The ArcGIS Geostatistical Analyst extension provides a broad range of powerful spatial modeling and analysis capabilities. With version 10, Geostatistical Analyst provides improvements in performance and new tools.
There are 11 new geoprocessing tools for Geostatistical Analyst in ArcGIS 10.
Diffusion Interpolation With Barriers uses a kernel that is based on the heat equation and allows you to use a combination of raster and feature datasets to act as barriers.
Kernel Interpolation With Barriers is a moving window predictor that uses the shortest distance between points. The illustration below shows the paths from the data locations (black circles) to the location where a prediction (red square) is required.
Global Polynomial Interpolation is like taking a piece of paper and fitting it between the raised points (raised to the height of value). It is also often referred to as Trend Surface Analysis.
Local Polynomial Interpolation fits many polynomials, each within specified overlapping neighborhoods. New functionality for this tool includes the ability to create a Prediction Standard Error surface and also the inclusion of optimization and diagnostic routines.
IDW interpolation explicitly implements the assumption that things that are close to one another are more alike than those that are farther apart. It weights the points closer to the prediction location greater than those farther away—hence, the name inverse distance weighted.
Radial Basis Functions methods are a series of exact interpolation techniques; that is, the surface must go through each measured sample value.
Create Spatially Balanced Points generates a set of sample points based on a priori inclusion probabilities. The resulting sample design is spatially balanced, meaning that the spatial independence between samples is maximized, making the design more efficient than sampling the study area at random.
Densify Sampling Network is based on a predefined geostatistical kriging layer. It uses, inter alia, the Standard Error of Prediction surface, to determine where new locations are required or which can be removed.
Extract Values to Table extracts the cell values from a set of rasters, based on a point or polygon feature class, to a table. If a point feature class is used, the output table has a record for each point and each raster that has data. Polygonal data is treated as point data; the cell center of the input rasters determines the number of points and is used to decide whether the cell is contained within the polygon or not. This tool can be used to further analyze the results from the Gaussian Geostatistical Simulations tool.
Cross Validation uses the idea of removing one data location and predicting the associated data using the data at the rest of the locations, then repeating this for the remaining locations. In this way, you can compare the predicted value to the observed value and obtain useful information about some of your decisions on the model.
Subset Features employs one of the most rigorous ways to assess the quality of an output surface by comparing the predicted values with those measured in the field. One solution is to divide the original dataset into two parts. One part can be used to model the spatial structure and produce a surface, and the other part can be used to compare and validate the output surface.
The Geostatistical Wizard is a dynamic set of pages that are designed to guide you through the process of constructing and evaluating the performance of an interpolation model.
Geostatistical Analyst Wizard
Example of interpolation methods in the wizard
A new Conditioning measurement error field is added to the Gaussian Geostatistical Simulations tool. It is used when a constant measurement error for all input data can be specified in the input semivariogram model. However, if the measurement error values are not the same at each sampling location, they can be specified using this field.
For example, A quick tour of Geostatistical Analyst has been added.
Introduction to the ArcGIS Geostatistical Analyst Tutorial has been updated.