What is geostatistics?
The geostatistical workflow
What is the Geostatistical Analyst extension in ArcGIS Pro
Essential vocabulary for Geostatistical Analyst
Get started with Geostatistical Analyst in ArcGIS Pro
An introduction to interpolation methods
Classification trees of the interpolation methods offered in Geostatistical Analyst
Examine the distribution of your data
Box-Cox arcsine and log transformations
Normal score transformation
Comparing normal score transformations to other transformations
Modeling global trends
Analyzing the surface properties of nearby locations
Search neighborhoods
Accounting for directional influences
Smooth interpolation
3D search neighborhoods
What output surface types can the interpolation models generate?
How coincident data are handled
How different input data formats are handled
Parameter optimization
Working with large datasets
Parallel processing with multiple CPUs
Deterministic methods for spatial interpolation
How Global Polynomial Interpolation works
Visualizing Global Polynomial Interpolation
How Local Polynomial Interpolation works
Visualizing Local Polynomial Interpolation
How Inverse Distance Weighted Interpolation works
How Radial Basis Functions work
Visualizing Radial Basis Functions
How Diffusion Interpolation with Barriers works
How Kernel Interpolation with Barriers works
What are geostatistical interpolation techniques?
Understanding geostatistical analysis
Kriging in Geostatistical Analyst
Random processes with dependence
Components of geostatistical models
Empirical semivariogram and covariance functions
Creating empirical semivariograms
Binning empirical semivariograms
Choosing a lag size
Empirical semivariograms for different directions
Semivariogram and covariance functions
Understanding a semivariogram the range sill and nugget
Modeling a semivariogram
Fitting a model to the empirical semivariogram
Combining semivariogram models
Accounting for anisotropy using directional semivariogram and covariance functions
Estimating crosscovariance models for cokriging
Understanding transformations and trends
Understanding how to remove trends from the data
Adjusting for preferential sampling by declustering the data
Bivariate normal distributions
Understanding how to create surfaces using geostatistical techniques
What are the different kriging models?
Understanding ordinary kriging
Understanding simple kriging
Understanding universal kriging
Understanding indicator kriging
Understanding thresholds
Understanding probability kriging
Understanding disjunctive kriging
Understanding cokriging
Understanding measurement error
How Moving Window Kriging works
What is geostatistical simulation?
Key concepts of geostatistical simulation
How Gaussian Geostatistical Simulations works
What is Areal Interpolation
Using areal interpolation to predict to new polygons
What is Empirical Bayesian Kriging?
What is Empirical Bayesian Kriging 3D?
What is EBK Regression Prediction?
Performing cross validation and validation
An introduction to sampling monitoring networks
How Create Spatially Balanced Points works
How Densify Sampling Network works
What is a geostatistical layer?
Geostatistical layers in 3D
Fundamentals of creating a raster from a geostatistical layer