Introduction to ArcGIS Geostatistical Analyst

& Fragstats

Represent the DataRepresent the Data

Explore the DataExplore the Data

Fit the ModelFit the Model

Perform DiagnosticsPerform Diagnostics

Compare ModelsCompare Models

Classify the OutputClassify the Output

Assess PatternAssess Pattern

ArcGIS

Using applied geostatistical methods to produce a continuous predictive surface from a discrete collection of sampled points

Using GIS to reclassify the predictive surface into functional classes or bins

Using landscape ecology metrics to assess and quantify the composition and configuration of the classification

Fragstats

Representing the DataRepresenting the Data

Converting data to GIS formatThe first step requires that the data be converted into a format that can be used by the GIS software

How are the data distributed?

Are there global trends in the data?

Exploring the DataExploring the Data

Are there outliers?

“The interpolation techniques used by the software work best with

normally distributed data….”

The semivariogram models the spatial dependence or autocorrelation between measured points. The semivariogram cloud shows ½ the squared difference

between all pairs of points as a function of separation distance (h).

Modeling the semivariogram is the key step between spatial description and spatial prediction.

Choosing the best model or continuous function to fit the empirical semivariogram helps ensure that the predicted values are as accurate as possible.

THE SEMIVARIOGRAM

Anisotropy

Things are more alike for longer distances in some directions than in other

directions

Directional Trends

When fitting a model to the semivariogram it is important to consider…

Set search neighborhood Assess the diagnostic stats

Model the semivariogramAccount for global trendsChoose the method

The ArcGIS Geostatistical Wizard uses a series of steps to calculate a best fit model & create a predictive surface

Fit the ModelFit the Model Perform DiagnosticsPerform Diagnostics

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&

Which model is best?

Compare ModelsCompare Models

Reclassify predictive surface raster into categories or functional groups

Classify the OutputClassify the Output

Assess PatternAssess Pattern

Using metrics of landscape ecology, assess pattern of classified data using Fragstats…

Input = classified input grid Output = spreadsheet of selected metrics