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Using_Geostatistical_Analyst.pdf
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Contents
1 Welcome to ArcGIS Geostatistical Analyst 1
Exploratory spatial data analysis 2
Semivariogram modeling 3
Surface prediction and error modeling 4
Threshold mapping 5
Model validation and diagnostics 6
Surface prediction using cokriging 7
Tips on learning Geostatistical Analyst 8
2 Quick-start tutorial 11
Introduction to the tutorial 12
Exercise 1: Creating a surface using default parameters 14
Exercise 2: Exploring your data 19
Exercise 3: Mapping ozone concentration 26
Exercise 4: Comparing models 38
Exercise 5: Mapping the probability of ozone exceeding a critical threshold 39
Exercise 6: Producing the final map 42
3 The principles of geostatistical analysis 49
Understanding deterministic methods 50
Understanding geostatistical methods 53
Working through a problem 54
Basic principles behind geostatistical methods 59
Modeling a semivariogram 61
Kriging 74
A guide to the Geostatistical Analyst extension 78
4 Exploratory Spatial Data Analysis 81
What is Exploratory Spatial Data Analysis`? 82
Exploratory Spatial Data Analysis 83
Exploratory Spatial Data Analysis tools 84
Examining the distribution of the data 95
Examining the distribution of your data 98
Looking for global and local outliers 99
Identifying global and local outliers 101
Looking for global trends 103
Looking for global trends 105
Examining spatial autocorrelation and directional variation 106
Examining spatial structure and directional variation 108
Understanding covariation among multiple datasets 109
Understanding spatial covariation among multiple datasets 111
5 Deterministic methods for spatial interpolation
How Inverse Distance Weighted interpolation works 114
Creating a map using ID W 118
How global polynomial interpolation works 120
Creating a map using global polynomial interpolation 122
How local polynomial interpolation works 123
Creating a map using local polynomial interpolation 125
How radial basis functions work 126
Creating a map using RBFs 129
6 Creating a surface with geostatistical techniques
What are geostatistical interpolation techniques? 132
Understanding the different kriging models 133
Understanding output surface types 135
Creating a kriging map using defaults 136
Understanding transformations and trends 137
Understanding ordinary kriging 138
Creating a map using ordinary kriging 139
Understanding simple kriging 143
Creating a map using simple kriging 144
Understanding universal kriging 150
Creating a map using universal kriging 151
Understanding thresholds 153
Understanding indicator kriging 154
Creating a map using indicator kriging 155
Understanding probability kriging 156
Creating a map using probability kriging 157
Understanding disjunctive kriging 159
Creating a map using disjunctive kriging 160
Understanding cokriging 165
Creating a map using cokriging 166
7 Using analytical tools when generating surfaces 167
Investigating spatial structure: variography 168
Modeling semivariograms and covariance functions 175
Determining the neighborhood search size 181
Determining the neighborhood search size 185
Performing cross-validation and validation 189
Performing cross-validation to assess parameter selections 193
Assessing decision protocol using validation 195
Comparing one model with another 197
Comparing one model with another 199
Modeling distributions and determining transformations 200
Using transformations (log, Box-Cox, and arcsine) 204
Using the normal score transformation 205
Checking for the bivariate normal distribution 206
Checking for bivariate distribution 209
linplementing declustering to a山ust for preferential sampling 211
Declustering to a山ust for preferential sampling 214
Removing trends from the data 216
Removing global and local trends from the data: detrending 218
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