The cell size and unit for the output rasters. This value can range from 1 to 64, but typical values are between 5 and 15. Using a larger number of neighbors will generally produce more accurate results, but the results take longer to calculate. This parameter controls how many points will be used in the calculation. Predictions are calculated based on neighboring points.

The value can range from 30 to 500, but typical values are between 50 and 200. Larger values will be more stable, but some local effects may be missed. Smaller values will make results more local and can reveal small-scale effects, but it may introduce some instability in the calculations. This parameter controls how many points will be contained in each local model. Interpolate Points works by building local interpolation models that are mixed together to create the final prediction map. If your data does not appear to be normally distributed, you should perform a transformation. Interpolation is most accurate for data that follows a normal (bell-shaped) distribution. By default, the tool will optimize for balance.Ĭhoose whether to transform your data to the normal distribution. This parameter alters the default values of several other parameters of Interpolate Points to optimize speed of calculation, accuracy of results, or a balance of the two. More accurate predictions take longer to calculate. The field must be numeric.Ĭhoose your preference for speed or accuracy. The point features that contains the locations where the values have been measured.Ĭhoose the field whose values you want to interpolate. The parameters for this tool are listed in the following table:Ĭhoose point layer containing locations with known values Points, but many are controlled automatically by

Meteorological applications include prediction of temperatures, rainfall, and associated variables (such as acid rain).Įmpirical Bayesian Kriging tool available with the ArcGIS Geostatistical Analyst extension is used to perform the underlying.

Predict soil nutrient levels (nitrogen, phosphorus, potassium, and so on) and other indicators (such as electrical conductivity) to study their relationships to crop yield and prescribe precise amounts of fertilizer for each location in the field.

Predict heavy metal concentrations in crops based on samples taken from individual plants.

Interpolate Points can be used to predict pollution levels at locations that don't have sensors, such as locations with at-risk populations-schools or hospitals, for example.

An air quality management district has sensors that measure pollution levels.

Some example applications of this tool include the following: Your portal may not be configured for raster analysis, or you may not have the privileges required to run the tool.

If you do not see this tool in Map Viewer, contact your portal administrator. To run this tool, the portal must be configured for raster analysis.

Interpolate points arcgis