the power by examining the preview surface on the left-hand side and evaluating the goodness of fit of the model on the next page of Geostatistical Wizard.

   There is an option to optimize the Power value by clicking the Optimize button . The optimization process evaluates several models and chooses the Power value that gives the model with the lowest root mean square error (see step 9 for more information on cross-validation and error statistics). Note that the search neighborhood is not changed during the optimization process. Adjusting the search neighborhood may lead to a better model and should also be investigated.

7. Adjust the search neighborhood options (refer to Altering the search neighborhood by changing its size and shape and Altering the search neighborhood by changing the number of neighbors to see how to modify the number of neighbors and the shape of the search neighborhood). Anisotropy (directional influences present in the phenomenon that the data represents) can be accounted for at this stage by modifying the Major semiaxis, Minor semiaxis, and Angle parameters.

   Neighborhood type can be changed from Standard to Smooth. In this case, Maximum neighbors, Minimum neighbors, and Sector type are replaced by a smoothing factor, and the method produces a smoother surface. Refer to Smooth interpolation for more details.

8. Click Next.
9. Assess the goodness of fit of the model using the Predicted and Error graphs and the summary information on prediction errors and by examining particular pairs of measured and predicted values in the table on the left-hand side.

   For more information on how to assess the goodness of fit of a model, refer to Performing cross-validation and validation.

10. Once you are satisfied with the model, click Finish. A Method Report window appears.
11. Click OK to produce the surface.

    The Method Report window contains a summary showing the dataset, attribute, interpolation method, and parameter values used to create the surface. This information can be retrieved for any geostatistical layer by right-clicking it in the ArcMap table of contents, choosing Properties from the menu, then clicking the Method Summary tab.

The result is a surface generated by interpolating attribute values using inverse distance weighting. The surface is added directly to the ArcMap table of contents and is displayed using a default color scheme and class breaks, which can be changed by accessing the layer's properties.