Spatial Statistical Analyst Help
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Introduction to SuperGIS Spatial Statistical Analyst
Preface
Definition and Characteristics of Geostatistics
Variography
Parameters of A Typical Variogram
Isotropy and Anisotropy
Variogram Theory Model
The Applications of Geostatistics
Wizard and Estimations
Isotropy and Anisotropy
Variography
Fitting Models
Kriging Estimation
Quick-Start Tutorial
Example 1: Estimate Un-sampled Points with Defaults
Starting SuperGIS and Starting SuperGIS Spatial Statistical Analyst
Setting up the Initial Layer Display in a Project
Adding Layer in a Project
Saving the Project
Estimations of Un-sampled Points with System Defaults
Example 2: Estimate Un-sampled Points with Parameters
Understanding Pointset Trend through Experimental Semivariogram
Experimental Semivariogram Model
Directional Semivariogram
Searching Neighborhood
Cross Validation
Finishing the Map
Example 3: Estimating Probability with Exponential Kriging
Variogram Model
Isotropy and Anisotropy
Semivariogram
Benning
Semivariogram
Experimental Semivariograms with Different Directions
Angle Settings
Variogram Theory Models
Spherical Mode
Exponential Model
Gaussian Model
Kriging Estimation
Kriging Estimation Models
Ordinary Kriging Estimation
Co-Kriging Estimation
Indicator Kriging Estimation
Indicator Function
Indicator Kriging Equations
Indicator Kriging Estimation for the Average Samples of Region A to Be Estimated
Starting Spatial Statistical Analyst
Manipulating Spatial Statistical Analyst
Basic Statistics of Samples
Field Statistics
SuperGIS Spatial Statistical Analysis Tools
Choosing Data to Analyze
Adjusting Data
The Variance Theory Model of Spatial Statistical Analyst
Establishment of A Variogram Model
Parameter Modifications of Variogram Models
Show Search Direction
About Cross-Validation
Finish Analysis
Establishment of Co-Kriging Estimation
Exporting Layer