![]() The deterministic methods include IDW (inverse distance weighting), Natural Neighbor, Trend, and Spline. The parameters that are supplied to this method are controlled by the interpolate option. The deterministic interpolation methods assign values to locations based on the surrounding measured values and on specified mathematical formulas that determine the smoothness of the resulting surface. ![]() ![]() This tool uses the Esri Empirical Bayesian Kriging method to perform the interpolation. From 40 points marked, 14 points are accessible and have been plotted. A 95 percent confidence interval can be calculated for the interpolated layer by taking the interpolation value and adding two standard errors for the upper limit and subtracting two standard errors from the lower limit. This study highlights the application of interpolation in ArcGIS spatial analysis. The more accurate the predictions, the slower the results take to calculate and vice versa.Ī layer of standard errors can be created by this tool using the output prediction error option. In the Spatial Analyst toolbox, there are a few toolboxes that will interpolate the points to a surface using various methods. The Interpolate Points tool can be set to optimize speed or accuracy, or a middle ground. It can be used to predict unknown values for any geographic point data, such as elevation, rainfall, chemical concentrations, and noise levels. It is not appropriate for data such as population or median income that change very abruptly over short distances. Interpolate Points is designed to work with data that changes slowly and smoothly over the landscape, like temperature and pollution levels. The input layer must have a numeric field to serve as the basis of the interpolation.
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