• What is • geostatistics? • Geostatistical Analyst? • New in 10+ • Interpolation workflow • Demonstrations • Supplementary information • Questions / Answers
Esri UC2013 . Technical Workshop .
What is geostatistics ?
The statistics of spatially correlated data
Semivariogram Sill
Nugget Range
Esri UC2013 . Technical Workshop .
Semivariogram Semivariogram(distance h) = 0.5 * average [ (valuei– valuej)2]
Esri UC2013 . Technical Workshop .
What is geostatistics ?
The statistics of spatially correlated data
Esri UC2013 . Technical Workshop .
Geostatistical Analyst - Overview •
Interactive -
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Exploratory Spatial Data Analysis tools Variography Kriging Other interpolation methods Cross validation
Experiment conducted by the US EPA 20 years ago Isaaks & Srivastava, 1989. An Introduction to Applied Geostatistics.
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12 independent reputable geostatisticians
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Given the same data
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Asked to perform the same straightforward estimation
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Results were widely different
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Different -
data analysis conclusions variogram models and choice of kriging type searching neighborhoods.
Esri UC2013 . Technical Workshop .
Geostatistical Analyst – Toolbar and Toolbox
Esri UC2013 . Technical Workshop .
Geostatistical Wizard Demonstration
Esri UC2013 . Technical Workshop .
What’s new in 10 – Optimize buttons Local Polynomial Interpolation • Kriging •
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Esri UC2013 . Technical Workshop .
Nugget, partial sill and other(s), are optimized using cross validation with focus on the estimation of the range parameter.
What’s new in 10.0+ •
Areal Interpolation -
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Empirical Bayesian Kriging (EBK) -
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predictions can be made from one set of polygons to another set of polygons builds local models on subsets of the data, which are then combined together to create the final surface.
Normal Score Transformation -
Multiplicative Skewing approximation method
Esri UC2013 . Technical Workshop .
Interpolation workflow •
Exploratory Spatial Data Analysis (ESDA)
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Interpolate -
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estimation of values at unsampled locations based on known values
Exploratory Spatial Data Analysis Where is the data located? • What are the values at the data points? • How does the location of a point relate to its value? •
Esri UC2013 . Technical Workshop .
Exploratory Spatial Data Analysis (ESDA)
Esri UC2013 . Technical Workshop .
Exploratory Spatial Data Analysis (ESDA)
Esri UC2013 . Technical Workshop .
Kriging •
Concepts and Applications of Kriging -
Tuesday 10:15am – 11:30am (room 04)
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Wednesday 3:15pm – 4:30pm (room 04)
Outline • Introduction to kriging • Best practices • Fitting a proper model • Variography, transformations, isotropy, stationarity • Comparing models using cross validation • Interpreting results
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Empirical Bayesian Kriging – Robust kriging as a GP tool -
automates the most difficult aspects of building a valid kriging model
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estimates the semivariogram through repeated simulations
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can handle non-stationary input data. Unlike other kriging methods (use weighted least squares), the semivariogram parameters in EBK are estimated using restricted maximum likelihood (REML). New in ArcGIS 10.1
Requires minimal interactive modeling Allows accurate predictions of non-stationary data More accurate than other kriging methods for small datasets Geoprocessing tool
Disadvantages -
Processing is slower than other kriging methods. Cokriging and anisotropy are unavailable.